Microsoft SharePoint has taken the enterprise by storm. A staggering number of corporations today are using SharePoint as their collaborative and information backbone. A tremendous amount of information is being stored within SharePoint lists.
As such, it’s becoming more and more important to be able to quickly and easily extract the data in those lists and bring it into other platforms for analysis, reporting and storage. SQL Server Integration Services seems like the ideal tool for moving and transforming this type of data around, but accessing data in SharePoint lists is not a trivial task.
Unless of course you have Task Factory. Task Factory is a suite of SSIS components from Pragmatic Works. In this video, we’ll look at the SharePoint Source component.
For any ETL developer, updating dimensional data is the heart of what you do. Using out of the box SSIS components, however, is an unattractive proposition. You either had to use the built in SCD wizard, or use the "roll your own" approach. As any veteran BI developer knows, the SCD wizard isn’t the best in the world, primarily due to it’s reliance on the OLEDB Command task. "Roll your own", in other words handling all the logic yourself, works, but is time consuming to develop and often confusing to maintain.
A far, far better solution for handling Kimball SCD is to use the Task Factory SSIS Dimension Merge Slowly Changing Dimension transform. While it’s name is rather long winded, it’s definitely worth the breath.
In this video we’ll take a look at the Dimension Merge Slowly Changing Dimension in action.
Task Factory is a suite of SSIS components available from Pragmatic Works. In this video we’ll look at the Update Batch Transform.
Updating data can be a real pain. You either have to setup a special staging table in your database, then update from it, or use the slow OLEDB command. In this video we’ll look at a better solution, Task Factory’s SSIS Update Batch transfrom.
Task Factory is a suite of SSIS components available from Pragmatic Works. In this video we’ll look at the Data Validation Transform.
In past videos we looked at using the various Data cleansing transforms to clean up data coming into our SSIS package. What if you didn’t want to clean that data? Instead, you may just want to validate the data, then take some action based on that validity. To accomplish that, we can use the Task Factory SSIS Data Validation transform from Pragmatic Works.
In past videos we’ve looked at the various Data Cleansing Transforms available in Task Factory. We looked at the case transform, and saw how it could handle correcting capitalization errors. We saw how the Trim Plus transform could not only be used to trim leading and trailing spaces from a column but trim specified characters or words too. Regular Expressions were also examined in the RegEx Transform video.
There is one Data Cleansing component in the Task Factory suite that we haven’t covered yet, and it’s the grand daddy of them all. It’s appropriately named the Task Factory SSIS Data Cleansing Transform, combining the power of all the other data cleansing transforms into a single component.
If you are a Regular Expression guru, you’ve probably wished you could use Regular Expressions within your SSIS Packages. With the Task Factory SSIS RegEx Replace Transform, part of the Task Factory suite of SSIS components from Pragmatic Works, you can do just that. Let’s see how…
Of all the components in Task Factory, by far the coolest is the E-Mail Source. Using this nifty component you can actually pull your data into SSIS from an E-Mail! In this video you can see the Pragmatic Works tool in all it’s glory. Then you can see that the Task Factory SSIS E-Mail Source, like bowties, is cool.