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• WCF data services - Limiting related objects returned based on critera

  - by Mike Morley

  I have an object graph consisting of a base employee object, and a set of related message objects. I am able to return the employee objects based on search criteria on the employee properties (eg team) etc. However, if I expand on the messages, I get the full collection of messages back. I would like to be able to either take the top n messages (i.e. restrict to 10 most recent) or ideally use a date range on the message objects to limit how many are brought back. So far I have not been able to figure out a way of doing this: I get an error if I attempt to filter on properties on the message (&$filter=employee/message/StartDate gives an error "No property 'StartDate' exists in type 'System.Data.Objects.DataClasses.EntityCollection`1). Attempting to use Top on the message related object doesn't work either. I have also tried using a WebGet extension that takes a string list of employee IDs. That works until the list gets too long, and then fails due to the URL getting too long (it might be possible to setup a paging mechanism on this approach)... Unfortunately the UI control I am using requires the data to be in a fairly specific hierarchical shape, so I can't easily come at this from starting on the message side and working backwards. Outside of making multiple calls does anyone know of a method to accomplish this with wcf data services? Thanks! M.

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• Compact data structure for storing a large set of integral values

  - by Odrade

  I'm working on an application that needs to pass around large sets of Int32 values. The sets are expected to contain ~1,000,000-50,000,000 items, where each item is a database key in the range 0-50,000,000. I expect distribution of ids in any given set to be effectively random over this range. The operations I need on the set are dirt simple: Add a new value Iterate over all of the values. There is a serious concern about the memory usage of these sets, so I'm looking for a data structure that can store the ids more efficiently than a simple List<int>or HashSet<int>. I've looked at BitArray, but that can be wasteful depending on how sparse the ids are. I've also considered a bitwise trie, but I'm unsure how to calculate the space efficiency of that solution for the expected data. A Bloom Filter would be great, if only I could tolerate the false negatives. I would appreciate any suggestions of data structures suitable for this purpose. I'm interested in both out-of-the-box and custom solutions. EDIT: To answer your questions: No, the items don't need to be sorted By "pass around" I mean both pass between methods and serialize and send over the wire. I clearly should have mentioned this. There could be a decent number of these sets in memory at once (~100).

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• Display data FROM Sheet1 on Sheet2 based on conditional value

  - by Shawn

  Imagine a worksheet with 30 pieces of information, such as: A1= Start Date A2 = End Date A3 = Resource Name A4 = Cost .... A30 = Whatever B1 = 1/1/2010 B2 = 2/15/2010 B3 = Joe Smith B4 = $10,000.00 ... B30 = Blah Blah Now imagine a third column, C. The purpose of the third column is to determine WHICH report that row of data needs to appear in. C1 = Report 1 C2 = Report 1 and Report 2 C3 = Report 4 and Report 7 C4 = Report 1 and Report 5 ... C30 = Report 2 Each report is on Sheets 2, 3, 4, 5 and so on (depending on how many I decide to create). As you can see form my example above, some data may need to appear in multiple reports. For example, the data in Row 3 (Resource Name: Joe Smith) needs to appear in Report 4 and Report 7. That is to say, it needs to DYNAMICALLY appear on two additional worksheets. If I change the values in column C, then the reports need to update automatically. How can I create the worksheets which will serve as the reports such that they only diaplay the rows which have been "flagged" to be displayed in that report? Thanks!

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• Python, web log data mining for frequent patterns

  - by descent

  Hello! I need to develop a tool for web log data mining. Having many sequences of urls, requested in a particular user session (retrieved from web-application logs), I need to figure out the patterns of usage and groups (clusters) of users of the website. I am new to Data Mining, and now examining Google a lot. Found some useful info, i.e. querying Frequent Pattern Mining in Web Log Data seems to point to almost exactly similar studies. So my questions are: Are there any python-based tools that do what I need or at least smth similar? Can Orange toolkit be of any help? Can reading the book Programming Collective Intelligence be of any help? What to Google for, what to read, which relatively simple algorithms to use best? I am very limited in time (to around a week), so any help would be extremely precious. What I need is to point me into the right direction and the advice of how to accomplish the task in the shortest time. Thanks in advance!

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• Data Integration Solution?

  - by Shlomo

  At my company we have a number of data feeds and processing that run on any given day. The number of feeds and processing steps is starting to out-number the ability to manage it ad-hoc as it is managed currently. Is there a good solution that helps with logging and managing/scheduling dependencies? For example: A: When file x is FTP dropped into directory D1, kick off processing step B B: Load flat file into DB1 C: When file y is FTP dropped into directory D2, kick off processing Step D D: Load flat file into DB11 E: When B and D are done, churn through the data, and load new data into DB111. F: When Step E is done, launch application process P G: etc... I want those steps to run at the appropriate times, not to mention if B fails, there's no reason to run steps E & F, but I could still run C & D. When I re-run B successfully, it should trigger just E & F to re-run, not C & D. We're a .NET/C#/Sql Server shop, and I'm already familiar with SSIS. Is that really the best there is? That manages steps well, but not external dependencies, or logging. Open source (.NET) preferred, but not required.

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• Save many-to-one relationship from JSON into Core Data

  - by Snow Crash

  I'm wanting to save a Many-to-one relationship parsed from JSON into Core Data. The code that parses the JSON and does the insert into Core Data looks like this: for (NSDictionary *thisRecipe in recipes) { Recipe *recipe = [NSEntityDescription insertNewObjectForEntityForName:@"Recipe" inManagedObjectContext:insertionContext]; recipe.title = [thisRecipe objectForKey:@"Title"]; NSDictionary *ingredientsForRecipe = [thisRecipe objectForKey:@"Ingredients"]; NSArray *ingredientsArray = [ingredientsForRecipe objectForKey:@"Results"]; for (NSDictionary *thisIngredient in ingredientsArray) { Ingredient *ingredient = [NSEntityDescription insertNewObjectForEntityForName:@"Ingredient" inManagedObjectContext:insertionContext]; ingredient.name = [thisIngredient objectForKey:@"Name"]; } } NSSet *ingredientsSet = [NSSet ingredientsArray]; [recipe setIngredients:ingredientsSet]; Notes: "setIngredients" is a Core Data generated accessor method. There is a many-to-one relationship between Ingredients and Recipe However, when I run this I get the following error: NSCFDictionary managedObjectContext]: unrecognized selector sent to instance If I remove the last line (i.e. [recipe setIngredients:ingredientsSet];) then, taking a peek at the SQLite database, I see the Recipe and Ingredients have been stored but no relationship has been created between Recipe and Ingredients Any suggestions as to how to ensure the relationship is stored correctly?

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• Parallelism in .NET – Part 2, Simple Imperative Data Parallelism

