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  • a firefox/chrome extension to darken pages & reduce eye strain?

    - by megafish
    I've been trying a ff plugin called Stylish, which overrides css in websites. The only problem is there is no way to toggle back to standard view. Because i work as a web designer/developer i need an extension for either chrome or ff that can do this and then i'll use that for my primary 'browsing' browser any tips would be greatly appreciated! ps. I've also tried changing colors in firefoxsettingscontentcolors but again there is no quick toggle

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  • Is there a Chrome extension to swap out CSS?

    - by fredley
    I'm trying to completely replace the CSS for a domain with different CSS (i.e. swap out the CSS at gaming.SE for that of Stack Overflow). I'd ideally like an extension that lets me do this. I've used Personalized Web, which allows loading in CSS for a given domain, but it still loads the original CSS (you can specify CSS to ignore, but you have to do this rule by rule! Does anyone know of a way of doing this?

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  • How can I tell Notepad++ to always use a particular language with a particular file extension.

    - by MatrixFrog
    I've associated .xul with Notepad++ so if I double-click on a .xul file, it will open in Notepad++. But Notepad++ doesn't know that XUL is just a particular type of XML, so I then have to manually click on "Language XML" to get XML syntax highlighting. Is there a way that I can tell it: "every time you open a file with the extension .xul, automatically switch to the XML language"?

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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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  • SQLAuthority News – Technical Review of Learning at Koenig Solutions

    - by pinaldave
    Yesterday I finished my 3 days fast track in person learning of course End to End SQL Server Business Intelligence at Koenig Solutions. You can read my previous article over here regarding why am I learning SQL Server. Yesterday I blogged about my experience of arriving to Training Center and my induction with the center. The Training Days I had enrolled for three days training so my routine each of the three days was very much same. However, the content every day was different as I was learning something new every day. Let me describe a few of the interesting details of my daily routine. A Single Student Batch The best part of my training was that in my training batch, I am single student. Koenig is known to smaller batches and often they have single student batches as well. I was very much delighted to know that I will have dedicated access and attention from my trainer in my batch as I will be single student in my batch. In most of the labs I have observed there are no more than 4 students at any time. Prakash and Pinal 7:30 AM Breakfast Talk We all students gather at 7:30 in breakfast area. The best time of the day. I was the only Indian student in the group. The other students were from USA, Canada, Nigeria, Bhutan, Tanzania, and a few others from other countries. I immediately become the source of information and reference manual. Though the distance between Delhi and Bangalore is 2000+ KM I was considered as a local guy. 8:30 AMHeading to Training Center Every day without fail at 8:30 the van started from our accommodation to the training center. As mentioned in an earlier blog post the distance is about 5 minutes and we were able to reach at the location before 8:45. This gave us some time settle in before our class starts at 9:00 AM. 9:00 AM Order Lunch Food Well it may sound funny that we just had breakfast 30 minutes but the first thing everybody has to do is to order lunch as soon as the class starts. There is an online training portal to order food for the day. Everybody has to place their order early during the day so the food arrives on time during lunch time. Everybody can order whatever they want to order using an online ordering system. The options are plenty and everybody can order what they like. 9:05 AM Learning Starts After deciding the lunch we started the learning. I was very fortunate to have a very experienced trainer - Prakash Chheatry. Though I have never met him before I have heard a lot about Prakash. He is known as the top most SQL Server Trainer in India. His student list contains some of the very well known SQL Server Experts of the world and few of SQL Server “best seller” book authors. Learning continues till 1:00 PM with one tea-coffee break in between. 1:00 PM Lunch The lunch time is again the fun time. We all students get together in the afternoon and tell the stories of the world. Indeed the best part of the day beside learning new stuff. 4:55 PM Ready to Return We stop at 4:55 as at precisely 5:00 PM the van stops by the institute which takes us back to our accommodation. Trust me seriously long long day always but the amount of the learning is the win of the day. 7:30 PM Dinner Time After coming back to the accommodation I study till 7:30 and then rush for dinner. Dinner is world cuisine and deserts are really delicious. After dinner every day I have written a blog and retired early as the next day is always going to be busier than the present day. What did I learn As I mentioned earlier I know SQL Server fairly well. I had expressed the same in my conversation as well. This is the reason I was assigned a fairly senior trainer and we learned everything quite quickly. As I know quite a few things we went pretty fast in many topics. There were a few things, I wanted to learn in detail as well practice on the labs. We slowed down where we wanted and rush through the concepts where I was very comfortable. Here is the list of the things which we covered in action pack three days. Introduction to Business Intelligence (Intro) SQL Server Analysis Service (Theory and Lab) SQL Server Integration Service  (Theory and Lab) SQL Server Reporting Service  (Theory and Lab) SQL Server PowerPivot (Lab) UDM (Theory) SharePoint Concepts (Theory) Power View (Demo) Business Intelligence and Security (Discussion) Well, I was delighted that I was able to refresh lots of concepts during these three days. Thanks to my trainer and my friend who helped me to have a good learning experience. I believe all the learning  will help me in my growth and future career. With this I end my this experience. I am planning to have another online learning experience later this month. I will blog about my experience as I begin it. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Training, T SQL, Technology

