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  • Custom Model Binding of IEnumerable Properties in ASP.Net MVC 2

    - by Doug Lampe
    MVC 2 provides a GREAT feature for dealing with enumerable types.  Let's say you have an object with a parent/child relationship and you want to allow users to modify multiple children at the same time.  You can simply use the following syntax for any indexed enumerables (arrays, generic lists, etc.) and then your values will bind to your enumerable model properties. 1: <% using (Html.BeginForm("TestModelParameter", "Home")) 2: { %> 3: < table > 4: < tr >< th >ID</th><th>Name</th><th>Description</th></tr> 5: <% for (int i = 0; i < Model.Items.Count; i++) 6: { %> 7: < tr > 8: < td > 9: <%= i %> 10: </ td > 11: < td > 12: <%= Html.TextBoxFor(m => m.Items[i].Name) %> 13: </ td > 14: < td > 15: <%= Model.Items[i].Description %> 16: </ td > 17: </ tr > 18: <% } %> 19: </ table > 20: < input type ="submit" /> 21: <% } %> Then just update your model either by passing it into your action method as a parameter or explicitly with UpdateModel/TryUpdateModel. 1: public ActionResult TestTryUpdate() 2: { 3: ContainerModel model = new ContainerModel(); 4: TryUpdateModel(model); 5:   6: return View("Test", model); 7: } 8:   9: public ActionResult TestModelParameter(ContainerModel model) 10: { 11: return View("Test", model); 12: } Simple right?  Well, not quite.  The problem is the DefaultModelBinder and how it sets properties.  In this case our model has a property that is a generic list (Items).  The first bad thing the model binder does is create a new instance of the list.  This can be fixed by making the property truly read-only by removing the set accessor.  However this won't help because this behaviour continues.  As the model binder iterates through the items to "set" their values, it creates new instances of them as well.  This means you lose any information not passed via the UI to your controller so in the examplel above the "Description" property would be blank for each item after the form posts. One solution for this is custom model binding.  I have put together a solution which allows you to retain the structure of your modelModel binding is a somewhat advanced concept so you may need to do some additional research to really understand what is going on here, but the code is fairly simple.  First we will create a binder for the parent object which will retain the state of the parent as well as some information on which children have already been bound. 1: public class ContainerModelBinder : DefaultModelBinder 2: { 3: /// <summary> 4: /// Gets an instance of the model to be used to bind child objects. 5: /// </summary> 6: public ContainerModel Model { get; private set; } 7:   8: /// <summary> 9: /// Gets a list which will be used to track which items have been bound. 10: /// </summary> 11: public List<ItemModel> BoundItems { get; private set; } 12:   13: public ContainerModelBinder() 14: { 15: BoundItems = new List<ItemModel>(); 16: } 17:   18: protected override object CreateModel(ControllerContext controllerContext, ModelBindingContext bindingContext, Type modelType) 19: { 20: // Set the Model property so child binders can find children. 21: Model = base.CreateModel(controllerContext, bindingContext, modelType) as ContainerModel; 22:   23: return Model; 24: } 25: } Next we will create the child binder and have it point to the parent binder to get instances of the child objects.  Note that this only works if there is only one property of type ItemModel in the parent class since the property to find the item in the parent is hard coded. 1: public class ItemModelBinder : DefaultModelBinder 2: { 3: /// <summary> 4: /// Gets the parent binder so we can find objects in the parent's collection 5: /// </summary> 6: public ContainerModelBinder ParentBinder { get; private set; } 7: 8: public ItemModelBinder(ContainerModelBinder containerModelBinder) 9: { 10: ParentBinder = containerModelBinder; 11: } 12:   13: protected override object CreateModel(ControllerContext controllerContext, ModelBindingContext bindingContext, Type modelType) 14: { 15: // Find the item in the parent collection and add it to the bound items list. 16: ItemModel item = ParentBinder.Model.Items.FirstOrDefault(i => !ParentBinder.BoundItems.Contains(i)); 17: ParentBinder.BoundItems.Add(item); 18: 19: return item; 20: } 21: } Finally, we will register these binders in Global.asax.cs so they will be used to bind the classes. 1: protected void Application_Start() 2: { 3: AreaRegistration.RegisterAllAreas(); 4:   5: ContainerModelBinder containerModelBinder = new ContainerModelBinder(); 6: ModelBinders.Binders.Add(typeof(ContainerModel), containerModelBinder); 7: ModelBinders.Binders.Add(typeof(ItemModel), new ItemModelBinder(containerModelBinder)); 8:   9: RegisterRoutes(RouteTable.Routes); 10: } I'm sure some of my fellow geeks will comment that this could be done more efficiently by simply rewriting some of the methods of the default model binder to get the same desired behavior.  I like my method shown here because it extends the binder class instead of modifying it so it minimizes the potential for unforseen problems. In a future post (if I ever get around to it) I will explore creating a generic version of these binders.

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  • Augmenting your Social Efforts via Data as a Service (DaaS)