  - by Reed

  In my discussion of Decomposition of the problem space, I mentioned that Data Decomposition is often the simplest abstraction to use when trying to parallelize a routine.  If a problem can be decomposed based off the data, we will often want to use what MSDN refers to as Data Parallelism as our strategy for implementing our routine.  The Task Parallel Library in .NET 4 makes implementing Data Parallelism, for most cases, very simple. Data Parallelism is the main technique we use to parallelize a routine which can be decomposed based off data.  Data Parallelism refers to taking a single collection of data, and having a single operation be performed concurrently on elements in the collection.  One side note here: Data Parallelism is also sometimes referred to as the Loop Parallelism Pattern or Loop-level Parallelism.  In general, for this series, I will try to use the terminology used in the MSDN Documentation for the Task Parallel Library.  This should make it easier to investigate these topics in more detail. Once we’ve determined we have a problem that, potentially, can be decomposed based on data, implementation using Data Parallelism in the TPL is quite simple.  Let’s take our example from the Data Decomposition discussion – a simple contrast stretching filter.  Here, we have a collection of data (pixels), and we need to run a simple operation on each element of the pixel.  Once we know the minimum and maximum values, we most likely would have some simple code like the following: for (int row=0; row < pixelData.GetUpperBound(0); ++row) { for (int col=0; col < pixelData.GetUpperBound(1); ++col) { pixelData[row, col] = AdjustContrast(pixelData[row, col], minPixel, maxPixel); } } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } This simple routine loops through a two dimensional array of pixelData, and calls the AdjustContrast routine on each pixel. As I mentioned, when you’re decomposing a problem space, most iteration statements are potentially candidates for data decomposition.  Here, we’re using two for loops – one looping through rows in the image, and a second nested loop iterating through the columns.  We then perform one, independent operation on each element based on those loop positions. This is a prime candidate – we have no shared data, no dependencies on anything but the pixel which we want to change.  Since we’re using a for loop, we can easily parallelize this using the Parallel.For method in the TPL: Parallel.For(0, pixelData.GetUpperBound(0), row => { for (int col=0; col < pixelData.GetUpperBound(1); ++col) { pixelData[row, col] = AdjustContrast(pixelData[row, col], minPixel, maxPixel); } }); Here, by simply changing our first for loop to a call to Parallel.For, we can parallelize this portion of our routine.  Parallel.For works, as do many methods in the TPL, by creating a delegate and using it as an argument to a method.  In this case, our for loop iteration block becomes a delegate creating via a lambda expression.  This lets you write code that, superficially, looks similar to the familiar for loop, but functions quite differently at runtime. We could easily do this to our second for loop as well, but that may not be a good idea.  There is a balance to be struck when writing parallel code.  We want to have enough work items to keep all of our processors busy, but the more we partition our data, the more overhead we introduce.  In this case, we have an image of data – most likely hundreds of pixels in both dimensions.  By just parallelizing our first loop, each row of pixels can be run as a single task.  With hundreds of rows of data, we are providing fine enough granularity to keep all of our processors busy. If we parallelize both loops, we’re potentially creating millions of independent tasks.  This introduces extra overhead with no extra gain, and will actually reduce our overall performance.  This leads to my first guideline when writing parallel code: Partition your problem into enough tasks to keep each processor busy throughout the operation, but not more than necessary to keep each processor busy. Also note that I parallelized the outer loop.  I could have just as easily partitioned the inner loop.  However, partitioning the inner loop would have led to many more discrete work items, each with a smaller amount of work (operate on one pixel instead of one row of pixels).  My second guideline when writing parallel code reflects this: Partition your problem in a way to place the most work possible into each task. This typically means, in practice, that you will want to parallelize the routine at the “highest” point possible in the routine, typically the outermost loop.  If you’re looking at parallelizing methods which call other methods, you’ll want to try to partition your work high up in the stack – as you get into lower level methods, the performance impact of parallelizing your routines may not overcome the overhead introduced. Parallel.For works great for situations where we know the number of elements we’re going to process in advance.  If we’re iterating through an IList<T> or an array, this is a typical approach.  However, there are other iteration statements common in C#.  In many situations, we’ll use foreach instead of a for loop.  This can be more understandable and easier to read, but also has the advantage of working with collections which only implement IEnumerable<T>, where we do not know the number of elements involved in advance. As an example, lets take the following situation.  Say we have a collection of Customers, and we want to iterate through each customer, check some information about the customer, and if a certain case is met, send an email to the customer and update our instance to reflect this change.  Normally, this might look something like: foreach(var customer in customers) { // Run some process that takes some time... DateTime lastContact = theStore.GetLastContact(customer); TimeSpan timeSinceContact = DateTime.Now - lastContact; // If it's been more than two weeks, send an email, and update... if (timeSinceContact.Days > 14) { theStore.EmailCustomer(customer); customer.LastEmailContact = DateTime.Now; } } Here, we’re doing a fair amount of work for each customer in our collection, but we don’t know how many customers exist.  If we assume that theStore.GetLastContact(customer) and theStore.EmailCustomer(customer) are both side-effect free, thread safe operations, we could parallelize this using Parallel.ForEach: Parallel.ForEach(customers, customer => { // Run some process that takes some time... DateTime lastContact = theStore.GetLastContact(customer); TimeSpan timeSinceContact = DateTime.Now - lastContact; // If it's been more than two weeks, send an email, and update... if (timeSinceContact.Days > 14) { theStore.EmailCustomer(customer); customer.LastEmailContact = DateTime.Now; } }); Just like Parallel.For, we rework our loop into a method call accepting a delegate created via a lambda expression.  This keeps our new code very similar to our original iteration statement, however, this will now execute in parallel.  The same guidelines apply with Parallel.ForEach as with Parallel.For. The other iteration statements, do and while, do not have direct equivalents in the Task Parallel Library.  These, however, are very easy to implement using Parallel.ForEach and the yield keyword. Most applications can benefit from implementing some form of Data Parallelism.  Iterating through collections and performing “work” is a very common pattern in nearly every application.  When the problem can be decomposed by data, we often can parallelize the workload by merely changing foreach statements to Parallel.ForEach method calls, and for loops to Parallel.For method calls.  Any time your program operates on a collection, and does a set of work on each item in the collection where that work is not dependent on other information, you very likely have an opportunity to parallelize your routine.

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• ERROR: Attempted to read or write protected memory. This is often an indication that other memory is corrupt

  - by SPSamL

  I get this error after having edited a few pages in SharePoint 2010. I have to do an IISReset on both front ends to get this to resolve. I don't know how to fix it or even what else to supply here, but please let me know as the resets now happen several times per day. Log Name: Application Source: ASP.NET 2.0.50727.0 Date: 1/26/2011 11:12:48 AM Event ID: 1309 Task Category: Web Event Level: Warning Keywords: Classic User: N/A Computer: PINTSPSFE02.samcstl.org Description: Event code: 3005 Event message: An unhandled exception has occurred. Event time: 1/26/2011 11:12:48 AM Event time (UTC): 1/26/2011 5:12:48 PM Event ID: c52fb336b7f147a3913fff3617a99d57 Event sequence: 4965 Event occurrence: 2178 Event detail code: 0 Application information: Application domain: /LM/W3SVC/1449762715/ROOT-2-129405348166941887 Trust level: WSS_Minimal Application Virtual Path: / Application Path: C:\inetpub\wwwroot\wss\VirtualDirectories\80\ Machine name: PINTSPSFE02 Process information: Process ID: 5928 Process name: w3wp.exe Account name: SAMC\MossAppPool Exception information: Exception type: AccessViolationException Exception message: Attempted to read or write protected memory. This is often an indication that other memory is corrupt. Request information: Request URL: http://mosscluster/Pages/Home.aspx Request path: /Pages/Home.aspx User host address: 10.3.60.26 User: SAMC\BARNMD Is authenticated: True Authentication Type: NTLM Thread account name: SAMC\MossAppPool Thread information: Thread ID: 110 Thread account name: SAMC\MossAppPool Is impersonating: False Stack trace: at Microsoft.Office.Server.ObjectCache.SPCache.MossObjectCache_Tracked.Delete(String key, Boolean recursive, DeletionReason reason) at Microsoft.Office.Server.ObjectCache.SPCache.MossObjectCache_Tracked.Get(String key) at Microsoft.Office.Server.ObjectCache.SPCache.Get(String objectTypeName, String id) at Microsoft.Office.Server.Administration.UserProfileServiceProxy.GetPartitionPropertiesCache(Guid applicationID) at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.get_PartitionPropertiesCache() at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.DataCache.get_PartitionProperties() at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.GetMySitePortalUrl(SPUrlZone zone, Guid partitionID) at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.GetMySitePortalUrl(SPUrlZone zone, SPServiceContext serviceContext) at Microsoft.Office.Server.WebControls.MyLinksRibbon.EnsureMySiteUrls() at Microsoft.Office.Server.WebControls.MyLinksRibbon.get_PortalMySiteUrlAvailable() at Microsoft.Office.Server.WebControls.MyLinksRibbon.OnLoad(EventArgs e) at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Page.ProcessRequestMain(Boolean includeStagesBeforeAsyncPoint, Boolean includeStagesAfterAsyncPoint) Custom event details: Event Xml: <Event xmlns="http://schemas.microsoft.com/win/2004/08/events/event"> <System> <Provider Name="ASP.NET 2.0.50727.0" /> <EventID Qualifiers="32768">1309</EventID> <Level>3</Level> <Task>3</Task> <Keywords>0x80000000000000</Keywords> <TimeCreated SystemTime="2011-01-26T17:12:48.000000000Z" /> <EventRecordID>35834</EventRecordID> <Channel>Application</Channel> <Computer>PINTSPSFE02.samcstl.org</Computer> <Security /> </System> <EventData> <Data>3005</Data> <Data>An unhandled exception has occurred.</Data> <Data>1/26/2011 11:12:48 AM</Data> <Data>1/26/2011 5:12:48 PM</Data> <Data>c52fb336b7f147a3913fff3617a99d57</Data> <Data>4965</Data> <Data>2178</Data> <Data>0</Data> <Data>/LM/W3SVC/1449762715/ROOT-2-129405348166941887</Data> <Data>WSS_Minimal</Data> <Data>/</Data> <Data>C:\inetpub\wwwroot\wss\VirtualDirectories\80\</Data> <Data>PINTSPSFE02</Data> <Data> </Data> <Data>5928</Data> <Data>w3wp.exe</Data> <Data>SAMC\MossAppPool</Data> <Data>AccessViolationException</Data> <Data></Data> <Data>http://mosscluster/Pages/Home.aspx</Data> <Data>/Pages/Home.aspx</Data> <Data>10.3.60.26</Data> <Data>SAMC\BARNMD</Data> <Data>True</Data> <Data>NTLM</Data> <Data>SAMC\MossAppPool</Data> <Data>110</Data> <Data>SAMC\MossAppPool</Data> <Data>False</Data> <Data> at Microsoft.Office.Server.ObjectCache.SPCache.MossObjectCache_Tracked.Delete(String key, Boolean recursive, DeletionReason reason) at Microsoft.Office.Server.ObjectCache.SPCache.MossObjectCache_Tracked.Get(String key) at Microsoft.Office.Server.ObjectCache.SPCache.Get(String objectTypeName, String id) at Microsoft.Office.Server.Administration.UserProfileServiceProxy.GetPartitionPropertiesCache(Guid applicationID) at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.get_PartitionPropertiesCache() at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.DataCache.get_PartitionProperties() at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.GetMySitePortalUrl(SPUrlZone zone, Guid partitionID) at Microsoft.Office.Server.Administration.UserProfileApplicationProxy.GetMySitePortalUrl(SPUrlZone zone, SPServiceContext serviceContext) at Microsoft.Office.Server.WebControls.MyLinksRibbon.EnsureMySiteUrls() at Microsoft.Office.Server.WebControls.MyLinksRibbon.get_PortalMySiteUrlAvailable() at Microsoft.Office.Server.WebControls.MyLinksRibbon.OnLoad(EventArgs e) at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Control.LoadRecursive() at System.Web.UI.Page.ProcessRequestMain(Boolean includeStagesBeforeAsyncPoint, Boolean includeStagesAfterAsyncPoint) </Data> </EventData> </Event>

