Candy maker Cloetta merges local and global data using TIBCO Data Virtualization
Overall Satisfaction with TIBCO Data Virtualization
Cloetta’s data was mainly stored in an enterprise data warehouse (EDW). The time needed to make new data available for reporting through the EDW was relatively long. Local and external data comes in high volumes, is scattered in many parts or objects, and is unstructured. The business expects a fast time to solution, thus eventually data needs to be retrieved in real time.
The business was manually creating reports, which was time consuming, inefficient, exposed to errors, and sometimes impossible due to large amounts of data. Data and reports were not readily available for everyone who needed them.
Cloetta wanted to find a way to combine global, local, internal, and external data into one comprehensive report. The limited number of users on some of these reports required that any solution be cost-efficient.
- Faster Time to Solution
- We can combine new data that we made available through data virtualization with the data that we had before in the enterprise data warehouse. It’s a strong combination.
- No integrated version management and no possibility for tem based development (with check-out and check-in)
- Performance, more out of the box query optimization
- 'Type ahead' and auto correction / detection of table and field names on script is not there, so requires ot of maual / textual work
- First solution not live yet, not possible to give fact based numbers yet (and even when live, increased reporting insights are hard to qualify)
Well suited to read data from Excel files, although to set up an efficient and error-proof process it requires you to create a foundation and that is quite time consuming, but once it's there, it works well.
Solution is structured nicely in a folder hierarchy.
Less apppropriate when you need to add a lot of business logic to the data, if you need to enrich the data. Such logic is hard to implement and slows down a lot.
Less appropriate for creating real-time insights, caching or storing on database is almost always required to get good performance.