Governed Data Discovery
Balancing Flexibility and Standards
The Discovery Hub is the magic component in any Data Discovery and Self-Service BI implementation. Covering end-to-end needs, the Hub enables business while simultaneously liberating IT.
We hereby introduce the first truly combined platform- covering all disciplines- that is needed for the organization to expose all relevant data to the business in a usable, and agile way. With the Discovery Hub, there is no need for standalone data preparation and data blending, catalog, or data quality tools. That’s the beauty of full automation.
The technology behind the hub is the same as that being used to automate the classic Enterprise Data Warehouse today but the design of the hub is focused on bridging the business and IT gap while respecting the business need for data access and simultaneously respecting the need for adherence to IT policy and governance.
Since the hub is built on automation technology, it can be implemented for the needs and at the speed of business. IT only has to maintain the ODS layer while the business serves itself and takes care of the rest!
Read on to see how this can help you.
Provide Business Users with Access to the Data They Need When They Need it
Respond to Changes Quickly and Efficiently
Maintain Governance, Security, and Control
Dramatically Reduce Your Backlog of IT Requests
Maintain the ODS, with full security and governance on sources system
What does Barry Devlin have to say about
the design of the Modern Data Warehouse?
This is the layer in which we connect all corporate data sources by accruing data in raw force and structure. There is no data manipulation here.
The strength of this approach is our ability to connect to the ever-growing, ever-changing and myriad types of data sources. The ODS is also as close to real-time as possible, based on what different sources systems can deliver and what IT accept in terms of workload on the different data sources.
The end product is that all data are now located in one place with the result that all users using Data Discovery have only one source to connect to in order to get access to raw data.
The ODS solves a large part of the problem, allowing users to avoid the need to access data sources directly and simultaneously allowing IT to maintain data governance.
The Modern Data Warehouse is built on the notion that business users need to access and understand data. As defined in Barry Devlin’s seminal white-paper, the MDW design differs from the classic star schema since pre-defining future uses of data is not possible. Data, in order to be useful, must be available in a format business users can understand.
With the MDW data quality issues need be handled only once. Also golden records are handled in which similar data from different systems can be combined into one data-set.
In addition, the MDW manages to preserve historical data since data changes over-time and since, at times, source systems are sunsetted.
In this way, the Modern Data Warehouse opens up new possibilities for business users who don’t need to be data experts in order to do their own data discovery.
Whichever Discovery Tool you prefer, we can help you prepare selected data for your applications.
For avid Qlik Sense users, we can help you to completely avoid the scripting hassle, by fully integrate the data model and the data directly into Qlik Sense.
What do our +2,600 customers have to say:
Time to result has been spectacular! TimeXtender simply helped us automate the technical process, just like QlikView has helped us deliver striking visuals
… It is reassuring to know that whatever future change may hold, our team will be ready to handle it.
What do our +2,600 customers have to say:
In the year since we implemented TimeXtender, it has already paid for itself several times
Thomas Guldberg Hansen
CFO – Pindstrup Mosebrug
TX DWA – The Engine Behind
Data Warehouse Automation – What It Really Means
Data Warehouse Automation (DWA) is all the rage right now. But what do we really mean when we say Data Warehouse Automation? And what does it mean for your business? In essence, it means that DWA enables you to rapidly deploy and modify your data warehouse by automating the process from data retrieval through data transformation to deployment and generation of project documentation
DWA makes all of this possible because the initial implementation takes place up to 5 times faster than in traditional data warehousing projects. Changes and improvements can be put into effect after the system goes live without interfering with business operations.
Moreover, DWA also minimizes manual code writing and repetitive, labor-intensive, and time-consuming tasks.