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• Big Data – Basics of Big Data Analytics – Day 18 of 21

  - by Pinal Dave

  In yesterday’s blog post we learned the importance of the various components in Big Data Story. In this article we will understand what are the various analytics tasks we try to achieve with the Big Data and the list of the important tools in Big Data Story. When you have plenty of the data around you what is the first thing which comes to your mind? “What do all these data means?” Exactly – the same thought comes to my mind as well. I always wanted to know what all the data means and what meaningful information I can receive out of it. Most of the Big Data projects are built to retrieve various intelligence all this data contains within it. Let us take example of Facebook. When I look at my friends list of Facebook, I always want to ask many questions such as - On which date my maximum friends have a birthday? What is the most favorite film of my most of the friends so I can talk about it and engage them? What is the most liked placed to travel my friends? Which is the most disliked cousin for my friends in India and USA so when they travel, I do not take them there. There are many more questions I can think of. This illustrates that how important it is to have analysis of Big Data. Here are few of the kind of analysis listed which you can use with Big Data. Slicing and Dicing: This means breaking down your data into smaller set and understanding them one set at a time. This also helps to present various information in a variety of different user digestible ways. For example if you have data related to movies, you can use different slide and dice data in various formats like actors, movie length etc. Real Time Monitoring: This is very crucial in social media when there are any events happening and you wanted to measure the impact at the time when the event is happening. For example, if you are using twitter when there is a football match, you can watch what fans are talking about football match on twitter when the event is happening. Anomaly Predication and Modeling: If the business is running normal it is alright but if there are signs of trouble, everyone wants to know them early on the hand. Big Data analysis of various patterns can be very much helpful to predict future. Though it may not be always accurate but certain hints and signals can be very helpful. For example, lots of data can help conclude that if there is lots of rain it can increase the sell of umbrella. Text and Unstructured Data Analysis: unstructured data are now getting norm in the new world and they are a big part of the Big Data revolution. It is very important that we Extract, Transform and Load the unstructured data and make meaningful data out of it. For example, analysis of lots of images, one can predict that people like to use certain colors in certain months in their cloths. Big Data Analytics Solutions There are many different Big Data Analystics Solutions out in the market. It is impossible to list all of them so I will list a few of them over here. Tableau – This has to be one of the most popular visualization tools out in the big data market. SAS – A high performance analytics and infrastructure company IBM and Oracle – They have a range of tools for Big Data Analysis Tomorrow In tomorrow’s blog post we will discuss about very important components of the Big Data Ecosystem – Data Scientist. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• Big Data – What is Big Data – 3 Vs of Big Data – Volume, Velocity and Variety – Day 2 of 21

  - by Pinal Dave

  Data is forever. Think about it – it is indeed true. Are you using any application as it is which was built 10 years ago? Are you using any piece of hardware which was built 10 years ago? The answer is most certainly No. However, if I ask you – are you using any data which were captured 50 years ago, the answer is most certainly Yes. For example, look at the history of our nation. I am from India and we have documented history which goes back as over 1000s of year. Well, just look at our birthday data – atleast we are using it till today. Data never gets old and it is going to stay there forever.  Application which interprets and analysis data got changed but the data remained in its purest format in most cases. As organizations have grown the data associated with them also grew exponentially and today there are lots of complexity to their data. Most of the big organizations have data in multiple applications and in different formats. The data is also spread out so much that it is hard to categorize with a single algorithm or logic. The mobile revolution which we are experimenting right now has completely changed how we capture the data and build intelligent systems.  Big organizations are indeed facing challenges to keep all the data on a platform which give them a  single consistent view of their data. This unique challenge to make sense of all the data coming in from different sources and deriving the useful actionable information out of is the revolution Big Data world is facing. Defining Big Data The 3Vs that define Big Data are Variety, Velocity and Volume. Volume We currently see the exponential growth in the data storage as the data is now more than text data. We can find data in the format of videos, musics and large images on our social media channels. It is very common to have Terabytes and Petabytes of the storage system for enterprises. As the database grows the applications and architecture built to support the data needs to be reevaluated quite often. Sometimes the same data is re-evaluated with multiple angles and even though the original data is the same the new found intelligence creates explosion of the data. The big volume indeed represents Big Data. Velocity The data growth and social media explosion have changed how we look at the data. There was a time when we used to believe that data of yesterday is recent. The matter of the fact newspapers is still following that logic. However, news channels and radios have changed how fast we receive the news. Today, people reply on social media to update them with the latest happening. On social media sometimes a few seconds old messages (a tweet, status updates etc.) is not something interests users. They often discard old messages and pay attention to recent updates. The data movement is now almost real time and the update window has reduced to fractions of the seconds. This high velocity data represent Big Data. Variety Data can be stored in multiple format. For example database, excel, csv, access or for the matter of the fact, it can be stored in a simple text file. Sometimes the data is not even in the traditional format as we assume, it may be in the form of video, SMS, pdf or something we might have not thought about it. It is the need of the organization to arrange it and make it meaningful. It will be easy to do so if we have data in the same format, however it is not the case most of the time. The real world have data in many different formats and that is the challenge we need to overcome with the Big Data. This variety of the data represent  represent Big Data. Big Data in Simple Words Big Data is not just about lots of data, it is actually a concept providing an opportunity to find new insight into your existing data as well guidelines to capture and analysis your future data. It makes any business more agile and robust so it can adapt and overcome business challenges. Tomorrow In tomorrow’s blog post we will try to answer discuss Evolution of Big Data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• The Data Scientist

  - by BuckWoody

  A new term - well, perhaps not that new - has come up and I’m actually very excited about it. The term is Data Scientist, and since it’s new, it’s fairly undefined. I’ll explain what I think it means, and why I’m excited about it. In general, I’ve found the term deals at its most basic with analyzing data. Of course, we all do that, and the term itself in that definition is redundant. There is no science that I know of that does not work with analyzing lots of data. But the term seems to refer to more than the common practices of looking at data visually, putting it in a spreadsheet or report, or even using simple coding to examine data sets. The term Data Scientist (as far as I can make out this early in it’s use) is someone who has a strong understanding of data sources, relevance (statistical and otherwise) and processing methods as well as front-end displays of large sets of complicated data. Some - but not all - Business Intelligence professionals have these skills. In other cases, senior developers, database architects or others fill these needs, but in my experience, many lack the strong mathematical skills needed to make these choices properly. I’ve divided the knowledge base for someone that would wear this title into three large segments. It remains to be seen if a given Data Scientist would be responsible for knowing all these areas or would specialize. There are pretty high requirements on the math side, specifically in graduate-degree level statistics, but in my experience a company will only have a few of these folks, so they are expected to know quite a bit in each of these areas. Persistence The first area is finding, cleaning and storing the data. In some cases, no cleaning is done prior to storage - it’s just identified and the cleansing is done in a later step. This area is where the professional would be able to tell if a particular data set should be stored in a Relational Database Management System (RDBMS), across a set of key/value pair storage (NoSQL) or in a file system like HDFS (part of the Hadoop landscape) or other methods. Or do you examine the stream of data without storing it in another system at all? This is an important decision - it’s a foundation choice that deals not only with a lot of expense of purchasing systems or even using Cloud Computing (PaaS, SaaS or IaaS) to source it, but also the skillsets and other resources needed to care and feed the system for a long time. The Data Scientist sets something into motion that will probably outlast his or her career at a company or organization. Often these choices are made by senior developers, database administrators or architects in a company. But sometimes each of these has a certain bias towards making a decision one way or another. The Data Scientist would examine these choices in light of the data itself, starting perhaps even before the business requirements are created. The business may not even be aware of all the strategic and tactical data sources that they have access to. Processing Once the decision is made to store the data, the next set of decisions are based around how to process the data. An RDBMS scales well to a certain level, and provides a high degree of ACID compliance as well as offering a well-known set-based language to work with this data. In other cases, scale should be spread among multiple nodes (as in the case of Hadoop landscapes or NoSQL offerings) or even across a Cloud provider like Windows Azure Table Storage. In fact, in many cases - most of the ones I’m dealing with lately - the data should be split among multiple types of processing environments. This is a newer idea. Many data professionals simply pick a methodology (RDBMS with Star Schemas, NoSQL, etc.) and put all data there, regardless of its shape, processing needs and so on. A Data Scientist is familiar not only with the various processing methods, but how they work, so that they can choose the right one for a given need. This is a huge time commitment, hence the need for a dedicated title like this one. Presentation This is where the need for a Data Scientist is most often already being filled, sometimes with more or less success. The latest Business Intelligence systems are quite good at allowing you to create amazing graphics - but it’s the data behind the graphics that are the most important component of truly effective displays. This is where the mathematics requirement of the Data Scientist title is the most unforgiving. In fact, someone without a good foundation in statistics is not a good candidate for creating reports. Even a basic level of statistics can be dangerous. Anyone who works in analyzing data will tell you that there are multiple errors possible when data just seems right - and basic statistics bears out that you’re on the right track - that are only solvable when you understanding why the statistical formula works the way it does. And there are lots of ways of presenting data. Sometimes all you need is a “yes” or “no” answer that can only come after heavy analysis work. In that case, a simple e-mail might be all the reporting you need. In others, complex relationships and multiple components require a deep understanding of the various graphical methods of presenting data. Knowing which kind of chart, color, graphic or shape conveys a particular datum best is essential knowledge for the Data Scientist. Why I’m excited I love this area of study. I like math, stats, and computing technologies, but it goes beyond that. I love what data can do - how it can help an organization. I’ve been fortunate enough in my professional career these past two decades to work with lots of folks who perform this role at companies from aerospace to medical firms, from manufacturing to retail. Interestingly, the size of the company really isn’t germane here. I worked with one very small bio-tech (cryogenics) company that worked deeply with analysis of complex interrelated data. So  watch this space. No, I’m not leaving Azure or distributed computing or Microsoft. In fact, I think I’m perfectly situated to investigate this role further. We have a huge set of tools, from RDBMS to Hadoop to allow me to explore. And I’m happy to share what I learn along the way.