    - by Mike Stiles
    The following is the 3rd in a series of posts on the value of leveraging social data across your enterprise by Oracle VP Product Development Don Springer and Oracle Cloud Data and Insight Service Sr. Director Product Management Niraj Deo. In this post, we will discuss the approach and value of integrating additional “public” data via a cloud-based Data-as-as-Service platform (or DaaS) to augment your Socially Enabled Big Data Analytics and CX Management. Let’s assume you have a functional Social-CRM platform in place. You are now successfully and continuously listening and learning from your customers and key constituents in Social Media, you are identifying relevant posts and following up with direct engagement where warranted (both 1:1, 1:community, 1:all), and you are starting to integrate signals for communication into your appropriate Customer Experience (CX) Management systems as well as insights for analysis in your business intelligence application. What is the next step? Augmenting Social Data with other Public Data for More Advanced Analytics When we say advanced analytics, we are talking about understanding causality and correlation from a wide variety, volume and velocity of data to Key Performance Indicators (KPI) to achieve and optimize business value. And in some cases, to predict future performance to make appropriate course corrections and change the outcome to your advantage while you can. The data to acquire, process and analyze this is very nuanced: It can vary across structured, semi-structured, and unstructured data It can span across content, profile, and communities of profiles data It is increasingly public, curated and user generated The key is not just getting the data, but making it value-added data and using it to help discover the insights to connect to and improve your KPIs. As we spend time working with our larger customers on advanced analytics, we have seen a need arise for more business applications to have the ability to ingest and use “quality” curated, social, transactional reference data and corresponding insights. The challenge for the enterprise has been getting this data inline into an easily accessible system and providing the contextual integration of the underlying data enriched with insights to be exported into the enterprise’s business applications. The following diagram shows the requirements for this next generation data and insights service or (DaaS): Some quick points on these requirements: Public Data, which in this context is about Common Business Entities, such as - Customers, Suppliers, Partners, Competitors (all are organizations) Contacts, Consumers, Employees (all are people) Products, Brands This data can be broadly categorized incrementally as - Base Utility data (address, industry classification) Public Master Reference data (trade style, hierarchy) Social/Web data (News, Feeds, Graph) Transactional Data generated by enterprise process, workflows etc. This Data has traits of high-volume, variety, velocity etc., and the technology needed to efficiently integrate this data for your needs includes - Change management of Public Reference Data across all categories Applied Big Data to extract statics as well as real-time insights Knowledge Diagnostics and Data Mining As you consider how to deploy this solution, many of our customers will be using an online “cloud” service that provides quality data and insights uniformly to all their necessary applications. In addition, they are requesting a service that is: Agile and Easy to Use: Applications integrated with the service can obtain data on-demand, quickly and simply Cost-effective: Pre-integrated into applications so customers don’t have to Has High Data Quality: Single point access to reference data for data quality and linkages to transactional, curated and social data Supports Data Governance: Becomes more manageable and cost-effective since control of data privacy and compliance can be enforced in a centralized place Data-as-a-Service (DaaS) Just as the cloud has transformed and now offers a better path for how an enterprise manages its IT from their infrastructure, platform, and software (IaaS, PaaS, and SaaS), the next step is data (DaaS). Over the last 3 years, we have seen the market begin to offer a cloud-based data service and gain initial traction. On one side of the DaaS continuum, we see an “appliance” type of service that provides a single, reliable source of accurate business data plus social information about accounts, leads, contacts, etc. On the other side of the continuum we see more of an online market “exchange” approach where ISVs and Data Publishers can publish and sell premium datasets within the exchange, with the exchange providing a rich set of web interfaces to improve the ease of data integration. Why the difference? It depends on the provider’s philosophy on how fast the rate of commoditization of certain data types will occur. How do you decide the best approach? Our perspective, as shown in the diagram below, is that the enterprise should develop an elastic schema to support multi-domain applicability. This allows the enterprise to take the most flexible approach to harness the speed and breadth of public data to achieve value. The key tenet of the proposed approach is that an enterprise carefully federates common utility, master reference data end points, mobility considerations and content processing, so that they are pervasively available. One way you may already be familiar with this approach is in how you do Address Verification treatments for accounts, contacts etc. If you design and revise this service in such a way that it is also easily available to social analytic needs, you could extend this to launch geo-location based social use cases (marketing, sales etc.). Our fundamental belief is that value-added data achieved through enrichment with specialized algorithms, as well as applying business “know-how” to weight-factor KPIs based on innovative combinations across an ever-increasing variety, volume and velocity of data, will be where real value is achieved. Essentially, Data-as-a-Service becomes a single entry point for the ever-increasing richness and volume of public data, with enrichment and combined capabilities to extract and integrate the right data from the right sources with the right factoring at the right time for faster decision-making and action within your core business applications. As more data becomes available (and in many cases commoditized), this value-added data processing approach will provide you with ongoing competitive advantage. Let’s look at a quick example of creating a master reference relationship that could be used as an input for a variety of your already existing business applications. In phase 1, a simple master relationship is achieved between a company (e.g. General Motors) and a variety of car brands’ social insights. The reference data allows for easy sort, export and integration into a set of CRM use cases for analytics, sales and marketing CRM. In phase 2, as you create more data relationships (e.g. competitors, contacts, other brands) to have broader and deeper references (social profiles, social meta-data) for more use cases across CRM, HCM, SRM, etc. This is just the tip of the iceberg, as the amount of master reference relationships is constrained only by your imagination and the availability of quality curated data you have to work with. DaaS is just now emerging onto the marketplace as the next step in cloud transformation. For some of you, this may be the first you have heard about it. Let us know if you have questions, or perspectives. In the meantime, we will continue to share insights as we can.Photo: Erik Araujo, stock.xchng

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  • Trouble accessing data in relationships in Ember

    - by user3618430
    I'm having trouble saving data in this model relationship. My models are as follows: App.Flow = DS.Model.extend({ title: DS.attr('string'), content: DS.attr('string'), isCustom: DS.attr('boolean'), params: DS.hasMany('parameter', {async: true}) }); App.Parameter = DS.Model.extend({ flow: DS.belongsTo('flow'), param: DS.attr('string'), param_tooltip: DS.attr('string'), param_value: DS.attr('string') }); As you can see, I want Flows to have multiple Parameters. I have a rudimentary setup using Flow and Parameter fixtures, which behave as expected in the templates. However, when I try to create new ones in the controller, I have trouble setting the flow and parameter values correctly. var p = this.store.createRecord('parameter', { param: "foo", param_tooltip: "world", param_value: "hello" }); var f = this.store.createRecord('flow', { title: 'job', content: title, isCustom: true, params: [p] // doesn't seem to work }); f.set('params', [p]); // doesn't seem to work p.set('flow', f); // also doesn't seem to work // Save the new model p.save(); f.save(); I've tried a lot of solutions after staring at this and StackOverflow for a while (not just the ones listed). I'm not really sure what to try next. One thing that I noticed in the Ember inspector was that the ids of these created elements were not integers (they were something like the string 'fixture_0'), but I'm not really sure why that would be, whether its related, or how to fix it. Thanks!

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  • Working with data and meta data that are separated on different servers

    - by afuzzyllama
    While developing a product, I've come across a situation where my group wants to store meta data for data entry forms (questions, layout, etc) in a different database then the database where the collected data is stored. This is mostly for security because we want to be able to have our meta data public facing, while keeping collected data as secure as possible. I was thinking about writing a web service that provides the meta information that the data collection program could access. The only issue I see with this approach is the front end is going to have to match the meta data with the collected data, which would be more efficient as a join on the back end. Currently, this system is slated to run on .NET and MSSQL. I haven't played around with .NET libraries running in SQL, but I'm considering trying to create logic that would pull from the web service, convert the meta data into a table that SQL can join on, and return the combined data and meta data that way. Is this solution the wrong way to approach the problem? Is there a pattern or "industry standard" way of bringing together two datasets that don't live in the same database?