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• Data Profiling without SSIS

  Strangely enough for a predominantly SSIS blog, this post is all about how to perform data profiling without using SSIS. Whilst the Data Profiling Task is a worthy addition, there are a couple of limitations I’ve encountered of late. The first is that it requires SQL Server 2008, and not everyone is there yet. The second is that it can only target SQL Server 2005 and above. What about older systems, which are the ones that we probably need to investigate the most, or other vendor databases such as Oracle? With these limitations in mind I did some searching to find a quick and easy alternative to help me perform some data profiling for a project I was working on recently. I only had SQL Server 2005 available, and anyway most of my target source systems were Oracle, and of course I had short timescales. I looked at several options. Some never got beyond the download stage, they failed to install or just did not run, and others provided less than I could have produced myself by spending 2 minutes writing some basic SQL queries. In the end I settled on an open source product called DataCleaner. To quote from their website: DataCleaner is an Open Source application for profiling, validating and comparing data. These activities help you administer and monitor your data quality in order to ensure that your data is useful and applicable to your business situation. DataCleaner is the free alternative to software for master data management (MDM) methodologies, data warehousing (DW) projects, statistical research, preparation for extract-transform-load (ETL) activities and more. DataCleaner is developed in Java and licensed under LGPL. As quoted above it claims to support profiling, validating and comparing data, but I didn’t really get past the profiling functions, so won’t comment on the other two. The profiling whilst not prefect certainly saved some time compared to the limited alternatives. The ability to profile heterogeneous data sources is a big advantage over the SSIS option, and I found it overall quite easy to use and performance was good. I could see it struggling at times, but actually for what it does I was impressed. It had some data type niggles with Oracle, and some metrics seem a little strange, although thankfully they were easy to augment with some SQL queries to ensure a consistent picture. The report export options didn’t do it for me, but copy and paste with a bit of Excel magic was sufficient. One initial point for me personally is that I have had limited exposure to things of the Java persuasion and whilst I normally get by fine, sometimes the simplest things can throw me. For example installing a JDBC driver, why do I have to copy files to make it all work, has nobody ever heard of an MSI? In case there are other people out there like me who have become totally indoctrinated with the Microsoft software paradigm, I’ve written a quick start guide that details every step required. Steps 1- 5 are the key ones, the rest is really an excuse for some screenshots to show you the tool. Quick Start Guide Step 1  - Download Data Cleaner. The Microsoft Windows zipped exe option, and I chose the latest stable build, currently DataCleaner 1.5.3 (final). Extract the files to a suitable location. Step 2 - Download Java. If you try and run datacleaner.exe without Java it will warn you, and then open your default browser and take you to the Java download site. Follow the installation instructions from there, normally just click Download Java a couple of times and you’re done. Step 3 - Download Microsoft SQL Server JDBC Driver. You may have SQL Server installed, but you won’t have a JDBC driver. Version 3.0 is the latest as of April 2010. There is no real installer, we are in the Java world here, but run the exe you downloaded to extract the files. The default Unzip to folder is not much help, so try a fully qualified path such as C:\Program Files\Microsoft SQL Server JDBC Driver 3.0\ to ensure you can find the files afterwards. Step 4 - If you wish to use Windows Authentication to connect to your SQL Server then first we need to copy a file so that Data Cleaner can find it. Browse to the JDBC extract location from Step 3 and drill down to the file sqljdbc_auth.dll. You will have to choose the correct directory for your processor architecture. e.g. C:\Program Files\Microsoft SQL Server JDBC Driver 3.0\sqljdbc_3.0\enu\auth\x86\sqljdbc_auth.dll. Now copy this file to the Data Cleaner extract folder you chose in Step 1. An alternative method is to edit datacleaner.cmd in the data cleaner extract folder as detailed in this data cleaner wiki topic, but I find copying the file simpler. Step 5 – Now lets run Data Cleaner, just run datacleaner.exe from the extract folder you chose in Step 1. Step 6 – Complete or skip the registration screen, and ignore the task window for now. In the main window click settings. Step 7 – In the Settings dialog, select the Database drivers tab, then click Register database driver and select the Local JAR file option. Step 8 – Browse to the JDBC driver extract location from Step 3 and drill down to select sqljdbc4.jar. e.g. C:\Program Files\Microsoft SQL Server JDBC Driver 3.0\sqljdbc_3.0\enu\sqljdbc4.jar Step 9 – Select the Database driver class as com.microsoft.sqlserver.jdbc.SQLServerDriver, and then click the Test and Save database driver button. Step 10 - You should be back at the Settings dialog with a the list of drivers that includes SQL Server. Just click Save Settings to persist all your hard work. Step 11 – Now we can start to profile some data. In the main Data Cleaner window click New Task, and then Profile from the task window. Step 12 – In the Profile window click Open Database Step 13 – Now choose the SQL Server connection string option. Selecting a connection string gives us a template like jdbc:sqlserver://<hostname>:1433;databaseName=<database>, but obviously it requires some details to be entered for example  jdbc:sqlserver://localhost:1433;databaseName=SQLBits. This will connect to the database called SQLBits on my local machine. The port may also have to be changed if using such as when you have a multiple instances of SQL Server running. If using SQL Server Authentication enter a username and password as required and then click Connect to database. You can use Window Authentication, just add integratedSecurity=true to the end of your connection string. e.g jdbc:sqlserver://localhost:1433;databaseName=SQLBits;integratedSecurity=true.  If you didn’t complete Step 4 above you will need to do so now and restart Data Cleaner before it will work. Manually setting the connection string is fine, but creating a named connection makes more sense if you will be spending any length of time profiling a specific database. As highlighted in the left-hand screen-shot, at the bottom of the dialog it includes partial instructions on how to create named connections. In the folder shown C:\Users\<Username>\.datacleaner\1.5.3, open the datacleaner-config.xml file in your editor of choice add your own details. You’ll see a sample connection in the file already, just add yours following the same pattern. e.g. <!-- Darren's Named Connections --> <bean class="dk.eobjects.datacleaner.gui.model.NamedConnection"> <property name="name" value="SQLBits Local Connection" /> <property name="driverClass" value="com.microsoft.sqlserver.jdbc.SQLServerDriver" /> <property name="connectionString" value="jdbc:sqlserver://localhost:1433;databaseName=SQLBits;integratedSecurity=true" /> <property name="tableTypes"> <list> <value>TABLE</value> <value>VIEW</value> </list> </property> </bean> Step 14 – Once back at the Profile window, you should now see your schemas, tables and/or views listed down the left hand side. Browse this tree and double-click a table to select it for profiling. You can then click Add profile, and choose some profiling options, before finally clicking Run profiling. You can see below a sample output for three of the most common profiles, click the image for full size.   I hope this has given you a taster for DataCleaner, and should help you get up and running pretty quickly.

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• Oracle Data Integration Solutions and the Oracle EXADATA Database Machine

  - by João Vilanova

  Oracle's data integration solutions provide a complete, open and integrated solution for building, deploying, and managing real-time data-centric architectures in operational and analytical environments. Fully integrated with and optimized for the Oracle Exadata Database Machine, Oracle's data integration solutions take data integration to the next level and delivers extremeperformance and scalability for all the enterprise data movement and transformation needs. Easy-to-use, open and standards-based Oracle's data integration solutions dramatically improve productivity, provide unparalleled efficiency, and lower the cost of ownership.You can watch a video about this subject, after clicking on the link below.DIS for EXADATA Video

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• BIWA Wednesday TechCast Series - Opposition to Data Warehouse Initiatives