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• Project Dashboards

  - by EightyEight

  I'm attempting to create a dashboard so that people not intimately involved with the project can get an indication of project's health. I'm struggling with determining what to put on said dashboard. I think it needs to be brief to be useful, yet complete. The project I'm working on depends on both 3rd party contractors, external hardware and of course my team's effort. Are there any suggestions or guidelines on how to encapsulate it all in a relatively easy manner? Mods, I believe this question falls squarely between development methodologies and business concerns as outlined in the faq. Thank you!

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• VS2010: Warning on add project reference to Silverlight project from .NET project

  - by nlawalker

  In VS2010, Silverlight 4, .NET 4, I've got a WCF service and a Silverlight app, and Silverlight is accessing the class not with Add Service Reference but by sharing the contract. Naturally, this means I have the contract in a Silverlight class library, and the service has a project reference to that library. Strangely, this results in a /!\ icon on the reference, and a warning: The project 'SilverlightClassLibrary1' cannot be referenced. The referenced project is targeted to a different framework family (Silverlight) However, the reference works fine (I can use the interface in my Silverlight app) and builds fine. Is this a bug? My guess is yes, since the warning is lying and also goes away if you add an assembly reference instead of a project reference. I filed a bug and there's more info here as well.

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• Big Data – Beginning Big Data Series Next Month in 21 Parts

  - by Pinal Dave

  Big Data is the next big thing. There was a time when we used to talk in terms of MB and GB of the data. However, the industry is changing and we are now moving to a conversation where we discuss about data in Petabyte, Exabyte and Zettabyte. It seems that the world is now talking about increased Volume of the data. In simple world we all think that Big Data is nothing but plenty of volume. In reality Big Data is much more than just a huge volume of the data. When talking about the data we need to understand about variety and volume along with volume. Though Big data look like a simple concept, it is extremely complex subject when we attempt to start learning the same. My Journey I have recently presented on Big Data in quite a few organizations and I have received quite a few questions during this roadshow event. I have collected all the questions which I have received and decided to post about them on the blog. In the month of October 2013, on every weekday we will be learning something new about Big Data. Every day I will share a concept/question and in the same blog post we will learn the answer of the same. Big Data – Plenty of Questions I received quite a few questions during my road trip. Here are few of the questions. I want to learn Big Data – where should I start? Do I need to know SQL to learn Big Data? What is Hadoop? There are so many organizations talking about Big Data, and every one has a different approach. How to start with big Data? Do I need to know Java to learn about Big Data? What is different between various NoSQL languages. I will attempt to answer most of the questions during the month long series in the next month. Big Data – Big Subject Big Data is a very big subject and I no way claim that I will be covering every single big data concept in this series. However, I promise that I will be indeed sharing lots of basic concepts which are revolving around Big Data. We will discuss from fundamentals about Big Data and continue further learning about it. I will attempt to cover the concept so simple that many of you might have wondered about it but afraid to ask. Your Role! During this series next month, I need your one help. Please keep on posting questions you might have related to big data as blog post comments and on Facebook Page. I will monitor them closely and will try to answer them as well during this series. Now make sure that you do not miss any single blog post in this series as every blog post will be linked to each other. You can subscribe to my feed or like my Facebook page or subscribe via email (by entering email in the blog post). Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Big Data, PostADay, SQL, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• Big Data – Role of Cloud Computing in Big Data – Day 11 of 21

  - by Pinal Dave

  In yesterday’s blog post we learned the importance of the NewSQL. In this article we will understand the role of Cloud in Big Data Story What is Cloud? Cloud is the biggest buzzword around from last few years. Everyone knows about the Cloud and it is extremely well defined online. In this article we will discuss cloud in the context of the Big Data. Cloud computing is a method of providing a shared computing resources to the application which requires dynamic resources. These resources include applications, computing, storage, networking, development and various deployment platforms. The fundamentals of the cloud computing are that it shares pretty much share all the resources and deliver to end users as a service.  Examples of the Cloud Computing and Big Data are Google and Amazon.com. Both have fantastic Big Data offering with the help of the cloud. We will discuss this later in this blog post. There are two different Cloud Deployment Models: 1) The Public Cloud and 2) The Private Cloud Public Cloud Public Cloud is the cloud infrastructure build by commercial providers (Amazon, Rackspace etc.) creates a highly scalable data center that hides the complex infrastructure from the consumer and provides various services. Private Cloud Private Cloud is the cloud infrastructure build by a single organization where they are managing highly scalable data center internally. Here is the quick comparison between Public Cloud and Private Cloud from Wikipedia:   Public Cloud Private Cloud Initial cost Typically zero Typically high Running cost Unpredictable Unpredictable Customization Impossible Possible Privacy No (Host has access to the data Yes Single sign-on Impossible Possible Scaling up Easy while within defined limits Laborious but no limits Hybrid Cloud Hybrid Cloud is the cloud infrastructure build with the composition of two or more clouds like public and private cloud. Hybrid cloud gives best of the both the world as it combines multiple cloud deployment models together. Cloud and Big Data – Common Characteristics There are many characteristics of the Cloud Architecture and Cloud Computing which are also essentially important for Big Data as well. They highly overlap and at many places it just makes sense to use the power of both the architecture and build a highly scalable framework. Here is the list of all the characteristics of cloud computing important in Big Data Scalability Elasticity Ad-hoc Resource Pooling Low Cost to Setup Infastructure Pay on Use or Pay as you Go Highly Available Leading Big Data Cloud Providers There are many players in Big Data Cloud but we will list a few of the known players in this list. Amazon Amazon is arguably the most popular Infrastructure as a Service (IaaS) provider. The history of how Amazon started in this business is very interesting. They started out with a massive infrastructure to support their own business. Gradually they figured out that their own resources are underutilized most of the time. They decided to get the maximum out of the resources they have and hence  they launched their Amazon Elastic Compute Cloud (Amazon EC2) service in 2006. Their products have evolved a lot recently and now it is one of their primary business besides their retail selling. Amazon also offers Big Data services understand Amazon Web Services. Here is the list of the included services: Amazon Elastic MapReduce – It processes very high volumes of data Amazon DynammoDB – It is fully managed NoSQL (Not Only SQL) database service Amazon Simple Storage Services (S3) – A web-scale service designed to store and accommodate any amount of data Amazon High Performance Computing – It provides low-tenancy tuned high performance computing cluster Amazon RedShift – It is petabyte scale data warehousing service Google Though Google is known for Search Engine, we all know that it is much more than that. Google Compute Engine – It offers secure, flexible computing from energy efficient data centers Google Big Query – It allows SQL-like queries to run against large datasets Google Prediction API – It is a cloud based machine learning tool Other Players Besides Amazon and Google we also have other players in the Big Data market as well. Microsoft is also attempting Big Data with the Cloud with Microsoft Azure. Additionally Rackspace and NASA together have initiated OpenStack. The goal of Openstack is to provide a massively scaled, multitenant cloud that can run on any hardware. Thing to Watch The cloud based solutions provides a great integration with the Big Data’s story as well it is very economical to implement as well. However, there are few things one should be very careful when deploying Big Data on cloud solutions. Here is a list of a few things to watch: Data Integrity Initial Cost Recurring Cost Performance Data Access Security Location Compliance Every company have different approaches to Big Data and have different rules and regulations. Based on various factors, one can implement their own custom Big Data solution on a cloud. Tomorrow In tomorrow’s blog post we will discuss about various Operational Databases supporting Big Data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• Numerous Unexpected Obstacles Ruining any Project Plans

  - by Libor

  I am working as software developer and struggling with this problem time and time again for almost thirteen years. There seems not to be any way out of the following problem. And it happens with small projects as well. For example, I plan to write an extension for Microsoft Visual Studio. I dowload learning materials, get some book on the topic and allocate time for learning and development. However, during the development, many seemingly trivial problems arise, for example: Why the script refuses to delete the file? Why Visual Studio does not register the extension? (after two days) OK, it registers it, but now it got broken. How to fix it? each of these "small" obstacles usually take 1-5 days to resolve and the project finally consumes several times more man-hours than planned. Maybe it happens only because I am working on Microsoft platform and many of their Frameworks and architectures are bit confusing and badly documented. I would like to have most problems resolved by finding answer in a book or official documentation (MSDN), but the only answer I usually find is on some weird forum or personal blog googled after desperately searching for any relevant information on the topic. Do you have the same struggles? Do you have techniques on how to prevent these problems? I was thinking of simply multiplying projected time for a given project by some factor, but this does not help. Some projects get done briskly and some take months and the guiding factor here are these small "glitches" which take programmers whole weeks to resolve. I have to admit that lots of these obstacles demoralizes me and drains me of focus and joy of work (who likes to get back to work when he have to resolve some stupid registry problem or weird framework bug instead of doing creative work?) After the project is finally done, I am feeling like dying from thousand cuts.