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  • SQL SERVER – Capturing Wait Types and Wait Stats Information at Interval – Wait Type – Day 5 of 28

    - by pinaldave
    Earlier, I have tried to cover some important points about wait stats in detail. Here are some points that we had covered earlier. DMV related to wait stats reset when we reset SQL Server services DMV related to wait stats reset when we manually reset the wait types However, at times, there is a need of making this data persistent so that we can take a look at them later on. Sometimes, performance tuning experts do some modifications to the server and try to measure the wait stats at that point of time and after some duration. I use the following method to measure the wait stats over the time. -- Create Table CREATE TABLE [MyWaitStatTable]( [wait_type] [nvarchar](60) NOT NULL, [waiting_tasks_count] [bigint] NOT NULL, [wait_time_ms] [bigint] NOT NULL, [max_wait_time_ms] [bigint] NOT NULL, [signal_wait_time_ms] [bigint] NOT NULL, [CurrentDateTime] DATETIME NOT NULL, [Flag] INT ) GO -- Populate Table at Time 1 INSERT INTO MyWaitStatTable ([wait_type],[waiting_tasks_count],[wait_time_ms],[max_wait_time_ms],[signal_wait_time_ms], [CurrentDateTime],[Flag]) SELECT [wait_type],[waiting_tasks_count],[wait_time_ms],[max_wait_time_ms],[signal_wait_time_ms], GETDATE(), 1 FROM sys.dm_os_wait_stats GO ----- Desired Delay (for one hour) WAITFOR DELAY '01:00:00' -- Populate Table at Time 2 INSERT INTO MyWaitStatTable ([wait_type],[waiting_tasks_count],[wait_time_ms],[max_wait_time_ms],[signal_wait_time_ms], [CurrentDateTime],[Flag]) SELECT [wait_type],[waiting_tasks_count],[wait_time_ms],[max_wait_time_ms],[signal_wait_time_ms], GETDATE(), 2 FROM sys.dm_os_wait_stats GO -- Check the difference between Time 1 and Time 2 SELECT T1.wait_type, T1.wait_time_ms Original_WaitTime, T2.wait_time_ms LaterWaitTime, (T2.wait_time_ms - T1.wait_time_ms) DiffenceWaitTime FROM MyWaitStatTable T1 INNER JOIN MyWaitStatTable T2 ON T1.wait_type = T2.wait_type WHERE T2.wait_time_ms > T1.wait_time_ms AND T1.Flag = 1 AND T2.Flag = 2 ORDER BY DiffenceWaitTime DESC GO -- Clean up DROP TABLE MyWaitStatTable GO If you notice the script, I have used an additional column called flag. I use it to find out when I have captured the wait stats and then use it in my SELECT query to SELECT wait stats related to that time group. Many times, I select more than 5 or 6 different set of wait stats and I find this method very convenient to find the difference between wait stats. In a future blog post, we will talk about specific wait stats. Read all the post in the Wait Types and Queue series. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL DMV, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • Big Data – Interacting with Hadoop – What is PIG? – What is PIG Latin? – Day 16 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the HIVE in Big Data Story. In this article we will understand what is PIG and PIG Latin in Big Data Story. Yahoo started working on Pig for their application deployment on Hadoop. The goal of Yahoo to manage their unstructured data. What is Pig and What is Pig Latin? Pig is a high level platform for creating MapReduce programs used with Hadoop and the language we use for this platform is called PIG Latin. The pig was designed to make Hadoop more user-friendly and approachable by power-users and nondevelopers. PIG is an interactive execution environment supporting Pig Latin language. The language Pig Latin has supported loading and processing of input data with series of transforming to produce desired results. PIG has two different execution environments 1) Local Mode – In this case all the scripts run on a single machine. 2) Hadoop – In this case all the scripts run on Hadoop Cluster. Pig Latin vs SQL Pig essentially creates set of map and reduce jobs under the hoods. Due to same users does not have to now write, compile and build solution for Big Data. The pig is very similar to SQL in many ways. The Ping Latin language provide an abstraction layer over the data. It focuses on the data and not the structure under the hood. Pig Latin is a very powerful language and it can do various operations like loading and storing data, streaming data, filtering data as well various data operations related to strings. The major difference between SQL and Pig Latin is that PIG is procedural and SQL is declarative. In simpler words, Pig Latin is very similar to SQ Lexecution plan and that makes it much easier for programmers to build various processes. Whereas SQL handles trees naturally, Pig Latin follows directed acyclic graph (DAG). DAGs is used to model several different kinds of structures in mathematics and computer science. DAG Tomorrow In tomorrow’s blog post we will discuss about very important components of the Big Data Ecosystem – Zookeeper. 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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  • TechEd 2012: Day 3 &ndash; Build Me A Solution