  - by jenny.gelhausen

  BIWA Wednesday TechCast Series - 19th Event! Opposition to Data Warehouse Initiatives Please join us for this webcast on Wednesday, March 24, 12 noon Eastern or check your local area's time Webcast is open to clients, prospects and partners. No matter how good your technology and technical skills, organizational issues can derail a data warehousing or BI project. Therefore BIWA presents a vital topic that crosses product boundaries: organizational resistance to data warehouse initiatives - how to recognize it and what to do about it. Many a DW/BI professional has been surprised by organizational resistance to DW/BI initiatives. Yet real organizational imperatives may be behind this apparently irrational behavior. Based on in-depth interviews with IT professionals, industry consultants, and power users, our speaker Bruce Jenks will present his research findings about what drives organizational resistance to data warehouse initiatives. The talk will cover specific behaviors that can signal organizational resistance to a data warehouse program and what organizations have done to address such resistance. Presenter: Bruce Jenks of Dun and Bradstreet Bruce Jenks has over 20 years experience in data warehousing and business intelligence, much of it as a consultant to large organizations spanning the US. Bruce's data warehousing clients have included firms such as Sprint, Gallo Wines, Southern California Edison, The Gap, and Safeway. He started his data warehousing career at Metaphor Computers, a pioneering DW/BI firm from which a number of industry luminaries sprang including Ralph Kimball (author of The Data Warehouse Toolkit ). Bruce continued his data warehousing career at HP, Stanford University and other firms. Bruce is currently completing his doctorate in business administration at Golden Gate University, and today's material arises from his doctoral research. He is also a principal consultant for Dun and Bradstreet. Audio Dial-In: 866 682 4770 Audio Meeting ID: 1683901 Audio Meeting Passcode: 334451 Web Conference: Please register at https://www1.gotomeeting.com/register/807185273 After you register you will be provided with a link to the TechCast. Invitation to Speakers: All BIWA members and Oracle professionals (experts, end users, managers, DBAs, developers, data analysts, ISVs, partners, etc.) may submit abstracts for 45 minute technical webcasts to our Oracle BIWA (IOUG SIG) Community. Submit your BIWA TechCast abstract today! BIWA is a worldwide forum with over 2000 members who are business intelligence, warehousing and analytics professionals. BIWA presents information, experiences and best practices in successfully deploying Oracle Database-centric BI, Data Warehousing, and Analytics products, features and Options--the Oracle Database "BIWA" platform. Attendance Information & Replays at the BIWA website: oraclebiwa.org var gaJsHost = (("https:" == document.location.protocol) ? "https://ssl." : "http://www."); document.write(unescape("%3Cscript src='" + gaJsHost + "google-analytics.com/ga.js' type='text/javascript'%3E%3C/script%3E")); try { var pageTracker = _gat._getTracker("UA-13185312-1"); pageTracker._trackPageview(); } catch(err) {}

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• SQL Monitor’s data repository

  - by Chris Lambrou

  As one of the developers of SQL Monitor, I often get requests passed on by our support people from customers who are looking to dip into SQL Monitor’s own data repository, in order to pull out bits of information that they’re interested in. Since there’s clearly interest out there in playing around directly with the data repository, I thought I’d write some blog posts to start to describe how it all works. The hardest part for me is knowing where to begin, since the schema of the data repository is pretty big. Hmmm… I guess it’s tricky for anyone to write anything but the most trivial of queries against the data repository without understanding the hierarchy of monitored objects, so perhaps my first post should start there. I always imagine that whenever a customer fires up SSMS and starts to explore their SQL Monitor data repository database, they become immediately bewildered by the schema – that was certainly my experience when I did so for the first time. The following query shows the number of different object types in the data repository schema: SELECT type_desc, COUNT(*) AS [count] FROM sys.objects GROUP BY type_desc ORDER BY type_desc;  type_desccount 1DEFAULT_CONSTRAINT63 2FOREIGN_KEY_CONSTRAINT181 3INTERNAL_TABLE3 4PRIMARY_KEY_CONSTRAINT190 5SERVICE_QUEUE3 6SQL_INLINE_TABLE_VALUED_FUNCTION381 7SQL_SCALAR_FUNCTION2 8SQL_STORED_PROCEDURE100 9SYSTEM_TABLE41 10UNIQUE_CONSTRAINT54 11USER_TABLE193 12VIEW124 With 193 tables, 124 views, 100 stored procedures and 381 table valued functions, that’s quite a hefty schema, and when you browse through it using SSMS, it can be a bit daunting at first. So, where to begin? Well, let’s narrow things down a bit and only look at the tables belonging to the data schema. That’s where all of the collected monitoring data is stored by SQL Monitor. The following query gives us the names of those tables: SELECT sch.name + '.' + obj.name AS [name] FROM sys.objects obj JOIN sys.schemas sch ON sch.schema_id = obj.schema_id WHERE obj.type_desc = 'USER_TABLE' AND sch.name = 'data' ORDER BY sch.name, obj.name; This query still returns 110 tables. I won’t show them all here, but let’s have a look at the first few of them:  name 1data.Cluster_Keys 2data.Cluster_Machine_ClockSkew_UnstableSamples 3data.Cluster_Machine_Cluster_StableSamples 4data.Cluster_Machine_Keys 5data.Cluster_Machine_LogicalDisk_Capacity_StableSamples 6data.Cluster_Machine_LogicalDisk_Keys 7data.Cluster_Machine_LogicalDisk_Sightings 8data.Cluster_Machine_LogicalDisk_UnstableSamples 9data.Cluster_Machine_LogicalDisk_Volume_StableSamples 10data.Cluster_Machine_Memory_Capacity_StableSamples 11data.Cluster_Machine_Memory_UnstableSamples 12data.Cluster_Machine_Network_Capacity_StableSamples 13data.Cluster_Machine_Network_Keys 14data.Cluster_Machine_Network_Sightings 15data.Cluster_Machine_Network_UnstableSamples 16data.Cluster_Machine_OperatingSystem_StableSamples 17data.Cluster_Machine_Ping_UnstableSamples 18data.Cluster_Machine_Process_Instances 19data.Cluster_Machine_Process_Keys 20data.Cluster_Machine_Process_Owner_Instances 21data.Cluster_Machine_Process_Sightings 22data.Cluster_Machine_Process_UnstableSamples 23… There are two things I want to draw your attention to: The table names describe a hierarchy of the different types of object that are monitored by SQL Monitor (e.g. clusters, machines and disks). For each object type in the hierarchy, there are multiple tables, ending in the suffixes _Keys, _Sightings, _StableSamples and _UnstableSamples. Not every object type has a table for every suffix, but the _Keys suffix is especially important and a _Keys table does indeed exist for every object type. In fact, if we limit the query to return only those tables ending in _Keys, we reveal the full object hierarchy: SELECT sch.name + '.' + obj.name AS [name] FROM sys.objects obj JOIN sys.schemas sch ON sch.schema_id = obj.schema_id WHERE obj.type_desc = 'USER_TABLE' AND sch.name = 'data' AND obj.name LIKE '%_Keys' ORDER BY sch.name, obj.name;  name 1data.Cluster_Keys 2data.Cluster_Machine_Keys 3data.Cluster_Machine_LogicalDisk_Keys 4data.Cluster_Machine_Network_Keys 5data.Cluster_Machine_Process_Keys 6data.Cluster_Machine_Services_Keys 7data.Cluster_ResourceGroup_Keys 8data.Cluster_ResourceGroup_Resource_Keys 9data.Cluster_SqlServer_Agent_Job_History_Keys 10data.Cluster_SqlServer_Agent_Job_Keys 11data.Cluster_SqlServer_Database_BackupType_Backup_Keys 12data.Cluster_SqlServer_Database_BackupType_Keys 13data.Cluster_SqlServer_Database_CustomMetric_Keys 14data.Cluster_SqlServer_Database_File_Keys 15data.Cluster_SqlServer_Database_Keys 16data.Cluster_SqlServer_Database_Table_Index_Keys 17data.Cluster_SqlServer_Database_Table_Keys 18data.Cluster_SqlServer_Error_Keys 19data.Cluster_SqlServer_Keys 20data.Cluster_SqlServer_Services_Keys 21data.Cluster_SqlServer_SqlProcess_Keys 22data.Cluster_SqlServer_TopQueries_Keys 23data.Cluster_SqlServer_Trace_Keys 24data.Group_Keys The full object type hierarchy looks like this: Cluster Machine LogicalDisk Network Process Services ResourceGroup Resource SqlServer Agent Job History Database BackupType Backup CustomMetric File Table Index Error Services SqlProcess TopQueries Trace Group Okay, but what about the individual objects themselves represented at each level in this hierarchy? Well that’s what the _Keys tables are for. This is probably best illustrated by way of a simple example – how can I query my own data repository to find the databases on my own PC for which monitoring data has been collected? Like this: SELECT clstr._Name AS cluster_name, srvr._Name AS instance_name, db._Name AS database_name FROM data.Cluster_SqlServer_Database_Keys db JOIN data.Cluster_SqlServer_Keys srvr ON db.ParentId = srvr.Id -- Note here how the parent of a Database is a Server JOIN data.Cluster_Keys clstr ON srvr.ParentId = clstr.Id -- Note here how the parent of a Server is a Cluster WHERE clstr._Name = 'dev-chrisl2' -- This is the hostname of my own PC ORDER BY clstr._Name, srvr._Name, db._Name;  cluster_nameinstance_namedatabase_name 1dev-chrisl2SqlMonitorData 2dev-chrisl2master 3dev-chrisl2model 4dev-chrisl2msdb 5dev-chrisl2mssqlsystemresource 6dev-chrisl2tempdb 7dev-chrisl2sql2005SqlMonitorData 8dev-chrisl2sql2005TestDatabase 9dev-chrisl2sql2005master 10dev-chrisl2sql2005model 11dev-chrisl2sql2005msdb 12dev-chrisl2sql2005mssqlsystemresource 13dev-chrisl2sql2005tempdb 14dev-chrisl2sql2008SqlMonitorData 15dev-chrisl2sql2008master 16dev-chrisl2sql2008model 17dev-chrisl2sql2008msdb 18dev-chrisl2sql2008mssqlsystemresource 19dev-chrisl2sql2008tempdb These results show that I have three SQL Server instances on my machine (a default instance, one named sql2005 and one named sql2008), and each instance has the usual set of system databases, along with a database named SqlMonitorData. Basically, this is where I test SQL Monitor on different versions of SQL Server, when I’m developing. There are a few important things we can learn from this query: Each _Keys table has a column named Id. This is the primary key. Each _Keys table has a column named ParentId. A foreign key relationship is defined between each _Keys table and its parent _Keys table in the hierarchy. There are two exceptions to this, Cluster_Keys and Group_Keys, because clusters and groups live at the root level of the object hierarchy. Each _Keys table has a column named _Name. This is used to uniquely identify objects in the table within the scope of the same shared parent object. Actually, that last item isn’t always true. In some cases, the _Name column is actually called something else. For example, the data.Cluster_Machine_Services_Keys table has a column named _ServiceName instead of _Name (sorry for the inconsistency). In other cases, a name isn’t sufficient to uniquely identify an object. For example, right now my PC has multiple processes running, all sharing the same name, Chrome (one for each tab open in my web-browser). In such cases, multiple columns are used to uniquely identify an object within the scope of the same shared parent object. Well, that’s it for now. I’ve given you enough information for you to explore the _Keys tables to see how objects are stored in your own data repositories. In a future post, I’ll try to explain how monitoring data is stored for each object, using the _StableSamples and _UnstableSamples tables. If you have any questions about this post, or suggestions for future posts, just submit them in the comments section below.