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• A project idea for project ideas!?

  - by Auxiliary

  First take a look at this question which I asked a few months ago. I still can't find a place where programmers and computer specialists can discuss their projects and ideas. I found OpenHatch.com. It's good but not sufficient, it's only for open-source projects and is not really a place to discuss ideas. OK, so here's an idea, Why don't we make one? The question is do you think there is a need for such a social programmer's lounge? A place where they can discuss their ideas? Do you think it's worth the time and money to start such a website? Do you think it has the potential of getting enough traffic to keep it alive? Many thanks

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• Big Data – Buzz Words: Importance of Relational Database in Big Data World – Day 9 of 21

  - by Pinal Dave

  In yesterday’s blog post we learned what is HDFS. In this article we will take a quick look at the importance of the Relational Database in Big Data world. A Big Question? Here are a few questions I often received since the beginning of the Big Data Series - Does the relational database have no space in the story of the Big Data? Does relational database is no longer relevant as Big Data is evolving? Is relational database not capable to handle Big Data? Is it true that one no longer has to learn about relational data if Big Data is the final destination? Well, every single time when I hear that one person wants to learn about Big Data and is no longer interested in learning about relational database, I find it as a bit far stretched. I am not here to give ambiguous answers of It Depends. I am personally very clear that one who is aspiring to become Big Data Scientist or Big Data Expert they should learn about relational database. NoSQL Movement The reason for the NoSQL Movement in recent time was because of the two important advantages of the NoSQL databases. Performance Flexible Schema In personal experience I have found that when I use NoSQL I have found both of the above listed advantages when I use NoSQL database. There are instances when I found relational database too much restrictive when my data is unstructured as well as they have in the datatype which my Relational Database does not support. It is the same case when I have found that NoSQL solution performing much better than relational databases. I must say that I am a big fan of NoSQL solutions in the recent times but I have also seen occasions and situations where relational database is still perfect fit even though the database is growing increasingly as well have all the symptoms of the big data. Situations in Relational Database Outperforms Adhoc reporting is the one of the most common scenarios where NoSQL is does not have optimal solution. For example reporting queries often needs to aggregate based on the columns which are not indexed as well are built while the report is running, in this kind of scenario NoSQL databases (document database stores, distributed key value stores) database often does not perform well. In the case of the ad-hoc reporting I have often found it is much easier to work with relational databases. SQL is the most popular computer language of all the time. I have been using it for almost over 10 years and I feel that I will be using it for a long time in future. There are plenty of the tools, connectors and awareness of the SQL language in the industry. Pretty much every programming language has a written drivers for the SQL language and most of the developers have learned this language during their school/college time. In many cases, writing query based on SQL is much easier than writing queries in NoSQL supported languages. I believe this is the current situation but in the future this situation can reverse when No SQL query languages are equally popular. ACID (Atomicity Consistency Isolation Durability) – Not all the NoSQL solutions offers ACID compliant language. There are always situations (for example banking transactions, eCommerce shopping carts etc.) where if there is no ACID the operations can be invalid as well database integrity can be at risk. Even though the data volume indeed qualify as a Big Data there are always operations in the application which absolutely needs ACID compliance matured language. The Mixed Bag I have often heard argument that all the big social media sites now a days have moved away from Relational Database. Actually this is not entirely true. While researching about Big Data and Relational Database, I have found that many of the popular social media sites uses Big Data solutions along with Relational Database. Many are using relational databases to deliver the results to end user on the run time and many still uses a relational database as their major backbone. Here are a few examples: Facebook uses MySQL to display the timeline. (Reference Link) Twitter uses MySQL. (Reference Link) Tumblr uses Sharded MySQL (Reference Link) Wikipedia uses MySQL for data storage. (Reference Link) There are many for prominent organizations which are running large scale applications uses relational database along with various Big Data frameworks to satisfy their various business needs. Summary I believe that RDBMS is like a vanilla ice cream. Everybody loves it and everybody has it. NoSQL and other solutions are like chocolate ice cream or custom ice cream – there is a huge base which loves them and wants them but not every ice cream maker can make it just right  for everyone’s taste. No matter how fancy an ice cream store is there is always plain vanilla ice cream available there. Just like the same, there are always cases and situations in the Big Data’s story where traditional relational database is the part of the whole story. In the real world scenarios there will be always the case when there will be need of the relational database concepts and its ideology. It is extremely important to accept relational database as one of the key components of the Big Data instead of treating it as a substandard technology. Ray of Hope – NewSQL In this module we discussed that there are places where we need ACID compliance from our Big Data application and NoSQL will not support that out of box. There is a new termed coined for the application/tool which supports most of the properties of the traditional RDBMS and supports Big Data infrastructure – NewSQL. Tomorrow In tomorrow’s blog post we will discuss about NewSQL. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• To sample or not to sample...

  - by [email protected]

  Ideally, we would know the exact answer to every question. How many people support presidential candidate A vs. B? How many people suffer from H1N1 in a given state? Does this batch of manufactured widgets have any defective parts? Knowing exact answers is expensive in terms of time and money and, in most cases, is impractical if not impossible. Consider asking every person in a region for their candidate preference, testing every person with flu symptoms for H1N1 (assuming every person reported when they had flu symptoms), or destructively testing widgets to determine if they are "good" (leaving no product to sell). Knowing exact answers, fortunately, isn't necessary or even useful in many situations. Understanding the direction of a trend or statistically significant results may be sufficient to answer the underlying question: who is likely to win the election, have we likely reached a critical threshold for flu, or is this batch of widgets good enough to ship? Statistics help us to answer these questions with a certain degree of confidence. This focuses on how we collect data. In data mining, we focus on the use of data, that is data that has already been collected. In some cases, we may have all the data (all purchases made by all customers), in others the data may have been collected using sampling (voters, their demographics and candidate choice). Building data mining models on all of your data can be expensive in terms of time and hardware resources. Consider a company with 40 million customers. Do we need to mine all 40 million customers to get useful data mining models? The quality of models built on all data may be no better than models built on a relatively small sample. Determining how much is a reasonable amount of data involves experimentation. When starting the model building process on large datasets, it is often more efficient to begin with a small sample, perhaps 1000 - 10,000 cases (records) depending on the algorithm, source data, and hardware. This allows you to see quickly what issues might arise with choice of algorithm, algorithm settings, data quality, and need for further data preparation. Instead of waiting for a model on a large dataset to build only to find that the results don't meet expectations, once you are satisfied with the results on the initial sample, you can  take a larger sample to see if model quality improves, and to get a sense of how the algorithm scales to the particular dataset. If model accuracy or quality continues to improve, consider increasing the sample size. Sampling in data mining is also used to produce a held-aside or test dataset for assessing classification and regression model accuracy. Here, we reserve some of the build data (data that includes known target values) to be used for an honest estimate of model error using data the model has not seen before. This sampling transformation is often called a split because the build data is split into two randomly selected sets, often with 60% of the records being used for model building and 40% for testing. Sampling must be performed with care, as it can adversely affect model quality and usability. Even a truly random sample doesn't guarantee that all values are represented in a given attribute. This is particularly troublesome when the attribute with omitted values is the target. A predictive model that has not seen any examples for a particular target value can never predict that target value! For other attributes, values may consist of a single value (a constant attribute) or all unique values (an identifier attribute), each of which may be excluded during mining. Values from categorical predictor attributes that didn't appear in the training data are not used when testing or scoring datasets. In subsequent posts, we'll talk about three sampling techniques using Oracle Database: simple random sampling without replacement, stratified sampling, and simple random sampling with replacement.

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• Project Professional 2010 can't publish existing project file

  - by JL

  I have an existing project file (created in project 2007 professional), opened by me in project professional 2010, and saved. I open this newly saved file, and connect to Project Server (2010) using my credentials (I'm admin), now when I try and publish this existing project, I can't because the button is grayed out. If I start from a blank file, I can publish without any issues (so its not permissions). I suspect something is wrong with the template for this project, but I have no idea what, any idea what to check for?