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  • The Business case for Big Data

    - by jasonw
    The Business Case for Big Data Part 1 What's the Big Deal Okay, so a new buzz word is emerging. It's gone beyond just a buzzword now, and I think it is going to change the landscape of retail, financial services, healthcare....everything. Let me spend a moment to talk about what i'm going to talk about. Massive amounts of data are being collected every second, more than ever imaginable, and the size of this data is more than can be practically managed by today’s current strategies and technologies. There is a revolution at hand centering on this groundswell of data and it will change how we execute our businesses through greater efficiencies, new revenue discovery and even enable innovation. It is the revolution of Big Data. This is more than just a new buzzword is being tossed around technology circles.This blog series for Big Data will explain this new wave of technology and provide a roadmap for businesses to take advantage of this growing trend. Cases for Big Data There is a growing list of use cases for big data. We naturally think of Marketing as the low hanging fruit. Many projects look to analyze twitter feeds to find new ways to do marketing. I think of a great example from a TED speech that I recently saw on data visualization from Facebook from my masters studies at University of Virginia. We can see when the most likely time for breaks-ups occurs by looking at status changes and updates on users Walls. This is the intersection of Big Data, Analytics and traditional structured data. Ted Video Marketers can use this to sell more stuff. I really like the following piece on looking at twitter feeds to measure mood. The following company was bought by a hedge fund. They could predict how the S&P was going to do within three days at an 85% accuracy. Link to the article Here we see a convergence of predictive analytics and Big Data. So, we'll look at a lot of these business cases and start talking about what this means for the business. It's more than just finding ways to use Hadoop + NoSql and we'll talk about that too. How do I start in Big Data? That's what is coming next post.

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  • Big Data – Buzz Words: What is NoSQL – Day 5 of 21

    - by Pinal Dave
    In yesterday’s blog post we explored the basic architecture of Big Data . In this article we will take a quick look at one of the four most important buzz words which goes around Big Data – NoSQL. What is NoSQL? NoSQL stands for Not Relational SQL or Not Only SQL. Lots of people think that NoSQL means there is No SQL, which is not true – they both sound same but the meaning is totally different. NoSQL does use SQL but it uses more than SQL to achieve its goal. As per Wikipedia’s NoSQL Database Definition – “A NoSQL database provides a mechanism for storage and retrieval of data that uses looser consistency models than traditional relational databases.“ Why use NoSQL? A traditional relation database usually deals with predictable structured data. Whereas as the world has moved forward with unstructured data we often see the limitations of the traditional relational database in dealing with them. For example, nowadays we have data in format of SMS, wave files, photos and video format. It is a bit difficult to manage them by using a traditional relational database. I often see people using BLOB filed to store such a data. BLOB can store the data but when we have to retrieve them or even process them the same BLOB is extremely slow in processing the unstructured data. A NoSQL database is the type of database that can handle unstructured, unorganized and unpredictable data that our business needs it. Along with the support to unstructured data, the other advantage of NoSQL Database is high performance and high availability. Eventual Consistency Additionally to note that NoSQL Database may not provided 100% ACID (Atomicity, Consistency, Isolation, Durability) compliance.  Though, NoSQL Database does not support ACID they provide eventual consistency. That means over the long period of time all updates can be expected to propagate eventually through the system and data will be consistent. Taxonomy Taxonomy is the practice of classification of things or concepts and the principles. The NoSQL taxonomy supports column store, document store, key-value stores, and graph databases. We will discuss the taxonomy in detail in later blog posts. Here are few of the examples of the each of the No SQL Category. Column: Hbase, Cassandra, Accumulo Document: MongoDB, Couchbase, Raven Key-value : Dynamo, Riak, Azure, Redis, Cache, GT.m Graph: Neo4J, Allegro, Virtuoso, Bigdata As of now there are over 150 NoSQL Database and you can read everything about them in this single link. Tomorrow In tomorrow’s blog post we will discuss Buzz Word – Hadoop. 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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  • BAM Data Control in multiple ADF Faces Components

    - by [email protected]
    As we know Oracle BAM data control instance sharing is not supported.When two or more ADF Faces components must display the same data, and are bound to the same Oracle BAM data control definition, we have to make sure that we wrap each ADF Faces component in an ADF task flow, and set the Data Control Scope to isolated. This blog will show a small sample to demonstrate this. In this sample we will create a Pie and Bar using same BAM DC, such that both components use same Data control but have isolated scope.This sample can be downloaded  fromSample1.zip Set-up: Create a BAM data control using employees DO (sample) Steps: Right click on View Controller project and select "New->ADF Task Flow" Check "Create Bounded Task Flow" and give some meaningful name (ex:EmpPieTF.xml ) to the TaskFlow(TF) and click on "OK"CreateTF.bmpFrom the "Components Palette", drag and drop "View" into the task flow diagram. Give a meaningful name to the view. Double Click and Click "Ok" for  "Create New JSF Page Fragment" From "Data Controls" drag and drop "Employees->Query"  into this jsff page as "Graph->Pie" (Pie: Sales_Number and Slices: Salesperson) Repeat step 1 through 4 for another Task Flow (ex: EmpBarTF). From "Data Controls" drag and drop "Employees->Query"  into this jsff page as "Graph->Bar" (Bars :Sales_Number and X-axis : Salesperson). Open the Taskflow created in step 2. In the Structure Pane, right click on "Task Flow Definition -EmpPieTF" Click "Insert inside Task Flow Definition - EmpPieTF -> ADF Task Flow -> Data Control Scope". Click "OK"TFDCScope.bmpFor the "Data Control Scope", In the Property Inspector ->General section, change data control scope from Shared to Isolated. Repeat step 8 through 11 for the 2nd Task flow created. Now create a new jspx page example: Main.jspxDrag and drop both the Task flows (ex: "EmpPieTF" and "EmpBarTF") as regions. Surround with panel components as needed.Run the page Main.jspxMainPage.bmpNow when the page runs although both components are created using same Data control the bindings are not shared and each component will have a separate instance of the data control.

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  • Should a model binder populate all of the model?

    - by Richard
    Should a model binder populate all of the model, or only the bits that are being posted? For example, I am adding a product in my system and on the form i want the user to select which sites the new product will appear on. Therefore, in my model I want to populate a collection called "AllAvailableSites" to render the checkboxes for the user to choose from. I also need to populate the model with any chosen sites on a post in case the form does not validate, and I need to represent the form showing the initial selections. It would seem that I should let the model binder set the chosen sites on the model, and (once in the controller method) I set the "AllAvailableSites" on the model. Does that sound right? It seems more efficient to set everything in the model binder but someone is suggesting it is not quite right. I am grateful for any advice; I have to say that all the MVC model binding help online seems to cite really simple examples, nothing complicated. Do I really need a GET and a POST version of a method? Can't they just take the same view model? Then I check in my model binder if it is a GET/POST, and populate all the model accordingly.

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  • Best industry to work for as a developer.

    - by The Elite Gentleman
    Hi guys, Hmmm, StackOverflow now warns me of: "The question you're asking appears subjective and is likely to be closed." I've been an avid java (J2SE, JEE) developer for over 5 years now (and I'm not complaining, even though I want to go back to Delphi & C++). My contract has just ended and I'm wondering of possible job to further tackle. I've done banking and insurance industry for all my career (with 1 year on a Fortuner 500 company) and pretty much, banking is the slowest (and boring) industry to work for (IMHO) since they're strict in their business practices (fair enough). The upside is that they pay. My question is: What is the best industry for a developer, who tends to get bored relatively quickly, to work for? Is it also worthwhile for me to do consultancy (and if so, what type of consultancy)? PS There's no gaming industry in South Africa, so suggesting it requires that I have to travel to a country where gaming is alive! I don't see the Community Wiki checkbox, so I don't know how to make this a wiki.