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• SQL – Migrate Database from SQL Server to NuoDB – A Quick Tutorial

  - by Pinal Dave

  Data is growing exponentially and every organization with growing data is thinking of next big innovation in the world of Big Data. Big data is a indeed a future for every organization at one point of the time. Just like every other next big thing, big data has its own challenges and issues. The biggest challenge associated with the big data is to find the ideal platform which supports the scalability and growth of the data. If you are a regular reader of this blog, you must be familiar with NuoDB. I have been working with NuoDB for a while and their recent release is the best thus far. NuoDB is an elastically scalable SQL database that can run on local host, datacenter and cloud-based resources. A key feature of the product is that it does not require sharding (read more here). Last week, I was able to install NuoDB in less than 90 seconds and have explored their Explorer and Admin sections. You can read about my experiences in these posts: SQL – Step by Step Guide to Download and Install NuoDB – Getting Started with NuoDB SQL – Quick Start with Admin Sections of NuoDB – Manage NuoDB Database SQL – Quick Start with Explorer Sections of NuoDB – Query NuoDB Database Many SQL Authority readers have been following me in my journey to evaluate NuoDB. One of the frequently asked questions I’ve received from you is if there is any way to migrate data from SQL Server to NuoDB. The fact is that there is indeed a way to do so and NuoDB provides a fantastic tool which can help users to do it. NuoDB Migrator is a command line utility that supports the migration of Microsoft SQL Server, MySQL, Oracle, and PostgreSQL schemas and data to NuoDB. The migration to NuoDB is a three-step process: NuoDB Migrator generates a schema for a target NuoDB database It loads data into the target NuoDB database It dumps data from the source database Let’s see how we can migrate our data from SQL Server to NuoDB using a simple three-step approach. But before we do that we will create a sample database in MSSQL and later we will migrate the same database to NuoDB: Setup Step 1: Build a sample data CREATE DATABASE [Test]; CREATE TABLE [Department]( [DepartmentID] [smallint] NOT NULL, [Name] VARCHAR(100) NOT NULL, [GroupName] VARCHAR(100) NOT NULL, [ModifiedDate] [datetime] NOT NULL, CONSTRAINT [PK_Department_DepartmentID] PRIMARY KEY CLUSTERED ( [DepartmentID] ASC ) ) ON [PRIMARY]; INSERT INTO Department SELECT * FROM AdventureWorks2012.HumanResources.Department; Note that I am using the SQL Server AdventureWorks database to build this sample table but you can build this sample table any way you prefer. Setup Step 2: Install Java 64 bit Before you can begin the migration process to NuoDB, make sure you have 64-bit Java installed on your computer. This is due to the fact that the NuoDB Migrator tool is built in Java. You can download 64-bit Java for Windows, Mac OSX, or Linux from the following link: http://java.com/en/download/manual.jsp. One more thing to remember is that you make sure that the path in your environment settings is set to your JAVA_HOME directory or else the tool will not work. Here is how you can do it: Go to My Computer >> Right Click >> Select Properties >> Click on Advanced System Settings >> Click on Environment Variables >> Click on New and enter the following values. Variable Name: JAVA_HOME Variable Value: C:\Program Files\Java\jre7 Make sure you enter your Java installation directory in the Variable Value field. Setup Step 3: Install JDBC driver for SQL Server. There are two JDBC drivers available for SQL Server.  Select the one you prefer to use by following one of the two links below: Microsoft JDBC Driver jTDS JDBC Driver In this example we will be using jTDS JDBC driver. Once you download the driver, move the driver to your NuoDB installation folder. In my case, I have moved the JAR file of the driver into the C:\Program Files\NuoDB\tools\migrator\jar folder as this is my NuoDB installation directory. Now we are all set to start the three-step migration process from SQL Server to NuoDB: Migration Step 1: NuoDB Schema Generation Here is the command I use to generate a schema of my SQL Server Database in NuoDB. First I go to the folder C:\Program Files\NuoDB\tools\migrator\bin and execute the nuodb-migrator.bat file. Note that my database name is ‘test’. Additionally my username and password is also ‘test’. You can see that my SQL Server database is running on my localhost on port 1433. Additionally, the schema of the table is ‘dbo’. nuodb-migrator schema –source.driver=net.sourceforge.jtds.jdbc.Driver –source.url=jdbc:jtds:sqlserver://localhost:1433/ –source.username=test –source.password=test –source.catalog=test –source.schema=dbo –output.path=/tmp/schema.sql The above script will generate a schema of all my SQL Server tables and will put it in the folder C:\tmp\schema.sql . You can open the schema.sql file and execute this file directly in your NuoDB instance. You can follow the link here to see how you can execute the SQL script in NuoDB. Please note that if you have not yet created the schema in the NuoDB database, you should create it before executing this step. Step 2: Generate the Dump File of the Data Once you have recreated your schema in NuoDB from SQL Server, the next step is very easy. Here we create a CSV format dump file, which will contain all the data from all the tables from the SQL Server database. The command to do so is very similar to the above command. Be aware that this step may take a bit of time based on your database size. nuodb-migrator dump –source.driver=net.sourceforge.jtds.jdbc.Driver –source.url=jdbc:jtds:sqlserver://localhost:1433/ –source.username=test –source.password=test –source.catalog=test –source.schema=dbo –output.type=csv –output.path=/tmp/dump.cat Once the above command is successfully executed you can find your CSV file in the C:\tmp\ folder. However, you do not have to do anything manually. The third and final step will take care of completing the migration process. Migration Step 3: Load the Data into NuoDB After building schema and taking a dump of the data, the very next step is essential and crucial. It will take the CSV file and load it into the NuoDB database. nuodb-migrator load –target.url=jdbc:com.nuodb://localhost:48004/mytest –target.schema=dbo –target.username=test –target.password=test –input.path=/tmp/dump.cat Please note that in the above script we are now targeting the NuoDB database, which we have already created with the name of “MyTest”. If the database does not exist, create it manually before executing the above script. I have kept the username and password as “test”, but please make sure that you create a more secure password for your database for security reasons. Voila!  You’re Done That’s it. You are done. It took 3 setup and 3 migration steps to migrate your SQL Server database to NuoDB.  You can now start exploring the database and build excellent, scale-out applications. In this blog post, I have done my best to come up with simple and easy process, which you can follow to migrate your app from SQL Server to NuoDB. Download NuoDB I strongly encourage you to download NuoDB and go through my 3-step migration tutorial from SQL Server to NuoDB. Additionally here are two very important blog post from NuoDB CTO Seth Proctor. He has written excellent blog posts on the concept of the Administrative Domains. NuoDB has this concept of an Administrative Domain, which is a collection of hosts that can run one or multiple databases.  Each database has its own TEs and SMs, but all are managed within the Admin Console for that particular domain. http://www.nuodb.com/techblog/2013/03/11/getting-started-provisioning-a-domain/ http://www.nuodb.com/techblog/2013/03/14/getting-started-running-a-database/ 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, Technology Tagged: NuoDB

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• Ameristar Wins with Oracle GoldenGate’s Heterogeneous Real-Time Data Integration

  - by Irem Radzik

  Today we announced a press release about another successful project with Oracle GoldenGate. This time at Ameristar. Ameristar is a casino gaming company and needed a single data integration solution to connect multiple heterogeneous systems to its Teradata data warehouse. The project involves integration of Ameristar’s promotional and gaming data from 14 data sources across its 7 casino hotel properties in real time into a central Teradata data warehouse. The source systems include the Aristocrat gaming and MGT promotional management platforms running on Microsoft SQL Server 2000 databases. As you can notice, there was no Oracle Database involved in this project, but Ameristar’s IT leadership knew that  GoldenGate’s strong heterogeneous and real-time data integration capabilities is the right technology for their data warehousing project. With GoldenGate Ameristar was able to reduce data latency to the enterprise data warehouse, and use this real-time customer information for marketing teams in improving overall customer experience. Ameristar customers receive more targeted and timely campaign offers, and the company has more up-to-date visibility into financial metrics of the company. One other key benefit the company experienced with GoldenGate is in operational costs. The previous data capture solution Ameristar used was trigger based and required a lot of effort to manage. They needed dedicated IT staff to maintain it. With GoldenGate, the solution runs seamlessly without needing a fully-dedicated staff, giving the IT team at Ameristar more resources for their other IT projects. If you want to learn more about GoldenGate and the latest features for Oracle Database and non-Oracle databases, please watch our on demand webcast about Oracle GoldenGate 11g Release 2.