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• Kipróbálható az ingyenes új Oracle Data Miner 11gR2 grafikus workflow-val

  - by Fekete Zoltán

  Oracle Data Mining technológiai információs oldal. Oracle Data Miner 11g Release 2 - Early Adopter oldal. Megjelent, letöltheto és kipróbálható az Oracle Data Mining, az Oracle adatbányászat új grafikus felülete, az Oracle Data Miner 11gR2. Az Oracle Data Minerhez egyszeruen az SQL Developer-t kell letöltenünk, mivel az adatbányászati felület abból indítható. Az Oracle Data Mining az Oracle adatbáziskezelobe ágyazott adatbányászati motor, ami az Oracle Database Enterprise Edition opciója. Az adatbányászat az adattárházak elemzésének kifinomult eszköze és folyamata. Az Oracle Data Mining in-database-mining elonyeit felvonultatja: - nincs felesleges adatmozgatás, a teljes adatbányászati folyamatban az adatbázisban maradnak az adatok - az adatbányászati modellek is az Oracle adatbázisban vannak - az adatbányászati eredmények, cluster adatok, döntések, valószínuségek, stb. szintén az adatbázisban keletkeznek, és ott közvetlenül elemezhetoek Az új ingyenes Data Miner felület "hatalmas gazdagodáson" ment keresztül az elozo verzióhoz képest. - grafikus adatbányászati workflow szerkesztés és futtatás jelent meg! - továbbra is ingyenes - kibovült a felület - új elemzési lehetoségekkel bovült - az SQL Developer 3.0 felületrol indítható, ez megkönnyíti az adatbányászati funkciók meghívását az adatbázisból, ha épp nem a grafikus felületetet szeretnénk erre használni Az ingyenes Data Miner felület az Oracle SQL Developer kiterjesztéseként érheto el, így az elemzok közvetlenül dolgozhatnak az adatokkal az adatbázisban és a Data Miner grafikus felülettel is, építhetnek és kiértékelhetnek, futtathatnak modelleket, predikciókat tehetnek és elemezhetnek, támogatást kapva az adatbányászati módszertan megvalósítására. A korábbi Oracle Data Miner felület a Data Miner Classic néven fut és továbbra is letöltheto az OTN-rol. Az új Data Miner GUI-ból egy képernyokép: Milyen feladatokra ad megoldási lehetoséget az Oracle Data Mining: - ügyfél viselkedés megjövendölése, prediktálása - a "legjobb" ügyfelek eredményes megcélzása - ügyfél megtartás, elvándorlás kezelés (churn) - ügyfél szegmensek, klaszterek, profilok keresése és vizsgálata - anomáliák, visszaélések felderítése - stb.

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• Setting up a new Silverlight 4 Project with WCF RIA Services

  - by Kevin Grossnicklaus

  Many of my clients are actively using Silverlight 4 and RIA Services to build powerful line of business applications.  Getting things set up correctly is critical to being to being able to take full advantage of the RIA services plumbing and when developers struggle with the setup they tend to shy away from the solution as a whole.  I’m a big proponent of RIA services and wanted to take the opportunity to share some of my experiences in setting up these types of projects.  In late 2010 I presented a RIA Services Master Class here in St. Louis, MO through my firm (ArchitectNow) and the information shared in this post was promised during that presentation. One other thing I want to mention before diving in is the existence of a number of other great posts on this subject.  I’ve learned a lot from many of them and wanted to call out a few of them.  The purpose of my post is to point out some of the gotchas that people get caught up on in the process but I would still encourage you to do as much additional research as you can to find the perfect setup for your needs. Here are a few additional blog posts and articles you should check out on the subject: http://msdn.microsoft.com/en-us/library/ee707351(VS.91).aspx http://adam-thompson.com/post/2010/07/03/Getting-Started-with-WCF-RIA-Services-for-Silverlight-4.aspx Technologies I don’t intend for this post to turn into a full WCF RIA Services tutorial but I did want to point out what technologies we will be using: Visual Studio.NET 2010 Silverlight 4.0 WCF RIA Services for Visual Studio 2010 Entity Framework 4.0 I also wanted to point out that the screenshots came from my personal development box which has a number of additional plug-ins and frameworks loaded so a few of the screenshots might not match 100% with what you see on your own machines. If you do not have Visual Studio 2010 you can download the express version from http://www.microsoft.com/express.  The Silverlight 4.0 tools and the WCF RIA Services components are installed via the Web Platform Installer (http://www.microsoft.com/web/download). Also, the examples given in this post are done in C#…sorry to you VB folks but the concepts are 100% identical. Setting up anew RIA Services Project This section will provide a step-by-step walkthrough of setting up a new RIA services project using a shared DLL for server side code and a simple Entity Framework model for data access.  All projects are created with the consistent ArchitectNow.RIAServices filename prefix and default namespace.  This would be modified to match your companies standards. First, open Visual Studio and open the new project window via File->New->Project.  In the New Project window, select the Silverlight folder in the Installed Templates section on the left and select “Silverlight Application” as your project type.  Verify your solution name and location are set appropriately.  Note that the project name we specified in the example below ends with .Client.  This indicates the name which will be given to our Silverlight project. I consider Silverlight a client-side technology and thus use this name to reflect that.  Click Ok to continue. During the creation on a new Silverlight 4 project you will be prompted with the following dialog to create a new web ASP.NET web project to host your Silverlight content.  As we are demonstrating the setup of a WCF RIA Services infrastructure, make sure the “Enable WCF RIA Services” option is checked and click OK.  Obviously, there are some other options here which have an effect on your solution and you are welcome to look around.  For our example we are going to leave the ASP.NET Web Application Project selected.  If you are interested in having your Silverlight project hosted in an MVC 2 application or a Web Site project these options are available as well.  Also, whichever web project type you select, the name can be modified here as well.  Note that it defaults to the same name as your Silverlight project with the addition of a .Web suffix. At this point, your full Silverlight 4 project and host ASP.NET Web Application should be created and will now display in your Visual Studio solution explorer as part of a single Visual Studio solution as follows: Now we want to add our WCF RIA Services projects to this same solution.  To do so, right-click on the Solution node in the solution explorer and select Add->New Project.  In the New Project dialog again select the Silverlight folder under the Visual C# node on the left and, in the main area of the screen, select the WCF RIA Services Class Library project template as shown below.  Make sure your project name is set appropriately as well.  For the sample below, we will name the project “ArchitectNow.RIAServices.Server.Entities”.   The .Server.Entities suffix we use is meant to simply indicate that this particular project will contain our WCF RIA Services entity classes (as you will see below).  Click OK to continue. Once you have created the WCF RIA Services Class Library specified above, Visual Studio will automatically add TWO projects to your solution.  The first will be an project called .Server.Entities (using our naming conventions) and the other will have the same name with a .Web extension.  The full solution (with all 4 projects) is shown in the image below.  The .Entities project will essentially remain empty and is actually a Silverlight 4 class library that will contain generated RIA Services domain objects.  It will be referenced by our front-end Silverlight project and thus allow for simplified sharing of code between the client and the server.   The .Entities.Web project is a .NET 4.0 class library into which we will put our data access code (via Entity Framework).  This is our server side code and business logic and the RIA Services plumbing will maintain a link between this project and the front end.  Specific entities such as our domain objects and other code we set to be shared will be copied automatically into the .Entities project to be used in both the front end and the back end. At this point, we want to do a little cleanup of the projects in our solution and we will do so by deleting the “Class1.cs” class from both the .Entities project and the .Entities.Web project.  (Has anyone ever intentionally named a class “Class1”?) Next, we need to configure a few references to make RIA Services work.  THIS IS A KEY STEP THAT CAUSES MANY HEADACHES FOR DEVELOPERS NEW TO THIS INFRASTRUCTURE! Using the Add References dialog in Visual Studio, add a project reference from the *.Client project (our Silverlight 4 client) to the *.Entities project (our RIA Services class library).  Next, again using the Add References dialog in Visual Studio, add a project reference from the *.Client.Web project (our ASP.NET host project) to the *.Entities.Web project (our back-end data services DLL).  To get to the Add References dialog, simply right-click on the project you with to add a reference to in the Visual Studio solution explorer and select “Add Reference” from the resulting context menu.  You will want to make sure these references are added as “Project” references to simplify your future debugging.  To reiterate the reference direction using the project names we have utilized in this example thus far:  .Client references .Entities and .Client.Web reference .Entities.Web.  If you have opted for a different naming convention, then the Silverlight project must reference the RIA Services Silverlight class library and the ASP.NET host project must reference the server-side class library. Next, we are going to add a new Entity Framework data model to our data services project (.Entities.Web).  We will do this by right clicking on this project (ArchitectNow.Server.Entities.Web in the above diagram) and selecting Add->New Project.  In the New Project dialog we will select ADO.NET Entity Data Model as in the following diagram.  For now we will call this simply SampleDataModel.edmx and click OK. It is worth pointing out that WCF RIA Services is in no way tied to the Entity Framework as a means of accessing data and any data access technology is supported (as long as the server side implementation maps to the RIA Services pattern which is a topic beyond the scope of this post).  We are using EF to quickly demonstrate the RIA Services concepts and setup infrastructure, as such, I am not providing a database schema with this post but am instead connecting to a small sample database on my local machine.  The following diagram shows a simple EF Data Model with two tables that I reverse engineered from a local data store.   If you are putting together your own solution, feel free to reverse engineer a few tables from any local database to which you have access. At this point, once you have an EF data model generated as an EDMX into your .Entites.Web project YOU MUST BUILD YOUR SOLUTION.  I know it seems strange to call that out but it important that the solution be built at this point for the next step to be successful.  Obviously, if you have any build errors, these must be addressed at this point. At this point we will add a RIA Services Domain Service to our .Entities.Web project (our server side code).  We will need to right-click on the .Entities.Web project and select Add->New Item.  In the Add New Item dialog, select Domain Service Class and verify the name of your new Domain Service is correct (ours is called SampleService.cs in the image below).  Next, click "Add”. After clicking “Add” to include the Domain Service Class in the selected project, you will be presented with the following dialog.  In it, you can choose which entities from the selected EDMX to include in your services and if they should be allowed to be edited (i.e. inserted, updated, or deleted) via this service.  If the “Available DataContext/ObjectContext classes” dropdown is empty, this indicates you have not yes successfully built your project after adding your EDMX.  I would also recommend verifying that the “Generate associated classes for metadata” option is selected.  Once you have selected the appropriate options, click “OK”. Once you have added the domain service class to the .Entities.Web project, the resulting solution should look similar to the following: Note that in the solution you now have a SampleDataModel.edmx which represents your EF data mapping to your database and a SampleService.cs which will contain a large amount of generated RIA Services code which RIA Services utilizes to access this data from the Silverlight front-end.  You will put all your server side data access code and logic into the SampleService.cs class.  The SampleService.metadata.cs class is for decorating the generated domain objects with attributes from the System.ComponentModel.DataAnnotations namespace for validation purposes. FINAL AND KEY CONFIGURATION STEP!  One key step that causes significant headache to developers configuring RIA Services for the first time is the fact that, when we added the EDMX to the .Entities.Web project for our EF data access, a connection string was generated and placed within a newly generated App.Context file within that project.  While we didn’t point it out at the time you can see it in the image above.  This connection string will be required for the EF data model to successfully locate it’s data.  Also, when we added the Domain Service class to the .Entities.Web project, a number of RIA Services configuration options were added to the same App.Config file.   Unfortunately, when we ultimately begin to utilize the RIA Services infrastructure, our Silverlight UI will be making RIA services calls through the ASP.NET host project (i.e. .Client.Web).  This host project has a reference to the .Entities.Web project which actually contains the code so all will pass through correctly EXCEPT the fact that the host project will utilize it’s own Web.Config for any configuration settings.  For this reason we must now merge all the sections of the App.Config file in the .Entities.Web project into the Web.Config file in the .Client.Web project.  I know this is a bit tedious and I wish there were a simpler solution but it is required for our RIA Services Domain Service to be made available to the front end Silverlight project.  Much of this manual merge can be achieved by simply cutting and pasting from App.Config into Web.Config.  Unfortunately, the <system.webServer> section will exist in both and the contents of this section will need to be manually merged.  Fortunately, this is a step that needs to be taken only once per solution.  As you add additional data structures and Domain Services methods to the server no additional changes will be necessary to the Web.Config. Next Steps At this point, we have walked through the basic setup of a simple RIA services solution.  Unfortunately, there is still a lot to know about RIA services and we have not even begun to take advantage of the plumbing which we just configured (meaning we haven’t even made a single RIA services call).  I plan on posting a few more introductory posts over the next few weeks to take us to this step.  If you have any questions on the content in this post feel free to reach out to me via this Blog and I’ll gladly point you in (hopefully) the right direction. Resources Prior to closing out this post, I wanted to share a number or resources to help you get started with RIA services.  While I plan on posting more on the subject, I didn’t invent any of this stuff and wanted to give credit to the following areas for helping me put a lot of these pieces into place.   The books and online resources below will go a long way to making you extremely productive with RIA services in the shortest time possible.  The only thing required of you is the dedication to take advantage of the resources available. Books Pro Business Applications with Silverlight 4 http://www.amazon.com/Pro-Business-Applications-Silverlight-4/dp/1430272074/ref=sr_1_2?ie=UTF8&qid=1291048751&sr=8-2 Silverlight 4 in Action http://www.amazon.com/Silverlight-4-Action-Pete-Brown/dp/1935182374/ref=sr_1_1?ie=UTF8&qid=1291048751&sr=8-1 Pro Silverlight for the Enterprise (Books for Professionals by Professionals) http://www.amazon.com/Pro-Silverlight-Enterprise-Books-Professionals/dp/1430218673/ref=sr_1_3?ie=UTF8&qid=1291048751&sr=8-3 Web Content RIA Services http://channel9.msdn.com/Blogs/RobBagby/NET-RIA-Services-in-5-Minutes http://silverlight.net/riaservices/ http://www.silverlight.net/learn/videos/all/net-ria-services-intro/ http://www.silverlight.net/learn/videos/all/ria-services-support-visual-studio-2010/ http://channel9.msdn.com/learn/courses/Silverlight4/SL4BusinessModule2/SL4LOB_02_01_RIAServices http://www.myvbprof.com/MainSite/index.aspx#/zSL4_RIA_01 http://channel9.msdn.com/blogs/egibson/silverlight-firestarter-ria-services http://msdn.microsoft.com/en-us/library/ee707336%28v=VS.91%29.aspx Silverlight www.silverlight.net http://msdn.microsoft.com/en-us/silverlight4trainingcourse.aspx http://channel9.msdn.com/shows/silverlighttv