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  • Data model for unlockable card collection

    - by Karlos Zafra
    My game has a collection of cards (about 64) that are unlocked (one by one) provided that 4 items are collected/gained in the game. Right now the deck of cards is modeled with a plist file, like this: <plist> <dict> <key>card1</key> <dict> <key>available</key> <true/> <key>series</key> <integer>1</integer> <key>model</key> <integer>1</integer> <key>color</key> <integer>1</integer> </dict> <key>card2</key> <dict> <key>available</key> <false/> <key>series</key> <integer>1</integer> <key>model</key> <integer>1</integer> <key>color</key> <integer>2</integer> </dict> The value for the key named "available" marks if the item is locked or not. Right now I have to include the data for the items collected by the user, but including that inside the plist looks like too much hassle. What kind of structure should be more suitable for this? How do you manage a collection of unlockable items like this?

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  • New Feature in ODI 11.1.1.6: ODI for Big Data

    - by Julien Testut
    Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} By Ananth Tirupattur Starting with Oracle Data Integrator 11.1.1.6.0, ODI is offering a solution to process Big Data. This post provides an overview of this feature. With all the buzz around Big Data and before getting into the details of ODI for Big Data, I will provide a brief introduction to Big Data and Oracle Solution for Big Data. So, what is Big Data? Big data includes: structured data (this includes data from relation data stores, xml data stores), semi-structured data (this includes data from weblogs) unstructured data (this includes data from text blob, images) Traditionally, business decisions are based on the information gathered from transactional data. For example, transactional Data from CRM applications is fed to a decision system for analysis and decision making. Products such as ODI play a key role in enabling decision systems. However, with the emergence of massive amounts of semi-structured and unstructured data it is important for decision system to include them in the analysis to achieve better decision making capability. While there is an abundance of opportunities for business for gaining competitive advantages, process of Big Data has challenges. The challenges of processing Big Data include: Volume of data Velocity of data - The high Rate at which data is generated Variety of data In order to address these challenges and convert them into opportunities, we would need an appropriate framework, platform and the right set of tools. Hadoop is an open source framework which is highly scalable, fault tolerant system, for storage and processing large amounts of data. Hadoop provides 2 key services, distributed and reliable storage called Hadoop Distributed File System or HDFS and a framework for parallel data processing called Map-Reduce. Innovations in Hadoop and its related technology continue to rapidly evolve, hence therefore, it is highly recommended to follow information on the web to keep up with latest information. Oracle's vision is to provide a comprehensive solution to address the challenges faced by Big Data. Oracle is providing the necessary Hardware, software and tools for processing Big Data Oracle solution includes: Big Data Appliance Oracle NoSQL Database Cloudera distribution for Hadoop Oracle R Enterprise- R is a statistical package which is very popular among data scientists. ODI solution for Big Data Oracle Loader for Hadoop for loading data from Hadoop to Oracle. Further details can be found here: http://www.oracle.com/us/products/database/big-data-appliance/overview/index.html ODI Solution for Big Data: ODI’s goal is to minimize the need to understand the complexity of Hadoop framework and simplify the adoption of processing Big Data seamlessly in an enterprise. ODI is providing the capabilities for an integrated architecture for processing Big Data. This includes capability to load data in to Hadoop, process data in Hadoop and load data from Hadoop into Oracle. ODI is expanding its support for Big Data by providing the following out of the box Knowledge Modules (KMs). IKM File to Hive (LOAD DATA).Load unstructured data from File (Local file system or HDFS ) into Hive IKM Hive Control AppendTransform and validate structured data on Hive IKM Hive TransformTransform unstructured data on Hive IKM File/Hive to Oracle (OLH)Load processed data in Hive to Oracle RKM HiveReverse engineer Hive tables to generate models Using the Loading KM you can map files (local and HDFS files) to the corresponding Hive tables. For example, you can map weblog files categorized by date into a corresponding partitioned Hive table schema. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Using the Hive control Append KM you can validate and transform data in Hive. In the below example, two source Hive tables are joined and mapped to a target Hive table. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} The Hive Transform KM facilitates processing of semi-structured data in Hive. In the below example, the data from weblog is processed using a Perl script and mapped to target Hive table. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Using the Oracle Loader for Hadoop (OLH) KM you can load data from Hive table or HDFS to a corresponding table in Oracle. OLH is available as a standalone product. ODI greatly enhances OLH capability by generating the configuration and mapping files for OLH based on the configuration provided in the interface and KM options. ODI seamlessly invokes OLH when executing the scenario. In the below example, a HDFS file is mapped to a table in Oracle. Development and Deployment:The following diagram illustrates the development and deployment of ODI solution for Big Data. Using the ODI Studio on your development machine create and develop ODI solution for processing Big Data by connecting to a MySQL DB or Oracle database on a BDA machine or Hadoop cluster. Schedule the ODI scenarios to be executed on the ODI agent deployed on the BDA machine or Hadoop cluster. ODI Solution for Big Data provides several exciting new capabilities to facilitate the adoption of Big Data in an enterprise. You can find more information about the Oracle Big Data connectors on OTN. You can find an overview of all the new features introduced in ODI 11.1.1.6 in the following document: ODI 11.1.1.6 New Features Overview

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  • Data recovery on a data HDD (no OS)

    - by aCuria
    I am helping a family member with a dead hard disk. It is a seagate 200Gb 3.5" HDD in one of those old-school external enclosures. The problem was that windows failed to detect the hard disk when plugged in through USB. I removed the hard disk from its enclosure, and plugged it into my desktop PC. The BIOS does detect it upon POST, but unfortunately windows 7 would refuse to boot. It will get stuck on the loading screen with the glowing windows logo. Safe mode doesn't help either. What options do I have before going for some professional data recovery? edit: Someone modified the Title to something completely different from what I was asking, i just changed it back. 1) 2 HDD drives, DiskA(Dead), DiskB(my OS disk) 2) when B is connected to my system, everything works fine 3) when A AND B is connected, failure to boot. POSTs fine, but windows wont load 4) A has NO OS, its PURE data. It came from an EXTERNAL HDD enclosure which doesnt belong to me, and im trying to do data recovery.