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• My Take on Hadoop World 2011

  - by Jean-Pierre Dijcks

  I’m sure some of you have read pieces about Hadoop World and I did see some headlines which were somewhat, shall we say, interesting? I thought the keynote by Larry Feinsmith of JP Morgan Chase & Co was one of the highlights of the conference for me. The reason was very simple, he addressed some real use cases outside of internet and ad platforms. The following are my notes, since the keynote was recorded I presume you can go and look at Hadoopworld.com at some point… On the use cases that were mentioned: ETL – how can I do complex data transformation at scale Doing Basel III liquidity analysis Private banking – transaction filtering to feed [relational] data marts Common Data Platform – a place to keep data that is (or will be) valuable some day, to someone, somewhere 360 Degree view of customers – become pro-active and look at events across lines of business. For example make sure the mortgage folks know about direct deposits being stopped into an account and ensure the bank is pro-active to service the customer Treasury and Security – Global Payment Hub [I think this is really consolidation of data to cross reference activity across business and geographies] Data Mining Bypass data engineering [I interpret this as running a lot of a large data set rather than on samples] Fraud prevention – work on event triggers, say a number of failed log-ins to the website. When they occur grab web logs, firewall logs and rules and start to figure out who is trying to log in. Is this me, who forget his password, or is it someone in some other country trying to guess passwords Trade quality analysis – do a batch analysis or all trades done and run them through an analysis or comparison pipeline One of the key requests – if you can say it like that – was for vendors and entrepreneurs to make sure that new tools work with existing tools. JPMC has a large footprint of BI Tools and Big Data reporting and tools should work with those tools, rather than be separate. Security and Entitlement – how to protect data within a large cluster from unwanted snooping was another topic that came up. I thought his Elephant ears graph was interesting (couldn’t actually read the points on it, but the concept certainly made some sense) and it was interesting – when asked to show hands – how the audience did not (!) think that RDBMS and Hadoop technology would overlap completely within a few years. Another interesting session was the session from Disney discussing how Disney is building a DaaS (Data as a Service) platform and how Hadoop processing capabilities are mixed with Database technologies. I thought this one of the best sessions I have seen in a long time. It discussed real use case, where problems existed, how they were solved and how Disney planned some of it. The planning focused on three things/phases: Determine the Strategy – Design a platform and evangelize this within the organization Focus on the people – Hire key people, grow and train the staff (and do not overload what you have with new things on top of their day-to-day job), leverage a partner with experience Work on Execution of the strategy – Implement the platform Hadoop next to the other technologies and work toward the DaaS platform This kind of fitted with some of the Linked-In comments, best summarized in “Think Platform – Think Hadoop”. In other words [my interpretation], step back and engineer a platform (like DaaS in the Disney example), then layer the rest of the solutions on top of this platform. One general observation, I got the impression that we have knowledge gaps left and right. On the one hand are people looking for more information and details on the Hadoop tools and languages. On the other I got the impression that the capabilities of today’s relational databases are underestimated. Mostly in terms of data volumes and parallel processing capabilities or things like commodity hardware scale-out models. All in all I liked this conference, it was great to chat with a wide range of people on Oracle big data, on big data, on use cases and all sorts of other stuff. Just hope they get a set of bigger rooms next time… and yes, I hope I’m going to be back next year!

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• Sort Data in Windows Phone using Collection View Source

  - by psheriff

  When you write a Windows Phone application you will most likely consume data from a web service somewhere. If that service returns data to you in a sort order that you do not want, you have an easy alternative to sort the data without writing any C# or VB code. You use the built-in CollectionViewSource object in XAML to perform the sorting for you. This assumes that you can get the data into a collection that implements the IEnumerable or IList interfaces.For this example, I will be using a simple Product class with two properties, and a list of Product objects using the Generic List class. Try this out by creating a Product class as shown in the following code:public class Product {  public Product(int id, string name)   {    ProductId = id;    ProductName = name;  }  public int ProductId { get; set; }  public string ProductName { get; set; }}Create a collection class that initializes a property called DataCollection with some sample data as shown in the code below:public class Products : List<Product>{  public Products()  {    InitCollection();  }  public List<Product> DataCollection { get; set; }  List<Product> InitCollection()  {    DataCollection = new List<Product>();    DataCollection.Add(new Product(3,        "PDSA .NET Productivity Framework"));    DataCollection.Add(new Product(1,        "Haystack Code Generator for .NET"));    DataCollection.Add(new Product(2,        "Fundamentals of .NET eBook"));    return DataCollection;  }}Notice that the data added to the collection is not in any particular order. Create a Windows Phone page and add two XML namespaces to the Page.xmlns:scm="clr-namespace:System.ComponentModel;assembly=System.Windows"xmlns:local="clr-namespace:WPSortData"The 'local' namespace is an alias to the name of the project that you created (in this case WPSortData). The 'scm' namespace references the System.Windows.dll and is needed for the SortDescription class that you will use for sorting the data. Create a phone:PhoneApplicationPage.Resources section in your Windows Phone page that looks like the following:<phone:PhoneApplicationPage.Resources>  <local:Products x:Key="products" />  <CollectionViewSource x:Key="prodCollection"      Source="{Binding Source={StaticResource products},                       Path=DataCollection}">    <CollectionViewSource.SortDescriptions>      <scm:SortDescription PropertyName="ProductName"                           Direction="Ascending" />    </CollectionViewSource.SortDescriptions>  </CollectionViewSource></phone:PhoneApplicationPage.Resources>The first line of code in the resources section creates an instance of your Products class. The constructor of the Products class calls the InitCollection method which creates three Product objects and adds them to the DataCollection property of the Products class. Once the Products object is instantiated you now add a CollectionViewSource object in XAML using the Products object as the source of the data to this collection. A CollectionViewSource has a SortDescriptions collection that allows you to specify a set of SortDescription objects. Each object can set a PropertyName and a Direction property. As you see in the above code you set the PropertyName equal to the ProductName property of the Product object and tell it to sort in an Ascending direction.All you have to do now is to create a ListBox control and set its ItemsSource property to the CollectionViewSource object. The ListBox displays the data in sorted order by ProductName and you did not have to write any LINQ queries or write other code to sort the data!<ListBox    ItemsSource="{Binding Source={StaticResource prodCollection}}"   DisplayMemberPath="ProductName" />SummaryIn this blog post you learned that you can sort any data without having to change the source code of where the data comes from. Simply feed the data into a CollectionViewSource in XAML and set some sort descriptions in XAML and the rest is done for you! This comes in very handy when you are consuming data from a source where the data is given to you and you do not have control over the sorting.NOTE: You can download this article and many samples like the one shown in this blog entry at my website. http://www.pdsa.com/downloads. Select “Tips and Tricks”, then “Sort Data in Windows Phone using Collection View Source” from the drop down list.Good Luck with your Coding,Paul Sheriff** SPECIAL OFFER FOR MY BLOG READERS **We frequently offer a FREE gift for readers of my blog. Visit http://www.pdsa.com/Event/Blog for your FREE gift!

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• Connect to QuickBooks from PowerBuilder using RSSBus ADO.NET Data Provider

  - by dataintegration

  The RSSBus ADO.NET providers are easy-to-use, standards based controls that can be used from any platform or development technology that supports Microsoft .NET, including Sybase PowerBuilder. In this article we show how to use the RSSBus ADO.NET Provider for QuickBooks in PowerBuilder. A similar approach can be used from PowerBuilder with other RSSBus ADO.NET Data Providers to access data from Salesforce, SharePoint, Dynamics CRM, Google, OData, etc. In this article we will show how to create a basic PowerBuilder application that performs CRUD operations using the RSSBus ADO.NET Provider for QuickBooks. Step 1: Open PowerBuilder and create a new WPF Window Application solution. Step 2: Add all the Visual Controls needed for the connection properties. Step 3: Add the DataGrid control from the .NET controls. Step 4:Configure the columns of the DataGrid control as shown below. The column bindings will depend on the table. <DataGrid AutoGenerateColumns="False" Margin="13,249,12,14" Name="datagrid1" TabIndex="70" ItemsSource="{Binding}"> <DataGrid.Columns> <DataGridTextColumn x:Name="idColumn" Binding="{Binding Path=ID}" Header="ID" Width="SizeToHeader" /> <DataGridTextColumn x:Name="nameColumn" Binding="{Binding Path=Name}" Header="Name" Width="SizeToHeader" /> ... </DataGrid.Columns> </DataGrid> Step 5:Add a reference to the RSSBus ADO.NET Provider for QuickBooks assembly. Step 6:Optional: Set the QBXML Version to 6. Some of the tables in QuickBooks require a later version of QuickBooks to support updates and deletes. Please check the help for details. Connect the DataGrid: Once the visual elements have been configured, developers can use standard ADO.NET objects like Connection, Command, and DataAdapter to populate a DataTable with the results of a SQL query: System.Data.RSSBus.QuickBooks.QuickBooksConnection conn conn = create System.Data.RSSBus.QuickBooks.QuickBooksConnection(connectionString) System.Data.RSSBus.QuickBooks.QuickBooksCommand comm comm = create System.Data.RSSBus.QuickBooks.QuickBooksCommand(command, conn) System.Data.DataTable table table = create System.Data.DataTable System.Data.RSSBus.QuickBooks.QuickBooksDataAdapter dataAdapter dataAdapter = create System.Data.RSSBus.QuickBooks.QuickBooksDataAdapter(comm) dataAdapter.Fill(table) datagrid1.ItemsSource=table.DefaultView The code above can be used to bind data from any query (set this in command), to the DataGrid. The DataGrid should have the same columns as those returned from the SELECT statement. PowerBuilder Sample Project The included sample project includes the steps outlined in this article. You will also need the QuickBooks ADO.NET Data Provider to make the connection. You can download a free trial here.