    - by Tim Murphy
    While digesting my lunch it was time to digest some TFS Build information. While much of my time is spent wearing my developer’s hat I am still a jack of all trades and automated builds are an important aspect of any project.  Because of this I was looking forward to finding out what new features are available in the latest release of Team Foundation Server. The first feature that caught my attention is the TFS Admin Client.  After being used to dealing with NAnt in the past it is nice to see a build a configuration GUI that is so flexible and well thought out.  The bonus is that it the tools that are incorporated in Visual Studio 2012 are just as feature rich.  Life is good. Since automated builds are the hub of your development process in a continuous integration shop I was really interested in the process related options. The biggest value add that I noticed was merge gated check-ins.  Merge or batch gated check-ins are an interesting concept.  If the build breaks with all the changes then TFS will run separate builds for each of the check-ins.  This ability to identify the actual offending check-in can save a lot of time and gray hair. The safari of TFS Build that was this session was packed with attractions.  How do you set it up builds, what are the different flavors of builds, how does the system report how the build went?  I would suggest anyone who is responsible for build automation spend some serious time with TFS 2012 and VS2012. del.icio.us Tags: Team Foundation Server 2012,TFS,Build,TechEd,TechEd 2012,Visual Studio 2012

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  • Big Data – Operational Databases Supporting Big Data – Key-Value Pair Databases and Document Databases – Day 13 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the Relational Database and NoSQL database in the Big Data Story. In this article we will understand the role of Key-Value Pair Databases and Document Databases Supporting Big Data Story. Now we will see a few of the examples of the operational databases. Relational Databases (Yesterday’s post) NoSQL Databases (Yesterday’s post) Key-Value Pair Databases (This post) Document Databases (This post) Columnar Databases (Tomorrow’s post) Graph Databases (Tomorrow’s post) Spatial Databases (Tomorrow’s post) Key Value Pair Databases Key Value Pair Databases are also known as KVP databases. A key is a field name and attribute, an identifier. The content of that field is its value, the data that is being identified and stored. They have a very simple implementation of NoSQL database concepts. They do not have schema hence they are very flexible as well as scalable. The disadvantages of Key Value Pair (KVP) database are that they do not follow ACID (Atomicity, Consistency, Isolation, Durability) properties. Additionally, it will require data architects to plan for data placement, replication as well as high availability. In KVP databases the data is stored as strings. Here is a simple example of how Key Value Database will look like: Key Value Name Pinal Dave Color Blue Twitter @pinaldave Name Nupur Dave Movie The Hero As the number of users grow in Key Value Pair databases it starts getting difficult to manage the entire database. As there is no specific schema or rules associated with the database, there are chances that database grows exponentially as well. It is very crucial to select the right Key Value Pair Database which offers an additional set of tools to manage the data and provides finer control over various business