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  • How to create a link to Nintex Start Workflow Page in the document set home page

    - by ybbest
    In this blog post, I’d like to show you how to create a link to start Nintex Workflow Page in the document set home page. 1. Firstly, you need to upload the latest version of jQuery to the style library of your team site. 2. Then, upload a text file to the style library for writing your own html and JavaScript 3. In the document set home page, insert a new content editor web part and link the text file you just upload. 4. Update the text file with the following content, you can download this file here. <script type="text/javascript" src="/Style%20Library/jquery-1.9.0.min.js"></script> <script type="text/javascript" src="/_layouts/sp.js"></script> <script type="text/javascript"> $(document).ready(function() { listItemId=getParameterByName("ID"); setTheWorkflowLink("YBBESTDocumentLibrary"); }); function buildWorkflowLink(webRelativeUrl,listId,itemId) { var workflowLink =webRelativeUrl+"_layouts/NintexWorkflow/StartWorkflow.aspx?list="+listId+"&ID="+itemId+"&WorkflowName=Start Approval"; return workflowLink; } function getParameterByName(name) { name = name.replace(/[\[]/, "\\\[").replace(/[\]]/, "\\\]"); var regexS = "[\\?&]" + name + "=([^&#]*)"; var regex = new RegExp(regexS); var results = regex.exec(window.location.search); if(results == null){ return ""; } else{ return decodeURIComponent(results[1].replace(/\+/g, " ")); } } function setTheWorkflowLink(listName) { var SPContext = new SP.ClientContext.get_current(); web = SPContext.get_web(); list = web.get_lists().getByTitle(listName); SPContext.load(web,"ServerRelativeUrl"); SPContext.load(list, 'Title', 'Id'); SPContext.executeQueryAsync(setTheWorkflowLink_Success, setTheWorkflowLink_Fail); } function setTheWorkflowLink_Success(sender, args) { var listId = list.get_id(); var listTitle = list.get_title(); var webRelativeUrl = web.get_serverRelativeUrl(); var startWorkflowLink=buildWorkflowLink(webRelativeUrl,listId,listItemId) $("a#submitLink").attr('href',startWorkflowLink); } function setTheWorkflowLink_Fail(sender, args) { alert("There is a problem setting up the submit exam approval link"); } </script> <a href="" target="_blank" id="submitLink"><span style="font-size:14pt">Start the approval process.</span></a> 5. Save your changes and go to the document set Item, you will see the link is on the home page now. Notes: 1. You can create a link to start the workflow using the following build dynamic string configuration: {Common:WebUrl}/_layouts/NintexWorkflow/StartWorkflow.aspx?list={Common:ListID}&ID={ItemProperty:ID}&WorkflowName=workflowname. With this link you will still need to click the start button, this is standard SharePoint behaviour and cannot be altered. References: http://connect.nintex.com/forums/27143/ShowThread.aspx How to use html and JavaScript in Content Editor web part in SharePoint2010

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  • Class-Level Model Validation with EF Code First and ASP.NET MVC 3

    - by ScottGu
    Earlier this week the data team released the CTP5 build of the new Entity Framework Code-First library.  In my blog post a few days ago I talked about a few of the improvements introduced with the new CTP5 build.  Automatic support for enforcing DataAnnotation validation attributes on models was one of the improvements I discussed.  It provides a pretty easy way to enable property-level validation logic within your model layer. You can apply validation attributes like [Required], [Range], and [RegularExpression] – all of which are built-into .NET 4 – to your model classes in order to enforce that the model properties are valid before they are persisted to a database.  You can also create your own custom validation attributes (like this cool [CreditCard] validator) and have them be automatically enforced by EF Code First as well.  This provides a really easy way to validate property values on your models.  I showed some code samples of this in action in my previous post. Class-Level Model Validation using IValidatableObject DataAnnotation attributes provides an easy way to validate individual property values on your model classes.  Several people have asked - “Does EF Code First also support a way to implement class-level validation methods on model objects, for validation rules than need to span multiple property values?”  It does – and one easy way you can enable this is by implementing the IValidatableObject interface on your model classes. IValidatableObject.Validate() Method Below is an example of using the IValidatableObject interface (which is built-into .NET 4 within the System.ComponentModel.DataAnnotations namespace) to implement two custom validation rules on a Product model class.  The two rules ensure that: New units can’t be ordered if the Product is in a discontinued state New units can’t be ordered if there are already more than 100 units in stock We will enforce these business rules by implementing the IValidatableObject interface on our Product class, and by implementing its Validate() method like so: The IValidatableObject.Validate() method can apply validation rules that span across multiple properties, and can yield back multiple validation errors. Each ValidationResult returned can supply both an error message as well as an optional list of property names that caused the violation (which is useful when displaying error messages within UI). Automatic Validation Enforcement EF Code-First (starting with CTP5) now automatically invokes the Validate() method when a model object that implements the IValidatableObject interface is saved.  You do not need to write any code to cause this to happen – this support is now enabled by default. This new support means that the below code – which violates one of our above business rules – will automatically throw an exception (and abort the transaction) when we call the “SaveChanges()” method on our Northwind DbContext: In addition to reactively handling validation exceptions, EF Code First also allows you to proactively check for validation errors.  Starting with CTP5, you can call the “GetValidationErrors()” method on the DbContext base class to retrieve a list of validation errors within the model objects you are working with.  GetValidationErrors() will return a list of all validation errors – regardless of whether they are generated via DataAnnotation attributes or by an IValidatableObject.Validate() implementation.  Below is an example of proactively using the GetValidationErrors() method to check (and handle) errors before trying to call SaveChanges(): ASP.NET MVC 3 and IValidatableObject ASP.NET MVC 2 included support for automatically honoring and enforcing DataAnnotation attributes on model objects that are used with ASP.NET MVC’s model binding infrastructure.  ASP.NET MVC 3 goes further and also honors the IValidatableObject interface.  This combined support for model validation makes it easy to display appropriate error messages within forms when validation errors occur.  To see this in action, let’s consider a simple Create form that allows users to create a new Product: We can implement the above Create functionality using a ProductsController class that has two “Create” action methods like below: The first Create() method implements a version of the /Products/Create URL that handles HTTP-GET requests - and displays the HTML form to fill-out.  The second Create() method implements a version of the /Products/Create URL that handles HTTP-POST requests - and which takes the posted form data, ensures that is is valid, and if it is valid saves it in the database.  If there are validation issues it redisplays the form with the posted values.  The razor view template of our “Create” view (which renders the form) looks like below: One of the nice things about the above Controller + View implementation is that we did not write any validation logic within it.  The validation logic and business rules are instead implemented entirely within our model layer, and the ProductsController simply checks whether it is valid (by calling the ModelState.IsValid helper method) to determine whether to try and save the changes or redisplay the form with errors. The Html.ValidationMessageFor() helper method calls within our view simply display the error messages our Product model’s DataAnnotations and IValidatableObject.Validate() method returned.  We can see the above scenario in action by filling out invalid data within the form and attempting to submit it: Notice above how when we hit the “Create” button we got an error message.  This was because we ticked the “Discontinued” checkbox while also entering a value for the UnitsOnOrder (and so violated one of our business rules).  You might ask – how did ASP.NET MVC know to highlight and display the error message next to the UnitsOnOrder textbox?  It did this because ASP.NET MVC 3 now honors the IValidatableObject interface when performing model binding, and will retrieve the error messages from validation failures with it. The business rule within our Product model class indicated that the “UnitsOnOrder” property should be highlighted when the business rule we hit was violated: Our Html.ValidationMessageFor() helper method knew to display the business rule error message (next to the UnitsOnOrder edit box) because of the above property name hint we supplied: Keeping things DRY ASP.NET MVC and EF Code First enables you to keep your validation and business rules in one place (within your model layer), and avoid having it creep into your Controllers and Views.  Keeping the validation logic in the model layer helps ensure that you do not duplicate validation/business logic as you add more Controllers and Views to your application.  It allows you to quickly change your business rules/validation logic in one single place (within your model layer) – and have all controllers/views across your application immediately reflect it.  This help keep your application code clean and easily maintainable, and makes it much easier to evolve and update your application in the future. Summary EF Code First (starting with CTP5) now has built-in support for both DataAnnotations and the IValidatableObject interface.  This allows you to easily add validation and business rules to your models, and have EF automatically ensure that they are enforced anytime someone tries to persist changes of them to a database.  ASP.NET MVC 3 also now supports both DataAnnotations and IValidatableObject as well, which makes it even easier to use them with your EF Code First model layer – and then have the controllers/views within your web layer automatically honor and support them as well.  This makes it easy to build clean and highly maintainable applications. You don’t have to use DataAnnotations or IValidatableObject to perform your validation/business logic.  You can always roll your own custom validation architecture and/or use other more advanced validation frameworks/patterns if you want.  But for a lot of applications this built-in support will probably be sufficient – and provide a highly productive way to build solutions. Hope this helps, Scott P.S. In addition to blogging, I am also now using Twitter for quick updates and to share links. Follow me at: twitter.com/scottgu

