Our team at Burbank can help you to implement a Business Intelligence solution, to derive value from your data. Our consultants are highly skilled in the technical as well as the business aspects of BI projects. Our experience and sharing culture ensures that we follow best practices and deliver world class solutions to our clients.
We have completed many Business Intelligence intelligence implementations, end-to-end. We support the full implementation life cycle:
We specialize in *Qlik set of products (Qlikview and Qliksense) as our Business Intelligence tools of choice. Qlikview revolutionized the Business Intelligence industry with its data discovery approach. Qlikview enables end users to explore and discover their own data. Qlikview puts you in the driving seat and enables you to identify patterns and valuable insights with only a few clicks.
Qliksense (or Qlik Sense) is the newer product from Qlik, which is very similar to Qlikview, but utilizes the HTML5 standard. We support both Qlikview and Qliksense implementations, based on client requirements.
* Our consultants have completed the Qlikview certification program and are certified Qlikview designers and developers, by Qlik.
Microsoft’s business intelligence product is called Power BI. Power BI entered this market rather late, but has been improving and adding new features on a monthly basis. We have completed Microsoft Power BI implementations for clients, and foresee a lot of growth for Power BI in the future.
We provide support services to existing BI implementations. Our highly skilled team also performs optimizations on existing implementations, that yields great user experience improvements and time savings.
Practical Example: One of our clients is a large financial institution. Burbank was appointed to take over the support and maintenance of existing Qlikview models. This client has a lot of data and this specific business area uses very large datasets. For this client it is not uncommon to see Qlikview models that are gigabytes in size, due to their large source data.
After conducting our analysis and understanding the underlying data, we reduced one of the BI models from 6GB (6000MB) to 70MB. This optimization made the model much more responsive and increased the user satisfaction and more users started using the model. This also saved on storage space (multiple backup replications) and server load.
This example shows the value of thorough analysis and understanding the underlying data, and not just loading all data, as many competitors do.