aspects of the same. Riak Rick is one of the most popular Key Value Database. It is known for its scalability and performance in high volume and velocity database. Additionally, it implements a mechanism for collection key and values which further helps to build manageable system. We will further discuss Riak in future blog posts. Key Value Databases are a good choice for social media, communities, caching layers for connecting other databases. In simpler words, whenever we required flexibility of the data storage keeping scalability in mind – KVP databases are good options to consider. Document Database There are two different kinds of document databases. 1) Full document Content (web pages, word docs etc) and 2) Storing Document Components for storage. The second types of the document database we are talking about over here. They use Javascript Object Notation (JSON) and Binary JSON for the structure of the documents. JSON is very easy to understand language and it is very easy to write for applications. There are two major structures of JSON used for Document Database – 1) Name Value Pairs and 2) Ordered List. MongoDB and CouchDB are two of the most popular Open Source NonRelational Document Database. MongoDB MongoDB databases are called collections. Each collection is build of documents and each document is composed of fields. MongoDB collections can be indexed for optimal performance. MongoDB ecosystem is highly available, supports query services as well as MapReduce. It is often used in high volume content management system. CouchDB CouchDB databases are composed of documents which consists fields and attachments (known as description). It supports ACID properties. The main attraction points of CouchDB are that it will continue to operate even though network connectivity is sketchy. Due to this nature CouchDB prefers local data storage. Document Database is a good choice of the database when users have to generate dynamic reports from elements which are changing very frequently. A good example of document usages is in real time analytics in social networking or content management system. 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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  • iPad Jailbreak &ndash; On The Lam In A Single Day

    - by David Totzke
    Exploits to jailbreak the iPhone are well known.  The iPad runs on the iPhone 3.2 firmware.  What this means is that the iPad was shipped with known security vulnerabilities that would allow someone to gain root access to the device. Nice. It’s not like these are security vulnerabilities that are known but have no exploits.  The exploits are numerous and freely available. Of course, if you fit the demographic, you probably have nothing to worry about. Magical and Revolutionary?  Hardly. Dave Just because I can…

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  • Windows.Threading.Dispatcher' does not contain a definition for 'RunAsync' and no extension method 'RunAsync' accepting a first argument of type

    - by suhail mehdi
    public MainPage() { InitializeComponent(); offline.Visibility = (Network.IsConnected ? Visibility.Collapsed : Visibility.Visible); Network.InternetConnectionChanged += async (s, e) => { await Dispatcher.RunAsync(CoreDispatcherPriority.Normal, () => { offline.Visibility = (e.IsConnected ? Visibility.Collapsed : Visibility.Visible); }); }; }

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  • Oracle Applications Day 2012. Experience the Global Innovation of Management Applications