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  • Data Governance 2010 Conference in San Diego

    - by Tony Ouk
    The Data Governance Annual Conference is one of the world's most authoritative and vendor neutral event on Data Governance and Data Quality.  The conference will focus on the "how-tos" from starting a data governance and stewardship program to attaining data governance maturity with specific topics on MDM.  This year's event will be hosted June 7 through June 10 in San Diego, California. For more information, including registration details, visit the Data Governance 2010 Conference website.

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  • How to search for newline or linebreak characters in Excel?

    - by Highly Irregular
    I've imported some data into Excel (from a text file) and it contains some sort of newline characters. It looks like this initially: If I hit F2 (to edit) then Enter (to save changes) on each of the cells with a newline (without actually editing anything), Excel automatically changes the layout to look like this: I don't want these newlines characters here, as it messes up data processing further down the track. How can I do a search for these to detect more of them? The usual search function doesn't accept an enter character as a search character.

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  • Oracle Data Integration 12c: Simplified, Future-Ready, High-Performance Solutions

    - by Thanos Terentes Printzios
    In today’s data-driven business environment, organizations need to cost-effectively manage the ever-growing streams of information originating both inside and outside the firewall and address emerging deployment styles like cloud, big data analytics, and real-time replication. Oracle Data Integration delivers pervasive and continuous access to timely and trusted data across heterogeneous systems. Oracle is enhancing its data integration offering announcing the general availability of 12c release for the key data integration products: Oracle Data Integrator 12c and Oracle GoldenGate 12c, delivering Simplified and High-Performance Solutions for Cloud, Big Data Analytics, and Real-Time Replication. The new release delivers extreme performance, increase IT productivity, and simplify deployment, while helping IT organizations to keep pace with new data-oriented technology trends including cloud computing, big data analytics, real-time business intelligence. With the 12c release Oracle becomes the new leader in the data integration and replication technologies as no other vendor offers such a complete set of data integration capabilities for pervasive, continuous access to trusted data across Oracle platforms as well as third-party systems and applications. Oracle Data Integration 12c release addresses data-driven organizations’ critical and evolving data integration requirements under 3 key themes: Future-Ready Solutions : Supporting Current and Emerging Initiatives Extreme Performance : Even higher performance than ever before Fast Time-to-Value : Higher IT Productivity and Simplified Solutions  With the new capabilities in Oracle Data Integrator 12c, customers can benefit from: Superior developer productivity, ease of use, and rapid time-to-market with the new flow-based mapping model, reusable mappings, and step-by-step debugger. Increased performance when executing data integration processes due to improved parallelism. Improved productivity and monitoring via tighter integration with Oracle GoldenGate 12c and Oracle Enterprise Manager 12c. Improved interoperability with Oracle Warehouse Builder which enables faster and easier migration to Oracle Data Integrator’s strategic data integration offering. Faster implementation of business analytics through Oracle Data Integrator pre-integrated with Oracle BI Applications’ latest release. Oracle Data Integrator also integrates simply and easily with Oracle Business Analytics tools, including OBI-EE and Oracle Hyperion. Support for loading and transforming big and fast data, enabled by integration with big data technologies: Hadoop, Hive, HDFS, and Oracle Big Data Appliance. Only Oracle GoldenGate provides the best-of-breed real-time replication of data in heterogeneous data environments. With the new capabilities in Oracle GoldenGate 12c, customers can benefit from: Simplified setup and management of Oracle GoldenGate 12c when using multiple database delivery processes via a new Coordinated Delivery feature for non-Oracle databases. Expanded heterogeneity through added support for the latest versions of major databases such as Sybase ASE v 15.7, MySQL NDB Clusters 7.2, and MySQL 5.6., as well as integration with Oracle Coherence. Enhanced high availability and data protection via integration with Oracle Data Guard and Fast-Start Failover integration. Enhanced security for credentials and encryption keys using Oracle Wallet. Real-time replication for databases hosted on public cloud environments supported by third-party clouds. Tight integration between Oracle Data Integrator 12c and Oracle GoldenGate 12c and other Oracle technologies, such as Oracle Database 12c and Oracle Applications, provides a number of benefits for organizations: Tight integration between Oracle Data Integrator 12c and Oracle GoldenGate 12c enables developers to leverage Oracle GoldenGate’s low overhead, real-time change data capture completely within the Oracle Data Integrator Studio without additional training. Integration with Oracle Database 12c provides a strong foundation for seamless private cloud deployments. Delivers real-time data for reporting, zero downtime migration, and improved performance and availability for Oracle Applications, such as Oracle E-Business Suite and ATG Web Commerce . Oracle’s data integration offering is optimized for Oracle Engineered Systems and is an integral part of Oracle’s fast data, real-time analytics strategy on Oracle Exadata Database Machine and Oracle Exalytics In-Memory Machine. Oracle Data Integrator 12c and Oracle GoldenGate 12c differentiate the new offering on data integration with these many new features. This is just a quick glimpse into Oracle Data Integrator 12c and Oracle GoldenGate 12c. Find out much more about the new release in the video webcast "Introducing 12c for Oracle Data Integration", where customer and partner speakers, including SolarWorld, BT, Rittman Mead will join us in launching the new release. Resource Kits Meet Oracle Data Integration 12c  Discover what's new with Oracle Goldengate 12c  Oracle EMEA DIS (Data Integration Solutions) Partner Community is available for all your questions, while additional partner focused webcasts will be made available through our blog here, so stay connected. For any questions please contact us at partner.imc-AT-beehiveonline.oracle-DOT-com Stay Connected Oracle Newsletters