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• Big Data – Operational Databases Supporting Big Data – RDBMS and NoSQL – Day 12 of 21

  - by Pinal Dave

  In yesterday’s blog post we learned the importance of the Cloud in the Big Data Story. In this article we will understand the role of Operational Databases Supporting Big Data Story. Even though we keep on talking about Big Data architecture, it is extremely crucial to understand that Big Data system can’t just exist in the isolation of itself. There are many needs of the business can only be fully filled with the help of the operational databases. Just having a system which can analysis big data may not solve every single data problem. Real World Example Think about this way, you are using Facebook and you have just updated your information about the current relationship status. In the next few seconds the same information is also reflected in the timeline of your partner as well as a few of the immediate friends. After a while you will notice that the same information is now also available to your remote friends. Later on when someone searches for all the relationship changes with their friends your change of the relationship will also show up in the same list. Now here is the question – do you think Big Data architecture is doing every single of these changes? Do you think that the immediate reflection of your relationship changes with your family member is also because of the technology used in Big Data. Actually the answer is Facebook uses MySQL to do various updates in the timeline as well as various events we do on their homepage. It is really difficult to part from the operational databases in any real world business. Now we will see a few of the examples of the operational databases. Relational Databases (This blog post) NoSQL Databases (This blog post) Key-Value Pair Databases (Tomorrow’s post) Document Databases (Tomorrow’s post) Columnar Databases (The Day After’s post) Graph Databases (The Day After’s post) Spatial Databases (The Day After’s post) Relational Databases We have earlier discussed about the RDBMS role in the Big Data’s story in detail so we will not cover it extensively over here. Relational Database is pretty much everywhere in most of the businesses which are here for many years. The importance and existence of the relational database are always going to be there as long as there are meaningful structured data around. There are many different kinds of relational databases for example Oracle, SQL Server, MySQL and many others. If you are looking for Open Source and widely accepted database, I suggest to try MySQL as that has been very popular in the last few years. I also suggest you to try out PostgreSQL as well. Besides many other essential qualities PostgreeSQL have very interesting licensing policies. PostgreSQL licenses allow modifications and distribution of the application in open or closed (source) form. One can make any modifications and can keep it private as well as well contribute to the community. I believe this one quality makes it much more interesting to use as well it will play very important role in future. Nonrelational Databases (NOSQL) We have also covered Nonrelational Dabases in earlier blog posts. NoSQL actually stands for Not Only SQL Databases. There are plenty of NoSQL databases out in the market and selecting the right one is always very challenging. Here are few of the properties which are very essential to consider when selecting the right NoSQL database for operational purpose. Data and Query Model Persistence of Data and Design Eventual Consistency Scalability Though above all of the properties are interesting to have in any NoSQL database but the one which most attracts to me is Eventual Consistency. Eventual Consistency RDBMS uses ACID (Atomicity, Consistency, Isolation, Durability) as a key mechanism for ensuring the data consistency, whereas NonRelational DBMS uses BASE for the same purpose. Base stands for Basically Available, Soft state and Eventual consistency. Eventual consistency is widely deployed in distributed systems. It is a consistency model used in distributed computing which expects unexpected often. In large distributed system, there are always various nodes joining and various nodes being removed as they are often using commodity servers. This happens either intentionally or accidentally. Even though one or more nodes are down, it is expected that entire system still functions normally. Applications should be able to do various updates as well as retrieval of the data successfully without any issue. Additionally, this also means that system is expected to return the same updated data anytime from all the functioning nodes. Irrespective of when any node is joining the system, if it is marked to hold some data it should contain the same updated data eventually. As per Wikipedia - Eventual consistency is a consistency model used in distributed computing that informally guarantees that, if no new updates are made to a given data item, eventually all accesses to that item will return the last updated value. In other words -  Informally, if no additional updates are made to a given data item, all reads to that item will eventually return the same value. Tomorrow In tomorrow’s blog post we will discuss about various other Operational Databases supporting Big Data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• Postgres user drop