    - by antonella.buonagurio
    1024x768 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:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; 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-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} 1024x768 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:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; 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-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} 10 ottobre 2012 – Milano, East End Studios | 17 ottobre 2012 - Roma, Officine Farneto Partecipa all’appuntamento dedicato alla comunità di Clienti e Partner per fare networking e condividere le esperienze sulle soluzioni più innovative per affrontare le sfide attuali e future. 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:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; 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-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} A Milano (10/10/2012) interverranno, tra gli altri:  Enrico Ancona, Amministratore Delegato - Imperia & Monferrina e Business Reply  Massimiliano Gerli, CIO - Amplifon e Michele Paolin, Senior Manager - Deloitte eXtended Business Services A Roma (17/10/2012) interverranno, tra gli altri: Giulio Carone, CFO - Enel Green Power e Claudio Arcudi, Senior Executive - Accenture Gianluca D’Aniello, CIO - Sky e Giorgio Pitruzzello, Manager - Deloitte Consulting Spartaco Parente, EPD Change & Label Control - Abbott e Business Reply Sono inoltre previsti i contributi delle aziende Abbott, Aeroporto di Napoli, Amplifon, Dema Aerospace, Enel Green Power, Fiera Milano, Imperia & Monferrina, La Rinascente, Safilo, Sky, Spal,Technogym, Tiscali e Tivù che parleranno di: Innovation for Human Resources Performance Management Excellence Empower Applications with Technology (Milano) Applications for Public Sector (Roma) Next Generation Global Operations Customer Experience Revolution Oltre dieci Instant Workshop ti permetteranno di conoscere e condividere l’esperienza dei Partner e delle aziende che utilizzano le soluzioni Oracle.In più, oltre dieci Instant Workshop per conoscere e condividere l’esperienza dei Partner e delle aziende che utilizzano con successo le soluzioni Oracle. Iscriviti sul sito Partecipa al concorso fotografico Oracle I.M.A.G.E. e vinci il tuo iPad! Scatta le immagini che per te descrivono i cinque concept dell’evento (Innovation, Management, Applications, Global, Experience) e inviale per e-mail. Per iscriverti al contest visita la pagina Concorso sul sito Non perdere l’evento più “social cool” dell’anno!

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  • Big Data – How to become a Data Scientist and Learn Data Science? – Day 19 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the analytics in Big Data Story. In this article we will understand how to become a Data Scientist for Big Data Story. Data Scientist is a new buzz word, everyone seems to be wanting to become Data Scientist. Let us go over a few key topics related to Data Scientist in this blog post. First of all we will understand what is a Data Scientist. In the new world of Big Data, I see pretty much everyone wants to become Data Scientist and there are lots of people I have already met who claims that they are Data Scientist. When I ask what is their role, I have got a wide variety of answers. What is Data Scientist? Data scientists are the experts who understand various aspects of the business and know how to strategies data to achieve the business goals. They should have a solid foundation of various data algorithms, modeling and statistics methodology. What do Data Scientists do? Data scientists understand the data very well. They just go beyond the regular data algorithms and builds interesting trends from available data. They innovate and resurrect the entire new meaning from the existing data. They are artists in disguise of computer analyst. They look at the data traditionally as well as explore various new ways to look at the data. Data Scientists do not wait to build their solutions from existing data. They think creatively, they think before the data has entered into the system. Data Scientists are visionary experts who understands the business needs and plan ahead of the time, this tremendously help to build solutions at rapid speed. Besides being data expert, the major quality of Data Scientists is “curiosity”. They always wonder about what more they can get from their existing data and how to get maximum out of future incoming data. Data Scientists do wonders with the data, which goes beyond the job descriptions of Data Analysist or Business Analysist. Skills Required for Data Scientists Here are few of the skills a Data Scientist must have. Expert level skills with statistical tools like SAS, Excel, R etc. Understanding Mathematical Models Hands-on with Visualization Tools like Tableau, PowerPivots, D3. j’s etc. Analytical skills to understand business needs Communication skills On the technology front any Data Scientists should know underlying technologies like (Hadoop, Cloudera) as well as their entire ecosystem (programming language, analysis and visualization tools etc.) . Remember that for becoming a successful Data Scientist one require have par excellent skills, just having a degree in a relevant education field will not suffice. Final Note Data Scientists is indeed very exciting job profile. As per research there are not enough Data Scientists in the world to handle the current data explosion. In near future Data is going to expand exponentially, and the need of the Data Scientists will increase along with it. It is indeed the job one should focus if you like data and science of statistics. Courtesy: emc Tomorrow In tomorrow’s blog post we will discuss about various Big Data Learning resources. 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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  • Code sample after Job offer?