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  • Building a Data Mart with Pentaho Data Integration Video Review by Diethard Steiner, Packt Publishing

    - by Compudicted
    Originally posted on: http://geekswithblogs.net/Compudicted/archive/2014/06/01/building-a-data-mart-with-pentaho-data-integration-video-review.aspx The Building a Data Mart with Pentaho Data Integration Video by Diethard Steiner from Packt Publishing is more than just a course on how to use Pentaho Data Integration, it also implements and uses the principals of the Data Warehousing (and I even heard the name of Ralph Kimball in the video). Indeed, a video watcher should be familiar with its concepts as the Star Schema, Slowly Changing Dimension types, etc. so I suggest prior to watching this course to consider skimming through the Data Warehouse concepts (if unfamiliar) or even better, read the excellent Ralph’s The Data Warehouse Tooolkit. By the way, the author expands beyond using Pentaho along to MySQL and MonetDB which is a real icing on the cake! Indeed, I even suggest the name of the course should be ‘Building a Data Warehouse with Pentaho’. To successfully complete the course one needs to know some Linux (Ubuntu used in the course), the VI editor and the Bash command shell, but it seems that similar requirements would also apply to the Weindows OS. Additionally, knowing some basic SQL would not hurt. As I had said, MonetDB is used in this course several times which seems to be not anymore complex than say MySQL, but based on what I read is very well suited for fast querying big volumes of data thanks to having a columnstore (vertical data storage). I don’t see what else can be a barrier, the material is very digestible. On this note, I must add that the author does not cover how to acquire the software, so here is what I found may help: Pentaho: the free Community Edition must be more than anyone needs to learn it. Or even go into a POC. MonetDB can be downloaded (exists for both, Linux and Windows) from http://goo.gl/FYxMy0 (just see the appropriate link on the left). The author seems to be using Eclipse to run SQL code, one can get it from http://goo.gl/5CcuN. To create, or edit database entities and/or schema otherwise one can use a universal tool called SQuirreL, get it from http://squirrel-sql.sourceforge.net.   Next, I must confess Diethard is very knowledgeable in what he does and beyond. However, there will be some accent heard to the user of the course especially if one’s mother tongue language is English, but it I got over it in a few chapters. I liked the rate at which the material is being presented, it makes me feel I paid for every second Eventually, my impressions are: Pentaho is an awesome ETL offering, it is worth learning it very much (I am an ETL fan and a heavy user of SSIS) MonetDB is nice, it tickles my fancy to know it more Data Warehousing, despite all the BigData tool offerings (Hive, Scoop, Pig on Hadoop), using the traditional tools still rocks Chapters 2 to 6 were the most fun to me with chapter 8 being the most difficult.   In terms of closing, I highly recommend this video to anyone who needs to grasp Pentaho concepts quick, likewise, the course is very well suited for any developer on a “supposed to be done yesterday” type of a project. It is for a beginner to intermediate level ETL/DW developer. But one would need to learn more on Data Warehousing and Pentaho, for such I recommend the 5 star Pentaho Data Integration 4 Cookbook. Enjoy it! Disclaimer: I received this video from the publisher for the purpose of a public review.

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  • Building a Data Mart with Pentaho Data Integration Video Review by Diethard Steiner, Packt Publishing

    - by Compudicted
    Originally posted on: http://geekswithblogs.net/Compudicted/archive/2014/06/01/building-a-data-mart-with-pentaho-data-integration-video-review-again.aspx The Building a Data Mart with Pentaho Data Integration Video by Diethard Steiner from Packt Publishing is more than just a course on how to use Pentaho Data Integration, it also implements and uses the principals of the Data Warehousing (and I even heard the name of Ralph Kimball in the video). Indeed, a video watcher should be familiar with its concepts as the Star Schema, Slowly Changing Dimension types, etc. so I suggest prior to watching this course to consider skimming through the Data Warehouse concepts (if unfamiliar) or even better, read the excellent Ralph’s The Data Warehouse Tooolkit. By the way, the author expands beyond using Pentaho along to MySQL and MonetDB which is a real icing on the cake! Indeed, I even suggest the name of the course should be ‘Building a Data Warehouse with Pentaho’. To successfully complete the course one needs to know some Linux (Ubuntu used in the course), the VI editor and the Bash command shell, but it seems that similar requirements would also apply to the Windows OS. Additionally, knowing some basic SQL would not hurt. As I had said, MonetDB is used in this course several times which seems to be not anymore complex than say MySQL, but based on what I read is very well suited for fast querying big volumes of data thanks to having a columnstore (vertical data storage). I don’t see what else can be a barrier, the material is very digestible. On this note, I must add that the author does not cover how to acquire the software, so here is what I found may help: Pentaho: the free Community Edition must be more than anyone needs to learn it. Or even go into a POC. MonetDB can be downloaded (exists for both, Linux and Windows) from http://goo.gl/FYxMy0 (just see the appropriate link on the left). The author seems to be using Eclipse to run SQL code, one can get it from http://goo.gl/5CcuN. To create, or edit database entities and/or schema otherwise one can use a universal tool called SQuirreL, get it from http://squirrel-sql.sourceforge.net.   Next, I must confess Diethard is very knowledgeable in what he does and beyond. However, there will be some accent heard to the user of the course especially if one’s mother tongue language is English, but it I got over it in a few chapters. I liked the rate at which the material is being presented, it makes me feel I paid for every second Eventually, my impressions are: Pentaho is an awesome ETL offering, it is worth learning it very much (I am an ETL fan and a heavy user of SSIS) MonetDB is nice, it tickles my fancy to know it more Data Warehousing, despite all the BigData tool offerings (Hive, Scoop, Pig on Hadoop), using the traditional tools still rocks Chapters 2 to 6 were the most fun to me with chapter 8 being the most difficult.   In terms of closing, I highly recommend this video to anyone who needs to grasp Pentaho concepts quick, likewise, the course is very well suited for any developer on a “supposed to be done yesterday” type of a project. It is for a beginner to intermediate level ETL/DW developer. But one would need to learn more on Data Warehousing and Pentaho, for such I recommend the 5 star Pentaho Data Integration 4 Cookbook. Enjoy it! Disclaimer: I received this video from the publisher for the purpose of a public review.