  - by Grasper

  I am trying to drop a user: drop user testUser; I want to force this to work in a simple manner (Not a million calls)... How can I do this easily? I get this output: ERROR: role "testUser" cannot be dropped because some objects depend on it DETAIL: access to table main.tap_db_version access to table main.user_instance access to table main.target_type access to table main.status_code access to table main.state_space_profile access to table main.service_subscription access to table main.service_instance access to table main.sa_ordnance_weapon_type access to table main.operation access to table main.mission_class access to table main.map_symbol access to table main.ada_weapon_type access to table main.active_process access to table main.acft_type_00_only access to table main.abp_create_params access to table main.exercise access to table main.decl access to table main.data_set access to table main.cancellation_notice access to table main.ato_family_tree access to table main.apportionment_cat_cd access to table main.abp access to table main.alert_settings access to table main.alert_log access to table main.airspace_usage_category access to schema main access to view testUser.top_priority access to view testUser.target_ssm_msn_count access to view testUser.target_air_msn_count access to view testUser.sortie_sum access to view testUser.ref_info access to view testUser.preview_rmk_count access to view testUser.preview_pgm_las_count access to view testUser.preview_pgm_desi_count access to view testUser.preview_objective_count access to view testUser.preview_gfriend_count access to view testUser.preview_escort_msn_req access to view testUser.preview_chaff_data access to view testUser.preview_airmove_seg access to view testUser.preview_aircraft_total access to view testUser.offload_total access to view testUser.objective_count access to view testUser.fuel_planned access to view testUser.ew_data access to view testUser.dual access to view testUser.current_base_inventory access to view testUser.cell_total access to view testUser.asgn_sortie_sum access to view testUser.appor_sorties_planned access to view testUser.airmove_seg access to view testUser.aircraft_total access to view testUser.abp access to table testUser.req_msn_task access to table testUser.req_task_source_req access to table testUser.req_ssm_msn access to table testUser.req_ssm_source access to table testUser.req_msn access to table testUser.req_msn_warnings access to table testUser.req_air_msn access to table testUser.req_src_header access to table testUser.req_msn_ids access to table testUser.req_msn_comment access to table testUser.req_c2_msn access to table testUser.req_c2_source access to table testUser.req_ada_msn access to table testUser.req_ada_vertex access to table testUser.weather_forecast access to table testUser.weather_coords access to table testUser.weather_area access to table testUser.weapon_option access to table testUser.wag_activity access to table testUser.unit_remark access to table testUser.unit_location_turn access to table testUser.unit_iff access to table testUser.unit_coordination access to table testUser.unit_code access to table testUser.trace_point access to table testUser.tasking_agency access to table testUser.task_unit access to table testUser.target_type access to table testUser.tap_db_version access to table testUser.status_code access to table testUser.state_space_threat access to table testUser.state_space_profile access to table testUser.state_space access to table testUser.ssm_mission access to table testUser.spins_section_id access to table testUser.spins_codes access to table testUser.spins access to table testUser.unit_location access to table testUser.ship_target_request access to table testUser.service_subscription access to table testUser.service_instance access to table testUser.sa_ordnance_weapon_type access to table testUser.runway access to table testUser.restricted_codes access to table testUser.response_entity access to table testUser.residual_mission access to table testUser.request_objective access to table testUser.request and 194 other objects (see server log for list)

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• Postgres user/role drop

  - by Grasper

  I am trying to drop a user: drop user testUser; I want to force this to work in a simple manner (Not a million calls)... How can I do this easily? I get this output: ERROR: role "testUser" cannot be dropped because some objects depend on it DETAIL: access to table main.tap_db_version access to table main.user_instance access to table main.target_type access to table main.status_code access to table main.state_space_profile access to table main.service_subscription access to table main.service_instance access to table main.sa_ordnance_weapon_type access to table main.operation access to table main.mission_class access to table main.map_symbol access to table main.ada_weapon_type access to table main.active_process access to table main.acft_type_00_only access to table main.abp_create_params access to table main.exercise access to table main.decl access to table main.data_set access to table main.cancellation_notice access to table main.ato_family_tree access to table main.apportionment_cat_cd access to table main.abp access to table main.alert_settings access to table main.alert_log access to table main.airspace_usage_category access to schema main access to view testUser.top_priority access to view testUser.target_ssm_msn_count access to view testUser.target_air_msn_count access to view testUser.sortie_sum access to view testUser.ref_info access to view testUser.preview_rmk_count access to view testUser.preview_pgm_las_count access to view testUser.preview_pgm_desi_count access to view testUser.preview_objective_count access to view testUser.preview_gfriend_count access to view testUser.preview_escort_msn_req access to view testUser.preview_chaff_data access to view testUser.preview_airmove_seg access to view testUser.preview_aircraft_total access to view testUser.offload_total access to view testUser.objective_count access to view testUser.fuel_planned access to view testUser.ew_data access to view testUser.dual access to view testUser.current_base_inventory access to view testUser.cell_total access to view testUser.asgn_sortie_sum access to view testUser.appor_sorties_planned access to view testUser.airmove_seg access to view testUser.aircraft_total access to view testUser.abp access to table testUser.req_msn_task access to table testUser.req_task_source_req access to table testUser.req_ssm_msn access to table testUser.req_ssm_source access to table testUser.req_msn access to table testUser.req_msn_warnings access to table testUser.req_air_msn access to table testUser.req_src_header access to table testUser.req_msn_ids access to table testUser.req_msn_comment access to table testUser.req_c2_msn access to table testUser.req_c2_source access to table testUser.req_ada_msn access to table testUser.req_ada_vertex access to table testUser.weather_forecast access to table testUser.weather_coords access to table testUser.weather_area access to table testUser.weapon_option access to table testUser.wag_activity access to table testUser.unit_remark access to table testUser.unit_location_turn access to table testUser.unit_iff access to table testUser.unit_coordination access to table testUser.unit_code access to table testUser.trace_point access to table testUser.tasking_agency access to table testUser.task_unit access to table testUser.target_type access to table testUser.tap_db_version access to table testUser.status_code access to table testUser.state_space_threat access to table testUser.state_space_profile access to table testUser.state_space access to table testUser.ssm_mission access to table testUser.spins_section_id access to table testUser.spins_codes access to table testUser.spins access to table testUser.unit_location access to table testUser.ship_target_request access to table testUser.service_subscription access to table testUser.service_instance access to table testUser.sa_ordnance_weapon_type access to table testUser.runway access to table testUser.restricted_codes access to table testUser.response_entity access to table testUser.residual_mission access to table testUser.request_objective access to table testUser.request and 194 other objects (see server log for list)