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• EBS Seed Data Comparison Reports Now Available

  - by Steven Chan (Oracle Development)

  Earlier this year we released a reporting tool that reports on the differences in E-Business Suite database objects between one release and another.  That's a very useful reference, but EBS defaults are delivered as seed data within the database objects themselves. What about the differences in this seed data between one release and another? I'm pleased to announce the availability of a new tool that provides comparison reports of E-Business Suite seed data between EBS 11.5.10.2, 12.0.4, 12.0.6, 12.1.1, and 12.1.3.  This new tool complements the information in the data model comparison tool.  You can download the new seed data comparison tool here: EBS ATG Seed Data Comparison Report (Note 1327399.1) The EBS ATG Seed Data Comparison Report provides report on the changes between different EBS releases based upon the seed data changes delivered by the product data loader files (.ldt extension) based on EBS ATG loader control (.lct extension) files.  You can use this new tool to report on the differences in the following types of seed data: Concurrent Program definitions Descriptive Flexfield entity definitions Application Object Library profile option definitions Application Object Library (AOL) key flexfield, function, lookups, value set definitions Application Object Library (AOL) menu and responsibility definitions Application Object Library messages Application Object Library request set definitions Application Object Library printer styles definitions Report Manager / WebADI component and integrator entity definitions Business Intelligence Publisher (BI Publisher) entity definitions BIS Request Set Generator entity definitions ... and more Your feedback is welcomeThis new tool was produced by our hard-working EBS Release Management team, and they're actively seeking your feedback.  Please feel free to share your experiences with it by posting a comment here.  You can also request enhancements to this tool via the distribution list address included in Note 1327399.1.Related Articles Oracle E-Business Suite Release 12.1.3 Now Available New Whitepaper: Upgrading EBS 11i Forms + OA Framework Personalizations to EBS 12 EBS 12.0 Minimum Requirements for Extended Support Finalized Five Key Resources for Upgrading to E-Business Suite Release 12 E-Business Suite Release 12.1.1 Consolidated Upgrade Patch 1 Now Available New Whitepaper: Planning Your E-Business Suite Upgrade from Release 11i to 12.1

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• How long for data highlighter mark up to appear in structured data tool?

  - by Max

  I used the data highlighter in webmaster tools over 3 weeks ago to mark up some local business data, but there is still no structured data being detected in webmaster tools. Does any body have any experience on approx how long it takes for Google Webmaster Tools to start reporting Structured Data that has been marked up with their data highlighter? I'm asking specifically about reporting on it in Web Master Tools Structured Data section, as opposed to actually appearing in the SERPs.

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• PASS Business Intelligence Virtual Chapter Upcoming Sessions (November 2013)

  - by Sergio Govoni

  Let me point out the upcoming live events, dedicated to Business Intelligence with SQL Server, that PASS Business Intelligence Virtual Chapter has scheduled for November 2013. The "Accidental Business Intelligence Project Manager"Date: Thursday 7th November - 8:00 PM GMT / 3:00 PM EST / Noon PSTSpeaker: Jen StirrupURL: https://attendee.gotowebinar.com/register/5018337449405969666 You've watched the Apprentice with Donald Trump and Lord Alan Sugar. You know that the Project Manager is usually the one gets firedYou've heard that Business Intelligence projects are prone to failureYou know that a quick Bing search for "why do Business Intelligence projects fail?" produces a search result of 25 million hits!Despite all this… you're now Business Intelligence Project Manager – now what do you do?In this session, Jen will provide a "sparks from the anvil" series of steps and working practices in Business Intelligence Project Management. What about waterfall vs agile? What is a Gantt chart anyway? Is Microsoft Project your friend or a problematic aspect of being a BI PM? Jen will give you some ideas and insights that will help you set your BI project right: assess priorities, avoid conflict, empower the BI team and generally deliver the Business Intelligence project successfully! Dimensional Modelling Design Patterns: Beyond BasicsDate: Tuesday 12th November - Noon AEDT / 1:00 AM GMT / Monday 11th November 5:00 PM PSTSpeaker: Jason Horner, Josh Fennessy and friendsURL: https://attendee.gotowebinar.com/register/852881628115426561 This session will provide a deeper dive into the art of dimensional modeling. We will look at the different types of fact tables and dimension tables, how and when to use them. We will also some approaches to creating rich hierarchies that make reporting a snap. This session promises to be very interactive and engaging, bring your toughest Dimensional Modeling quandaries. Data Vault Data Warehouse ArchitectureDate: Tuesday 19th November - 4:00 PM PST / 7 PM EST / Wednesday 20th November 11:00 PM AEDTSpeaker: Jeff Renz and Leslie WeedURL: https://attendee.gotowebinar.com/register/1571569707028142849 Data vault is a compelling architecture for an enterprise data warehouse using SQL Server 2012. A well designed data vault data warehouse facilitates fast, efficient and maintainable data integration across business systems. In this session Leslie and I will review the basics about enterprise data warehouse design, introduce you to the data vault architecture and discuss how you can leverage new features of SQL Server 2012 help make your data warehouse solution provide maximum value to your users. 

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• MapRedux - PowerShell and Big Data