    - by mdominick
    I was verbally offered a job and the manager insisted that I start the day after the following day from the interview; so two days after the interview. I left the interview unsure of the offer the manager called me later that day and I agreed to take the position. At this point, I was told that I would get an offer letter the following day and would start the day after that. Later that evening I was asked for a code sample. I have yet to receive the offer letter the business day is about to close. I've been mostly contracting and usually answer technical questions or show samples at the beginning of the process and find this situation somewhat odd. Is this a common practice? Should I call the manager before business closes?

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  • Staying focussed - Any applications to monitor what windows are open, record the titles and then tell you what you spend you day doing?

    - by Rory McCann
    I am bad at procrastination. I'm always opening new tabs to check out HackerNews or something. So I've installed StayFocussed on Chromium, so that I can't view more than X minutes of certain sites. Is there something like this for the Ubuntu Desktop? It would work with applications, not websites (obviously). I would like an application that would monitor what windows I have open or visible, and limit me to only certain applications. Maybe give warnings if I spend to much time looking at IRC or something. Is there any applications for that?

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  • OPN DAY VIRTUAL EVENT FY11 le rendez-vous à ne pas manquer ! 29 juin 2010

    - by [email protected]
    Comment les dernières acquisitions et technologies Oracle permettent d'augmenter encore davantage les ventes de nos partenaires grâce à une offre logicielle et matérielle complète Quels sont les investissements continus d'Oracle pour aider nos partenaires à réussir. Comment utiliser la spécialisation pour différencier son offre partenaire, gagner en notoriété, s' imposer comme le fournisseur privilégié de ses clients et attirer de nouveaux prospects. Des entretiens avec des partenaires Oracle Specialized, un stand virtuel regorgeant d'informations téléchargeables et des discussions avec les employés d'Oracle seront également au programme, le tout en direct et en ligne ! Pour vous inscrire, cliquez ici

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  • Big Data – Interacting with Hadoop – What is Sqoop? – What is Zookeeper? – Day 17 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the Pig and Pig Latin in Big Data Story. In this article we will understand what is Sqoop and Zookeeper in Big Data Story. There are two most important components one should learn when learning about interacting with Hadoop – Sqoop and Zookper. What is Sqoop? Most of the business stores their data in RDBMS as well as other data warehouse solutions. They need a way to move data to the Hadoop system to do various processing and return it back to RDBMS from Hadoop system. The data movement can happen in real time or at various intervals in bulk. We need a tool which can help us move this data from SQL to Hadoop and from Hadoop to SQL. Sqoop (SQL to Hadoop) is such a tool which extract data from non-Hadoop data sources and transform them into the format which Hadoop can use it and later it loads them into HDFS. Essentially it is ETL tool where it Extracts, Transform and Load from SQL to Hadoop. The best part is that it also does extract data from Hadoop and loads them to Non-SQL (or RDBMS) data stores. Essentially, Sqoop is a command line tool which does SQL to Hadoop and Hadoop to SQL. It is a command line interpreter. It creates MapReduce job behinds the scene to import data from an external database to HDFS. It is very effective and easy to learn tool for nonprogrammers. What is Zookeeper? ZooKeeper is a centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services. In other words Zookeeper is a replicated synchronization service with eventual consistency. In simpler words – in Hadoop cluster there are many different nodes and one node is master. Let us assume that master node fails due to any reason. In this case, the role of the master node has to be transferred to a different node. The main role of the master node is managing the writers as that task requires persistence in order of writing. In this kind of scenario Zookeeper will assign new master node and make sure that Hadoop cluster performs without any glitch. Zookeeper is the Hadoop’s method of coordinating all the elements of these distributed systems. Here are few of the tasks which Zookeepr is responsible for. Zookeeper manages the entire workflow of starting and stopping various nodes in the Hadoop’s cluster. In Hadoop cluster when any processes need certain configuration to complete the task. Zookeeper makes sure that certain node gets necessary configuration consistently. In case of the master node fails, Zookeepr can assign new master node and make sure cluster works as expected. There many other tasks Zookeeper performance when it is about Hadoop cluster and communication. Basically without the help of Zookeeper it is not possible to design any new fault tolerant distributed application. Tomorrow In tomorrow’s blog post we will discuss about very important components of the Big Data Ecosystem – Big Data Analytics. 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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