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• timetable in a jTable

  - by chandra

  I want to create a timetable in a jTable. For the top row it will display from monday to sunday and the left colume will display the time of the day with 2h interval e.g 1st colume (0000 - 0200), 2nd colume (0200 - 0400) .... And if i click a button the timing will change from 2h interval to 1h interval. I do not want to hardcode it because i need to do for 2h, 1h, 30min , 15min, 1min, 30sec and 1 sec interval and it will take too long for me to hardcode. Can anyone show me an example or help me create an example for the 2h to 1h interval so that i know what to do? The data array is for me to store data and are there any other easier or shortcuts for me to store them because if it is in 1 sec interval i got thousands of array i need to type it out. private void oneHour() //1 interval functions { if(!once) { initialize(); once = true; } jTable.setModel(new javax.swing.table.DefaultTableModel( new Object [][] { {"0000 - 0100", data[0][0], data[0][1], data[0][2], data[0][3], data[0][4], data[0][5], data[0][6]}, {"0100 - 0200", data[2][0], data[2][1], data[2][2], data[2][3], data[2][4], data[2][5], data[2][6]}, {"0200 - 0300", data[4][0], data[4][1], data[4][2], data[4][3], data[4][4], data[4][5], data[4][6]}, {"0300 - 0400", data[6][0], data[6][1], data[6][2], data[6][3], data[6][4], data[6][5], data[6][6]}, {"0400 - 0600", data[8][0], data[8][1], data[8][2], data[8][3], data[8][4], data[8][5], data[8][6]}, {"0600 - 0700", data[10][0], data[4][1], data[10][2], data[10][3], data[10][4], data[10][5], data[10][6]}, {"0700 - 0800", data[12][0], data[12][1], data[12][2], data[12][3], data[12][4], data[12][5], data[12][6]}, {"0800 - 0900", data[14][0], data[14][1], data[14][2], data[14][3], data[14][4], data[14][5], data[14][6]}, {"0900 - 1000", data[16][0], data[16][1], data[16][2], data[16][3], data[16][4], data[16][5], data[16][6]}, {"1000 - 1100", data[18][0], data[18][1], data[18][2], data[18][3], data[18][4], data[18][5], data[18][6]}, {"1100 - 1200", data[20][0], data[20][1], data[20][2], data[20][3], data[20][4], data[20][5], data[20][6]}, {"1200 - 1300", data[22][0], data[22][1], data[22][2], data[22][3], data[22][4], data[22][5], data[22][6]}, {"1300 - 1400", data[24][0], data[24][1], data[24][2], data[24][3], data[24][4], data[24][5], data[24][6]}, {"1400 - 1500", data[26][0], data[26][1], data[26][2], data[26][3], data[26][4], data[26][5], data[26][6]}, {"1500 - 1600", data[28][0], data[28][1], data[28][2], data[28][3], data[28][4], data[28][5], data[28][6]}, {"1600 - 1700", data[30][0], data[30][1], data[30][2], data[30][3], data[30][4], data[30][5], data[30][6]}, {"1700 - 1800", data[32][0], data[32][1], data[32][2], data[32][3], data[32][4], data[32][5], data[32][6]}, {"1800 - 1900", data[34][0], data[34][1], data[34][2], data[34][3], data[34][4], data[34][5], data[34][6]}, {"1900 - 2000", data[36][0], data[36][1], data[36][2], data[36][3], data[36][4], data[36][5], data[36][6]}, {"2000 - 2100", data[38][0], data[38][1], data[38][2], data[38][3], data[38][4], data[38][5], data[38][6]}, {"2100 - 2200", data[40][0], data[40][1], data[40][2], data[40][3], data[40][4], data[40][5], data[40][6]}, {"2200 - 2300", data[42][0], data[42][1], data[42][2], data[42][3], data[42][4], data[42][5], data[42][6]}, {"2300 - 2400", data[44][0], data[44][1], data[44][2], data[44][3], data[44][4], data[44][5], data[44][6]}, {"2400 - 0000", data[46][0], data[46][1], data[46][2], data[46][3], data[46][4], data[46][5], data[46][6]}, }, new String [] { "Time/Day", "(Mon)", "(Tue)", "(Wed)", "(Thurs)", "(Fri)", "(Sat)", "(Sun)" } )); } private void twoHour() //2 hour interval functions { if(!once) { initialize(); once = true; } jTable.setModel(new javax.swing.table.DefaultTableModel( new Object [][] { {"0000 - 0200", data[0][0], data[0][1], data[0][2], data[0][3], data[0][4], data[0][5], data[0][6]}, {"0200 - 0400", data[4][0], data[4][1], data[4][2], data[4][3], data[4][4], data[4][5], data[4][6]}, {"0400 - 0600", data[8][0], data[8][1], data[8][2], data[8][3], data[8][4], data[8][5], data[8][6]}, {"0600 - 0800", data[12][0], data[12][1], data[12][2], data[12][3], data[12][4], data[12][5], data[12][6]}, {"0800 - 1000", data[16][0], data[16][1], data[16][2], data[16][3], data[16][4], data[16][5], data[16][6]}, {"1000 - 1200", data[20][0], data[20][1], data[20][2], data[20][3], data[20][4], data[20][5], data[20][6]}, {"1200 - 1400", data[24][0], data[24][1], data[24][2], data[24][3], data[24][4], data[24][5], data[24][6]}, {"1400 - 1600", data[28][0], data[28][1], data[28][2], data[28][3], data[28][4], data[28][5], data[28][6]}, {"1600 - 1800", data[32][0], data[32][1], data[32][2], data[32][3], data[32][4], data[32][5], data[32][6]}, {"1800 - 2000", data[36][0], data[36][1], data[36][2], data[36][3], data[36][4], data[36][5], data[36][6]}, {"2000 - 2200", data[40][0], data[40][1], data[40][2], data[40][3], data[40][4], data[40][5], data[40][6]}, {"2200 - 2400",data[44][0], data[44][1], data[44][2], data[44][3], data[44][4], data[44][5], data[44][6]} },

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• How do I create an Access 2003 MDE programmatically or by command line in Access 2007?

  - by Ned Ryerson

  I have a legacy Access 2003 database file that must remain in that format to preserve its menus and toolbars. I have recently moved to Access 2007 in my build environment and will be deploying the compiled Access 2003 program with the Access 2007 runtime. In Access 2003, I could script the process of creating an MDE with the Access Developer Extensions (WZADE.mde) using the command line and an .xml file of build preferences (without creating an install package). The Access 2007 developer extensions do not seem to offer a similar option. I can "Package a Solution", but it creates an accdr and buries it in a CD installer. I've tried programmatic options like Docmd.RunCommand acMakeMDEFILe and Syscmd(603, mdbpath, mdepath) but they no longer work in Access 2007. Of course, i can manually create an MDE using Database ToolsCreate MDE, but that is no scriptable as far as I can tell.

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• Oracle Data Mining a Star Schema: Telco Churn Case Study

  - by charlie.berger

  There is a complete and detailed Telco Churn case study "How to" Blog Series just posted by Ari Mozes, ODM Dev. Manager.  In it, Ari provides detailed guidance in how to leverage various strengths of Oracle Data Mining including the ability to: mine Star Schemas and join tables and views together to obtain a complete 360 degree view of a customer combine transactional data e.g. call record detail (CDR) data, etc. define complex data transformation, model build and model deploy analytical methodologies inside the Database  His blog is posted in a multi-part series.  Below are some opening excerpts for the first 3 blog entries.  This is an excellent resource for any novice to skilled data miner who wants to gain competitive advantage by mining their data inside the Oracle Database.  Many thanks Ari! Mining a Star Schema: Telco Churn Case Study (1 of 3) One of the strengths of Oracle Data Mining is the ability to mine star schemas with minimal effort.  Star schemas are commonly used in relational databases, and they often contain rich data with interesting patterns.  While dimension tables may contain interesting demographics, fact tables will often contain user behavior, such as phone usage or purchase patterns.  Both of these aspects - demographics and usage patterns - can provide insight into behavior.Churn is a critical problem in the telecommunications industry, and companies go to great lengths to reduce the churn of their customer base.  One case study1 describes a telecommunications scenario involving understanding, and identification of, churn, where the underlying data is present in a star schema.  That case study is a good example for demonstrating just how natural it is for Oracle Data Mining to analyze a star schema, so it will be used as the basis for this series of posts...... Mining a Star Schema: Telco Churn Case Study (2 of 3) This post will follow the transformation steps as described in the case study, but will use Oracle SQL as the means for preparing data.  Please see the previous post for background material, including links to the case study and to scripts that can be used to replicate the stages in these posts.1) Handling missing values for call data recordsThe CDR_T table records the number of phone minutes used by a customer per month and per call type (tariff).  For example, the table may contain one record corresponding to the number of peak (call type) minutes in January for a specific customer, and another record associated with international calls in March for the same customer.  This table is likely to be fairly dense (most type-month combinations for a given customer will be present) due to the coarse level of aggregation, but there may be some missing values.  Missing entries may occur for a number of reasons: the customer made no calls of a particular type in a particular month, the customer switched providers during the timeframe, or perhaps there is a data entry problem.  In the first situation, the correct interpretation of a missing entry would be to assume that the number of minutes for the type-month combination is zero.  In the other situations, it is not appropriate to assume zero, but rather derive some representative value to replace the missing entries.  The referenced case study takes the latter approach.  The data is segmented by customer and call type, and within a given customer-call type combination, an average number of minutes is computed and used as a replacement value.In SQL, we need to generate additional rows for the missing entries and populate those rows with appropriate values.  To generate the missing rows, Oracle's partition outer join feature is a perfect fit.  select cust_id, cdre.tariff, cdre.month, minsfrom cdr_t cdr partition by (cust_id) right outer join     (select distinct tariff, month from cdr_t) cdre     on (cdr.month = cdre.month and cdr.tariff = cdre.tariff);   ....... Mining a Star Schema: Telco Churn Case Study (3 of 3) Now that the "difficult" work is complete - preparing the data - we can move to building a predictive model to help identify and understand churn.The case study suggests that separate models be built for different customer segments (high, medium, low, and very low value customer groups).  To reduce the data to a single segment, a filter can be applied: create or replace view churn_data_high asselect * from churn_prep where value_band = 'HIGH'; It is simple to take a quick look at the predictive aspects of the data on a univariate basis.  While this does not capture the more complex multi-variate effects as would occur with the full-blown data mining algorithms, it can give a quick feel as to the predictive aspects of the data as well as validate the data preparation steps.  Oracle Data Mining includes a predictive analytics package which enables quick analysis. begin  dbms_predictive_analytics.explain(   'churn_data_high','churn_m6','expl_churn_tab'); end; /select * from expl_churn_tab where rank <= 5 order by rank; ATTRIBUTE_NAME       ATTRIBUTE_SUBNAME EXPLANATORY_VALUE RANK-------------------- ----------------- ----------------- ----------LOS_BAND                                      .069167052          1MINS_PER_TARIFF_MON  PEAK-5                   .034881648          2REV_PER_MON          REV-5                    .034527798          3DROPPED_CALLS                                 .028110322          4MINS_PER_TARIFF_MON  PEAK-4                   .024698149          5From the above results, it is clear that some predictors do contain information to help identify churn (explanatory value > 0).  The strongest uni-variate predictor of churn appears to be the customer's (binned) length of service.  The second strongest churn indicator appears to be the number of peak minutes used in the most recent month.  The subname column contains the interior piece of the DM_NESTED_NUMERICALS column described in the previous post.  By using the object relational approach, many related predictors are included within a single top-level column. .....   NOTE:  These are just EXCERPTS.  Click here to start reading the Oracle Data Mining a Star Schema: Telco Churn Case Study from the beginning.    