  - by Dittenhafer Solutions

  MapRedux – #PowerShell and #Big Data Have you been hearing about “big data”, “map reduce” and other large scale computing terms over the past couple of years and been curious to dig into more detail? Have you read some of the Apache Hadoop online documentation and unfortunately concluded that it wasn't feasible to setup a “test” hadoop environment on your machine? More recently, I have read about some of Microsoft’s work to enable Hadoop on the Azure cloud. Being a "Microsoft"-leaning technologist, I am more inclinded to be successful with experimentation when on the Windows platform. Of course, it is not that I am "religious" about one set of technologies other another, but rather more experienced. Anyway, within the past couple of weeks I have been thinking about PowerShell a bit more as the 2012 PowerShell Scripting Games approach and it occured to me that PowerShell's support for Windows Remote Management (WinRM), and some other inherent features of PowerShell might lend themselves particularly well to a simple implementation of the MapReduce framework. I fired up my PowerShell ISE and started writing just to see where it would take me. Quite simply, the ScriptBlock feature combined with the ability of Invoke-Command to create remote jobs on networked servers provides much of the plumbing of a distributed computing environment. There are some limiting factors of course. Microsoft provided some default settings which prevent PowerShell from taking over a network without administrative approval first. But even with just one adjustment, a given Windows-based machine can become a node in a MapReduce-style distributed computing environment. Ok, so enough introduction. Let's talk about the code. First, any machine that will participate as a remote "node" will need WinRM enabled for remote access, as shown below. This is not exactly practical for hundreds of intended nodes, but for one (or five) machines in a test environment it does just fine. C:> winrm quickconfig WinRM is not set up to receive requests on this machine. The following changes must be made: Set the WinRM service type to auto start. Start the WinRM service. Make these changes [y/n]? y Alternatively, you could take the approach described in the Remotely enable PSRemoting post from the TechNet forum and use PowerShell to create remote scheduled tasks that will call Enable-PSRemoting on each intended node. Invoke-MapRedux Moving on, now that you have one or more remote "nodes" enabled, you can consider the actual Map and Reduce algorithms. Consider the following snippet: $MyMrResults = Invoke-MapRedux -MapReduceItem $Mr -ComputerName $MyNodes -DataSet $dataset -Verbose Invoke-MapRedux takes an instance of a MapReduceItem which references the Map and Reduce scriptblocks, an array of computer names which are the remote nodes, and the initial data set to be processed. As simple as that, you can start working with concepts of big data and the MapReduce paradigm. Now, how did we get there? I have published the initial version of my PsMapRedux PowerShell Module on GitHub. The PsMapRedux module provides the Invoke-MapRedux function described above. Feel free to browse the underlying code and even contribute to the project! In a later post, I plan to show some of the inner workings of the module, but for now let's move on to how the Map and Reduce functions are defined. Map Both the Map and Reduce functions need to follow a prescribed prototype. The prototype for a Map function in the MapRedux module is as follows. A simple scriptblock that takes one PsObject parameter and returns a hashtable. It is important to note that the PsObject $dataset parameter is a MapRedux custom object that has a "Data" property which offers an array of data to be processed by the Map function. $aMap = { Param ( [PsObject] $dataset ) # Indicate the job is running on the remote node. Write-Host ($env:computername + "::Map"); # The hashtable to return $list = @{}; # ... Perform the mapping work and prepare the $list hashtable result with your custom PSObject... # ... The $dataset has a single 'Data' property which contains an array of data rows # which is a subset of the originally submitted data set. # Return the hashtable (Key, PSObject) Write-Output $list; } Reduce Likewise, with the Reduce function a simple prototype must be followed which takes a $key and a result $dataset from the MapRedux's partitioning function (which joins the Map results by key). Again, the $dataset is a MapRedux custom object that has a "Data" property as described in the Map section. $aReduce = { Param ( [object] $key, [PSObject] $dataset ) Write-Host ($env:computername + "::Reduce - Count: " + $dataset.Data.Count) # The hashtable to return $redux = @{}; # Return Write-Output $redux; } All Together Now When everything is put together in a short example script, you implement your Map and Reduce functions, query for some starting data, build the MapReduxItem via New-MapReduxItem and call Invoke-MapRedux to get the process started: # Import the MapRedux and SQL Server providers Import-Module "MapRedux" Import-Module “sqlps” -DisableNameChecking # Query the database for a dataset Set-Location SQLSERVER:\sql\dbserver1\default\databases\myDb $query = "SELECT MyKey, Date, Value1 FROM BigData ORDER BY MyKey"; Write-Host "Query: $query" $dataset = Invoke-SqlCmd -query $query # Build the Map function $MyMap = { Param ( [PsObject] $dataset ) Write-Host ($env:computername + "::Map"); $list = @{}; foreach($row in $dataset.Data) { # Write-Host ("Key: " + $row.MyKey.ToString()); if($list.ContainsKey($row.MyKey) -eq $true) { $s = $list.Item($row.MyKey); $s.Sum += $row.Value1; $s.Count++; } else { $s = New-Object PSObject; $s | Add-Member -Type NoteProperty -Name MyKey -Value $row.MyKey; $s | Add-Member -type NoteProperty -Name Sum -Value $row.Value1; $list.Add($row.MyKey, $s); } } Write-Output $list; } $MyReduce = { Param ( [object] $key, [PSObject] $dataset ) Write-Host ($env:computername + "::Reduce - Count: " + $dataset.Data.Count) $redux = @{}; $count = 0; foreach($s in $dataset.Data) { $sum += $s.Sum; $count += 1; } # Reduce $redux.Add($s.MyKey, $sum / $count); # Return Write-Output $redux; } # Create the item data $Mr = New-MapReduxItem "My Test MapReduce Job" $MyMap $MyReduce # Array of processing nodes... $MyNodes = ("node1", "node2", "node3", "node4", "localhost") # Run the Map Reduce routine... $MyMrResults = Invoke-MapRedux -MapReduceItem $Mr -ComputerName $MyNodes -DataSet $dataset -Verbose # Show the results Set-Location C:\ $MyMrResults | Out-GridView Conclusion I hope you have seen through this article that PowerShell has a significant infrastructure available for distributed computing. While it does take some code to expose a MapReduce-style framework, much of the work is already done and PowerShell could prove to be the the easiest platform to develop and run big data jobs in your corporate data center, potentially in the Azure cloud, or certainly as an academic excerise at home or school. Follow me on Twitter to stay up to date on the continuing progress of my Powershell MapRedux module, and thanks for reading! Daniel

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• EMEA Analytics & Data Integration Oracle Partner Forum

  - by Mike.Hallett(at)Oracle-BI&EPM

  MONDAY 12TH NOVEMBER, 2012 IN LONDON (UK) For Oracle Partners across Europe, Middle East and Africa: come to hear the latest news from Oracle OpenWorld about Oracle BI & Data Integration, and propel your business growth as an Oracle partner. This event should appeal to BI or Data Integration specialised partners, Executives, Sales, Pre-sales and Solution architects: with a choice of participation in the plenary day and then a set of special interest (technical) sessions. The follow on breakout sessions from the 13th November provide deeper dives and technical training for those of you who wish to stay for more detailed and hands-on workshops. Keynote: Andrew Sutherland, SVP Oracle Technology Hot agenda items will include: The Fusion Middleware Stack: Engineered to work together A complete Analytics and Data Integration Solution Architecture: Big Data and Little Data combined In-Memory Analytics for Extreme Insight Latest Product Development Roadmap for Data Integration and Analytics Venue:  Oracles London CITY Moorgate Offices Places are limited, Register from this Link {see Register button at bottom right of page}. Note: Registration for the conference and the deeper dives and technical training is free of charge to OPN member Partners, but you will be responsible for your own travel and hotel expenses. Event Schedule During this event you can learn about partner success stories, participate in an array of break-out sessions, exchange information with other partners and enjoy a vibrant panel discussion. Nov. 12th  : Day 1 Main Plenary Session : Full day, starting 10.30 am.     Oracle Hosted Dinner in the Evening Nov. 13th  onwards Architecture Masterclass : IM Reference Architecture – Big Data and Little Data combined (1 day) BI-Apps Bootcamp  (4-days) Oracle GoldenGate workshop (1 day) Oracle Data Integrator and Oracle Enterprise Data Quality workshop (1 day)   For further information and detail download the Agenda (pdf) or contact Michael Hallett at [email protected].

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• Swiss Re increases data warehouse performance and deploys in record time

  - by KLaker

  Great information on yet another data warehouse deployment on Exadata. A little background on Swiss Re: In 2002, Swiss Re established a data warehouse for its client markets and products to gather reinsurance information across all organizational units into an integrated structure. The data warehouse provided the basis for reporting at the group level with drill-down capability to individual contracts, while facilitating application integration and data exchange by using common data standards. Initially focusing on property and casualty reinsurance information only, it now includes life and health reinsurance, insurance, and nonlife insurance information. Key highlights of the benefits that Swiss Re achieved by using Exadata: Reduced the time to feed the data warehouse and generate data marts by 58% Reduced average runtime by 24% for standard reports comfortably loading two data warehouse refreshes per day with incremental feeds Freed up technical experts by significantly minimizing time spent on tuning activities Most importantly this was one of the fastest project deployments in Swiss Re's history. They went from installation to production in just four months! What is truly surprising is the that it only took two weeks between power-on to testing the machine with full data volumes! Business teams at Swiss Re are now able to fully exploit up-to-date analytics across property, casualty, life, health insurance, and reinsurance lines to identify successful products. These points are highlighted in the following quotes from Dr. Stephan Gutzwiller, Head of Data Warehouse Services at Swiss Re:  "We were operating a complete Oracle stack, including servers, storage area network, operating systems, and databases that was well optimized and delivered very good performance over an extended period of time. When a hardware replacement was scheduled for 2012, Oracle Exadata was a natural choice—and the performance increase was impressive. It enabled us to deliver analytics to our internal customers faster, without hiring more IT staff" “The high quality data that is readily available with Oracle Exadata gives us the insight and agility we need to cater to client needs. We also can continue re-engineering to keep up with the increasing demand without having to grow the organization. This combination creates excellent business value.” Our full press release is available here: http://www.oracle.com/us/corporate/customers/customersearch/swiss-re-1-exadata-ss-2050409.html. If you want more information about how Exadata can increase the performance of your data warehouse visit our home page: http://www.oracle.com/us/products/database/exadata-database-machine/overview/index.html

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• Does using structure data semantic LocalBusiness schema markup work for local EMD URL's?

  - by ElHaix

  Based on what I have read about Google's recent Panda and Penguin updates, I'm getting the impression that using semantic markup may help improve SEO results. On a EMD (exact match domain) site, that may have been hit, we list location-based products. We are now going to be adding a itemtype="http://schema.org/Product" to each product, with relevant details. However, that product may be available in Los Angeles and also in appear in a Seattle results page. We could add a LocalBusiness item type on each geo page to define the geo location for that page. While the definition states: A particular physical business or branch of an organization. Examples of LocalBusiness include a restaurant, a particular branch of a restaurant chain, a branch of a bank, a medical practice, a club, a bowling alley, etc. We could add use the location property which would simply include the city/state details. I realize that this looks like it is meant for a physical location, however could this be done without seeming black-hat?

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• How to recover data from NTFS partition that was made into a Swap partition?

  - by Raghav Mehta

  I have extremely important stuff on my windows partition which during the ubuntu 10.10 installation,when it said that I should create something called swap space, I selected it to be a swap space (without even knowing what it actually meant) The Grub2 doesn't show up so I don't get a choice to boot Ubuntu or Windows. I don't get my windows partition as a removable device in Ubuntu either. When I go to disk utility and select the sda2 (i.e.. my windows partition) and click edit partition and select HPFS/NTFS for the type and tick bootable and click OK the small processing sign keep on rotating on the bottom right of the sda2 in the chart and after about 10 to 15 minutes it gives an unknown error and thus, I am still unable to use my windows. I am even worse than a beginner who doesn't know a thing about Ubuntu so please be patient and help me out.

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