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      4 min read

      Even faster data warehousing with TX DWA

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      Feature Highlights in TX DWA, the newest version of TimeXtender's data warehouse automation platform.

      Easier Reporting Directly from the Data Warehouse

      With tools such as Microsoft Power BI, reporting directly from the data warehouse, as opposed to using OLAP cubes, is becoming increasingly popular. This puts new demands on data warehouses to structure and deliver data to applications in a way that they can understand – and with the performance users expect.

      Features in the latest release of our Data Warehouse Automation platform address these challenges. To enable reporting applications to understand how the data in the data warehouse fits together, you can now choose to make the relations between tables physical. This means that the tables get to know each other better, since the relation is now stored in the database and not just in the metadata generated by the software.

      To improve the performance of reports, the new release makes it easy to help reporting tools with some of the calculation work. Aggregated tables enables you to easily create aggregations, such as sales per customer per month, saving the reporting tool from doing it and thereby improving performance.

      Detailed Data Access Control

      While you would obviously not like your biggest competitor to see all the data gathered in you data warehouse, making sure the right people inside your organization have access to only the right information is almost equally important.

      Our new release enables you to control access to data on the data warehouse level, which is convenient when you do reporting directly from the data warehouse. You can restrict access to specific data all together or just some of the data. For instance, a salesperson might only have access to detailed information about his or her own sales, while the sales director has access to all sales data.At the same time, neither the sales person nor the sales director have access to financial data.

      Improved Execution Performance

      You can never have too much of a good thing – and your business intelligence solution can never be too fast. That is why we have included a number of performance improvements in our new release that makes execution – the process of extracting data from ERP and other systems, making the data ready for reporting and analysis and loading the data into the data warehouse – much faster. 

      The headline feature is prioritizing. While our intelligent execution engine is able to process loads of data simultaneously, squeezing as much performance out of you hardware as possible, it is not smart enough to prioritize anything but getting it done as fast as possible.

      In real life, however, you might have other considerations: For instance, you might only have a few hours each night to fetch data from an otherwise busy server. Using our new prioritizing feature, you can give priority to certain tables and sources to make sure they are processed as early as possible. You can also choose to block all other execution tasks until a certain step is completed.

      In addition to prioritizing some tables, we are also introducing another way of guiding the execution engine.
      When the execution engine figures out what to do, it does not take into account that some systems might not be able to handle multiple simultaneous connections without slowing down considerably. This can lead to unexpected drops in the performance of the overall execution. To safeguard against such problems, you can now set the maximum number of simultaneous connections to a specific source.

      Unfortunately, an execution does not always go as planned. In this release, we have made a few improvements that makes it easier for you to handle failure.

      You probably have some source systems in your solution that are less than critical for your reporting. You can now configure your solution so that the entire execution does not stop just because the software cannot reach these noncritical systems. Instead, you can choose to keep the newest data from the system in question until fresh data can be fetched.

      When a critical error do occur and a three-hour execution fails halfway through, a large amount of data has already been processed before the execution stopped. In our new release, you can fix the error and resume the execution from where it stopped, saving sometimes hours of waiting.

      AnySource – The Most Flexible Connection Adapter Ever

      Modern businesses often have many specialized systems in their IT portfolio. The get a complete overview of your business, you need to get data from all these systems. With the AnySource adapter included in our new release, connecting to a wide number of systems just go a whole lot easier. 

      The AnySource adapter works in conjunction with specialized drivers provided by software vendors or third-party developers that follow the OLE DB or ADO standards. This opens up new possibilities. For example, drivers for social networks could enable you to fetch data about fans and followers, allowing you to enrich your reports with demographic data about the community around your products or services.

      Built Your Data Warehouse Even Faster

      While a Data Warehouse Automation platform such as ours allows you to build a data warehouse much faster than with traditional methods, our goal is to make it both faster and easier with each release. The keyword, of cause, is automation. Why should you have to do routine tasks when we can automate them?

      One routine task we have automated in the new release is adding a basic time dimension to you data warehouse. You can also add custom periods to track data from e.g. the holiday season easily in your reporting. In addition to that, the new time dimension contains indexes that makes it easier to compare the present date with, for example, the last quarter or same month last year.

      Another useful addition to the data warehouse builder’s toolbox in the new release is project variables. Instead of changing the same value in five or ten places across the project, you now only have to change it once. You can also use context-sensitive variables, such as server, environment or user name, which gives you an easy way to handle for instance production and development environments differently.

      In TX2014 SR2, we introduced Project Perspectives that makes it easier maintain an overview over large projects. Now, we have made them a bit smarter. You can now configure a perspective to update itself dynamically, automatically including all the tables and other objects that has something to do with objects already in the perspective. For instance, if you are using OLAP cubes, you can create a dynamic perspective based on a sales, production or finance cube and instantly have an overview of all the objects relating to the area you have chosen.

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