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• AutoVue Integrates with Primavera P6

  - by celine.beck

  Oracle's Primavera P6 Enterprise Project Portfolio Management is an integrated project portfolio management (PPM) application that helps select the right strategic mix of projects, balance resource capacity, manage project risk and complete projects on time and within budget. AutoVue 19.3 and later versions (release 20.0) now integrate out of the box with the Web version of Oracle Primavera P6 release 7. The integration between the two products, which was announced during Oracle Open World 2009, provides project teams with ready access to any project documents directly from within the context of P6 in support for project scope definition and project planning and execution. You can learn more about the integration between AutoVue and Primavera P6 by: Listening to the Oracle Appcast entitled Enhance Primavera Project Document Collaboration with AutoVue Enterprise Visualization Watching an Oracle Webcast about how to improve project success with document visualization and collaboration Watching a recorded demo of the integrated solution Teams involved in complex projects like construction or plant shutdown activities are highly interdependent: the decisions of one affecting the actions of many others. This coupled with increasing project complexity, a vast array of players and heavy engineering and document-intensive workflows makes it more challenging to complete jobs on time and within budget. Organizations need complete visibility into project information, as well as robust project planning, risk analysis and resource balancing capabilities similar to those featured in Primavera P6 ; they also need to make sure that all project stakeholders, even those who neither understand engineering drawings nor are interested in engineering details that go beyond their specific needs, have ready access to technically advanced project information. This is exactly what the integration between AutoVue and Primavera delivers: ready access to any project information attached to Primavera projects, tasks or activities via AutoVue. There is no need for users to waste time searching for project-related documents or disrupting engineers for printouts, users have all the context they need to make sound decisions right from within Primavera P6 with a single click of a button. We are very excited about this new integration. If you are using Primavera and / or Primavera tied with AutoVue, we would be interested in getting your feedback on this integration! Please do not hesitate to post your comments / reactions on the blog!

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• Ant calling child project parent project ivy.xml overriding child project ivy.xml

  - by J G

  We've got a parent project and a child project java builds using ant and ivy. The child project needs to be able to build independently. When the parent project calls the child project the antfile command - the parent project's ivy.xml overrides the child project's ivy.xml Does anyone know how to keep the child project using its own ivy.xml?

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• SQL Rally Pre-Con: Data Warehouse Modeling – Making the Right Choices

  - by Davide Mauri

  As you may have already learned from my old post or Adam’s or Kalen’s posts, there will be two SQL Rally in North Europe. In the Stockholm SQL Rally, with my friend Thomas Kejser, I’ll be delivering a pre-con on Data Warehouse Modeling: Data warehouses play a central role in any BI solution. It's the back end upon which everything in years to come will be created. For this reason, it must be rock solid and yet flexible at the same time. To develop such a data warehouse, you must have a clear idea of its architecture, a thorough understanding of the concepts of Measures and Dimensions, and a proven engineered way to build it so that quality and stability can go hand-in-hand with cost reduction and scalability. In this workshop, Thomas Kejser and Davide Mauri will share all the information they learned since they started working with data warehouses, giving you the guidance and tips you need to start your BI project in the best way possible?avoiding errors, making implementation effective and efficient, paving the way for a winning Agile approach, and helping you define how your team should work so that your BI solution will stand the test of time. You'll learn: Data warehouse architecture and justification Agile methodology Dimensional modeling, including Kimball vs. Inmon, SCD1/SCD2/SCD3, Junk and Degenerate Dimensions, and Huge Dimensions Best practices, naming conventions, and lessons learned Loading the data warehouse, including loading Dimensions, loading Facts (Full Load, Incremental Load, Partitioned Load) Data warehouses and Big Data (Hadoop) Unit testing Tracking historical changes and managing large sizes With all the Self-Service BI hype, Data Warehouse is become more and more central every day, since if everyone will be able to analyze data using self-service tools, it’s better for him/her to rely on correct, uniform and coherent data. Already 50 people registered from the workshop and seats are limited so don’t miss this unique opportunity to attend to this workshop that is really a unique combination of years and years of experience! http://www.sqlpass.org/sqlrally/2013/nordic/Agenda/PreconferenceSeminars.aspx See you there!

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• Oracle Financial Analytics for SAP Certified with Oracle Data Integrator EE

  - by denis.gray

  Two days ago Oracle announced the release of Oracle Financial Analytics for SAP.  With the amount of press this has garnered in the past two days, there's a key detail that can't be missed.  This release is certified with Oracle Data Integrator EE - now making the combination of Data Integration and Business Intelligence a force to contend with.  Within the Oracle Press Release there were two important bullets: ·         Oracle Financial Analytics for SAP includes a pre-packaged ABAP code compliant adapter and is certified with Oracle Data Integrator Enterprise Edition to integrate SAP Financial Accounting data directly with the analytic application.  ·         Helping to integrate SAP financial data and disparate third-party data sources is Oracle Data Integrator Enterprise Edition which delivers fast, efficient loading and transformation of timely data into a data warehouse environment through its high-performance Extract Load and Transform (E-LT) technology. This is very exciting news, demonstrating Oracle's overall commitment to Oracle Data Integrator EE.   This is a great way to start off the new year and we look forward to building on this momentum throughout 2011.   The following links contain additional information and media responses about the Oracle Financial Analytics for SAP release. IDG News Service (Also appeared in PC World, Computer World, CIO: "Oracle is moving further into rival SAP's turf with Oracle Financial Analytics for SAP, a new BI (business intelligence) application that can crunch ERP (enterprise resource planning) system financial data for insights." Information Week: "Oracle talks a good game about the appeal of an optimized, all-Oracle stack. But the company also recognizes that we live in a predominantly heterogeneous IT world" CRN: "While some businesses with SAP Financial Accounting already use Oracle BI, those integrations had to be custom developed. The new offering provides pre-built integration capabilities." ECRM Guide:  "Among other features, Oracle Financial Analytics for SAP helps front-line managers improve financial performance and decision-making with what the company says is comprehensive, timely and role-based information on their departments' expenses and revenue contributions."   SAP Getting Started Guide for ODI on OTN: http://www.oracle.com/technetwork/middleware/data-integrator/learnmore/index.html For more information on the ODI and its SAP connectivity please review the Oracle® Fusion Middleware Application Adapters Guide for Oracle Data Integrator11g Release 1 (11.1.1)

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• What is the definition of "Big Data"?

  - by Ben

  Is there one? All the definitions I can find describe the size, complexity / variety or velocity of the data. Wikipedia's definition is the only one I've found with an actual number Big data sizes are a constantly moving target, as of 2012 ranging from a few dozen terabytes to many petabytes of data in a single data set. However, this seemingly contradicts the MIKE2.0 definition, referenced in the next paragraph, which indicates that "big" data can be small and that 100,000 sensors on an aircraft creating only 3GB of data could be considered big. IBM despite saying that: Big data is more simply than a matter of size. have emphasised size in their definition. O'Reilly has stressed "volume, velocity and variety" as well. Though explained well, and in more depth, the definition seems to be a re-hash of the others - or vice-versa of course. I think that a Computer Weekly article title sums up a number of articles fairly well "What is big data and how can it be used to gain competitive advantage". But ZDNet wins with the following from 2012: “Big Data” is a catch phrase that has been bubbling up from the high performance computing niche of the IT market... If one sits through the presentations from ten suppliers of technology, fifteen or so different definitions are likely to come forward. Each definition, of course, tends to support the need for that supplier’s products and services. Imagine that. Basically "big data" is "big" in some way shape or form. What is "big"? Is it quantifiable at the current time? If "big" is unquantifiable is there a definition that does not rely solely on generalities?

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