Mobile BI is clearly on our door-steps, with many organizations starting to integrate a level of Mobile Business Intelligence into their reporting and analytics road-maps, although the uptake has not been as strong as one might expect, this is mainly because of the following reasons:

• The landscape of the Mobile BI reporting suites is still very new with only a few names out there that offer such solutions
• Integrating a level of Mobile BI into your report offering could mean an increased level of complexity in terms of data preparation.
• Due to a low number of providers, Mobile BI tends to be more expensive than what one might expect, which could increase the risks of a project revolving around such a system, causing managers to be deterred away from taking the first step, even if that steps allows for a competitive edge.

But this is all about to change, Mobile BI is becoming as easy as installing an App on your Tablet.
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An essential part of creating a Sentiment Analysis algorithm (or any Data Mining algorithm for that matter) is to have a comprehensive dataset or corpus to learn from, as well as a test dataset to ensure that the accuracy of your algorithm meets the standards you expect. This will also allow you to tweak your algorithm and deduce better (or more precise) features of natural language that you could extract from the text that contribute towards stronger sentiment classification, rather than using a generic “word bag” approach.

This post will contain a corpus of already classified tweets in terms of sentiment, this Twitter sentiment dataset is by no means diverse and should not be used in a final product for sentiment analysis, at least not without diluting the dataset with a much more diverse one.

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A very common requirement when administering an SSAS instance or cube is killing a particular connection, SPID or Session, this could be due to a lengthy operation exceeding the expected time to completing, or merely cancelling a transaction that was issued by mistake, hopefully that wont be a schema change on a live environment tho!.

This post goes through the XMLA required for killing an SSAS command, as well as the Analysis Service DMVs that can be utilized to identify the required IDs.

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Recently I’ve been getting the following error message while trying to create an SSIS 2012 step in SQL Server Job Agent, and setting the Parameters or Connection Strings for that step:

The property ‘ParameterName’ contains invalid characters as an object name. Remove the invalid characters. (Microsoft.SqlServer.Management.IntegrationServices)

This error emerges after confirming the newly created step (which will run the SSIS package) in SQL Server Job Agent, and after setting the parameter.

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For some strange reason I can’t seem to find a lot of literature online about the basic behavior of the LastNonEmpty SSAS function, which is currently only available in an Enterprise Edition of Analysis Service (for some really strange reason, since you can emulate the behavior in other SSAS versions relatively painlessly), so here is a nice wee post that goes through the syntax of the LastNonEmpty function, how to override and customize it’s default behavior, what performance improvement techniques you can apply, and some of the quirks you might experience when playing around with the LastNonEmpty Analysis Service function.

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The SSIS 2012 Catalog integration with SQL Server comes with the advantage of being able to execute SSIS packages indigenously from within T-SQL, along with a host of other functionality including improved monitoring and logging, integrated security and obviously the new deployment model.

Executing SSIS packages by calling a stored procedure can be handy in many situations, but also comes with some (albeit minor) stipulations and quirks, this post tries to go through some of the basics of executing SSIS packages through stored procedures, while also touching lightly on some of the issues I encountered while having a go at this new SSIS execution method.

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Although the new SSIS 2012 Project Deployment Model is pretty cool, it is a completely new deployment architecture that is bound exhibit some bugs. To be honest SSIS 2012 in general seems to be less geared up towards enterprise level scale-out, and will work better in a non-24/7 load environment.

The error I am experiencing with SSIS 2012 is to do with deploying a project (from SQL Server Data Tools) to an SSIS Catalog DB, whenever a project is deployed, there seems to be a 50/50 chance that I will receive the following deployment error:

Failed to deploy project. For more information, query the operation_messages view for the operation identifier ’123456′. (Microsoft SQL Server, Error: 27203)

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If you have used Microsoft development products long enough, then you must be familiar with the error reporting nightmares some of their products exhibit, the classic “please check the error log for more details” message, even though you are in the error log, is not just frustrating, but in my opinion is a bug that shouldn’t even reach end consumer, especially when you are handing the developers a framework for them to build on and extend.

Microsoft’s SSIS and SSRS have always been shortchanged when it comes to error logging; whether they are run-time errors on the server, or even while trying to debug a package or a report in a development environment, there is no lack of confusing error messages that send you down hours of so many long winded paths that leaves you tugging on strings hoping something might eventually make sense.

Today I will go through one of SSIS 2012 new quirks, the SSIS Canceled Status (or error), and what could be the reasons that you might receive such an error.

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Ok, this might be abit of a general question, as am sure anyone who found themselves in this blog knows a thing or two about BI, but in this post I will try to give a more holistic overview of what is a full Business Intelligence offering, and what dimensions constitutes a full analytical offering. Additionally, having a BI infrastructure is all well and good, but at the end of the day, the over-all goal of any BI platform is to identify and act upon the data as quickly as possible, when the data is most useful for strategic, tactical or operational business decisions, a concept that we will try and explore in this article.

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The new Office 365 ProPlus is different and very exciting, there is a host of new features that makes this release really stand-out, for example installing this new Office suite will only take 5 seconds, after which you are able to run it and interact with it while it is still finalizing the installation in the background. This is very cool and a change from the usual 1 hour installation process.

What makes Excel 13 really exciting for me is the introduction of the new Power View visualization and data exploration layer baked into this new release. This is what I will be covering throughout this post

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