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  • Reminder - Mobile World Congress - 4 Industry Workshops

    - by michael.seback
    Got 4G? Paving the Road to Profitable and Efficient LTE Network Planning and Monetization, Register by emailing your details here. Achieving Management Excellence through Enterprise Performance Management, Register by emailing your details here. Offer Deliver and Monetize: Mobile Operator Strategies Consumer and Enterprise Services featuring Telenor and Vodafone Groups, Register by emailing your details here. Is Your Head in the Cloud? How to Get it Right the First Time, Register by emailing your details here. With more than 49,000 communications industry attendees, Mobile World Congress is where the industry comes together and you won't want to miss Oracle at this year's show. The 2011 conference agenda will feature speakers representing the leaders of the world's most innovative companies, both from within the Communications industry and from the growing number of adjacent market sectors joining our expanding mobile ecosystem. Join us to learn how Oracle enables innovative services while reducing the cost and complexity of infrastructure software and hardware.

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  • Internal Mutation of Persistent Data Structures

    - by Greg Ros
    To clarify, when I mean use the terms persistent and immutable on a data structure, I mean that: The state of the data structure remains unchanged for its lifetime. It always holds the same data, and the same operations always produce the same results. The data structure allows Add, Remove, and similar methods that return new objects of its kind, modified as instructed, that may or may not share some of the data of the original object. However, while a data structure may seem to the user as persistent, it may do other things under the hood. To be sure, all data structures are, internally, at least somewhere, based on mutable storage. If I were to base a persistent vector on an array, and copy it whenever Add is invoked, it would still be persistent, as long as I modify only locally created arrays. However, sometimes, you can greatly increase performance by mutating a data structure under the hood. In more, say, insidious, dangerous, and destructive ways. Ways that might leave the abstraction untouched, not letting the user know anything has changed about the data structure, but being critical in the implementation level. For example, let's say that we have a class called ArrayVector implemented using an array. Whenever you invoke Add, you get a ArrayVector build on top of a newly allocated array that has an additional item. A sequence of such updates will involve n array copies and allocations. Here is an illustration: However, let's say we implement a lazy mechanism that stores all sorts of updates -- such as Add, Set, and others in a queue. In this case, each update requires constant time (adding an item to a queue), and no array allocation is involved. When a user tries to get an item in the array, all the queued modifications are applied under the hood, requiring a single array allocation and copy (since we know exactly what data the final array will hold, and how big it will be). Future get operations will be performed on an empty cache, so they will take a single operation. But in order to implement this, we need to 'switch' or mutate the internal array to the new one, and empty the cache -- a very dangerous action. However, considering that in many circumstances (most updates are going to occur in sequence, after all), this can save a lot of time and memory, it might be worth it -- you will need to ensure exclusive access to the internal state, of course. This isn't a question about the efficacy of such a data structure. It's a more general question. Is it ever acceptable to mutate the internal state of a supposedly persistent or immutable object in destructive and dangerous ways? Does performance justify it? Would you still be able to call it immutable? Oh, and could you implement this sort of laziness without mutating the data structure in the specified fashion?

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  • Sabre Manages Fast Data Growth with Oracle Data Integration Products

    - by Irem Radzik
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} Last year at OpenWorld we announced Sabre Holding as a winner of the Fusion Middleware Innovation Awards. The Sabre team did an excellent job at leveraging cutting edge technologies for managing rapid data growth and exponential scalability demands they have experienced in the travel industry. Today we announced the details and specific benefits of Sabre’s new real-time data integration solution in a press release. Please take a look if you haven’t seen it yet. Sabre Holdings Deploys Oracle Data Integrator and Oracle GoldenGate to Support Rapid Customer Growth There are 3 different areas of benefits Sabre achieved by using Oracle Data Integration products: Manages 7X increase in data sources for the enterprise data warehouse Reduced infrastructure complexity Decreased time to market for new products and services by 30 percent. This simply shows that using latest technologies helps the companies to innovate robust solutions against today’s key data management challenges. And the benefit of using a next generation data integration technology is not only seen in the IT operations, but also in the business side. A better data integration solution for the enterprise data warehouse delivered the platform they need to accelerate how they service their customers, improving their competitive advantage. Tomorrow I will give another great example of innovation with next generation data integration from Oracle. We will be discussing the Fusion Middleware Innovation Awards 2012 winners and their results with using Oracle’s data integration products.

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  • Can I get enough experience to get an industry job just by reading books?

    - by MahanGM
    I've been recently working with DirectX and getting familiar with game engines, sub-systems and have done game development for the last 5 years. I have a real question for those whom have worked in larger game making companies before. How is it possible to get to into these big game creators such as Ubisoft, Infinity Ward or EA. I'm not a beginner in my field and I'm going to produce a real nice 2D platform with my team this year, which is the result of 5 years 2D game creation experience. I'm working with prepared engines such as Unity3D or Game Maker software and using .Net with C# to write many tools for our production and proceeding in my way but never had a real engine programming experience 'till now. I'm now reading good books around this topic but I wanted to know: Is it possible to become an employee in big game company by just reading books? I mean beside having an active mind and new ideas and being a solution solver.

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  • implementing dynamic query handler on historical data

    - by user2390183
    EDIT : Refined question to focus on the core issue Context: I have historical data about property (house) sales collected from various sources in a centralized/cloud data source (assume info collection is handled by a third party) Planning to develop an application to query and retrieve data from this centralized data source Example Queries: Simple : for given XYZ post code, what is average house price for 3 bed room house? Complex: What is estimated price for an house at "DD,Some Street,XYZ Post Code" (worked out from average values of historic data filtered by various characteristics of the house: house post code, no of bed rooms, total area, and other deeper insights like house building type, year of built, features)? In addition to average price, the application should support other property info ** maximum, or minimum price..etc and trend (graph) on a selected property attribute over a period of time**. Hence, the queries should not enforce the search based on a primary key or few fixed fields In other words, queries can be What is the change in 3 Bed Room house price (irrespective of location) over last 30 days? What kind of properties we can get for X price (irrespective of location or house type) The challenge I have is identifying the domain (BI/ Data Analytical or DB Design or DB Query Interface or DW related or something else) this problem (dynamic query on historic data) belong to, so that I can do further exploration My findings so far I could be wrong on the following, so please correct me if you think so I briefly read about BI/Data Analytics - I think it is heavy weight solution for my problem and has scalability issues. DB Design - As I understand RDBMS works well if you know Data model at design time. I am expecting attributes about property or other entity (user) that am going to bring in, would evolve quickly. hence maintenance would be an issue. As I am going to have multiple users executing query at same time, performance would be a bottleneck Other options like Graph DB (http://www.tinkerpop.com/) seems to be bit complex (they are good. but using those tools meant for generic purpose, make me think like assembly programming to solve my problem ) BigData related solution are to analyse data from multiple unrelated domains So, Any suggestion on the space this problem fit in ? (Especially if you have design/implementation experience of back-end for property listing or similar portals)

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