9 Considerations for Enterprises Establishing a Mobile BI Strategy

Today’s “Gen Y” workforce, a workforce which embraces “Bring Your Own Device” (BYOD) including tablets, smartphones and other mobile devices, is forcing organizations to put into place comprehensive mobile Business Intelligence (BI) strategies. While the enterprise mobility team will be the primary drivers in terms of choosing the right mobile strategy, there are very specific items related to BI which organizations must carefully consider. It’s crucial that the BI strategy and mobile BI apps work alongside the existing enterprise mobility strategy, complementing it and supporting it. A lot has been written and discussed about the mobility side of the equation, but not on the BI specific needs which enable mobility. Below are 9 crucial considerations enterprises must keep in mind when creating a mobile BI strategy:

  1. Determine the Mobility Framework You Will Use. Decide whether you want to use the mobility framework provided by your current BI vendor or use a reporting vendor agnostic one. Creating a custom BI mobility framework in-house is also an option. The decision regarding your mobility framework will be different based on the size, structure and needs of your organization.
  2. Determine Your Stance towards BYOD. BYOD is a growing phenomenon that is greatly impacting how businesses are run. It’s important to think about how BYOD will affect your BI applications. Depending on your objectives, you may want to consider simplifying the BYOD paradigm, and limit BI applications to a mobile OS platform.
  3. Tie Mobile BI Apps Back to the Business Case. Make sure mobile BI apps are not just an extension of existing content, but instead are targeted at a specific audience and serve a very specific business function.  Before deploying a mobile BI strategy, make sure you have a solid business case for doing so.
  4. Consider Highly Aggregated Data Marts for Mobile BI Apps. Don’t shy away from creating very highly aggregated data marts for Mobile BI apps when it’s necessary. However, don’t try to make existing data marts work if it’s too much of  a stretch. This will vary from organization to organization.
  5. Consider Quantity and Capabilities. Consider creating more BI apps with very specific business functions instead of trying to force your current BI apps to do things they are not really capable of doing. The more specialized an app, the better.
  6. Avoid Dynamic Derivation and Transformations. Mobile BI apps are expected to be low latency apps, thus it’s important to avoid dynamic derivations and transformations.
  7. Hold your Mobile BI Apps to a High Standard. Mobile BI apps will largely fall in the light weight, pervasive analysis group. If they don’t, then think twice about these apps and what they are really accomplishing for you.
  8. Think About Security. Ensure that existing traditional BI security roles and privileges are carried over to mobile BI apps and ensure that a new authorization mechanism is not invented. Given the BYOD craze, this is more important than ever.
  9. Think About Functionality,  Not Look and Feel. Instead of focusing on the novelty associated with new apps (in this case mobile BI apps), really drill down to their functionality. The whole purpose is to streamline business processes for users who are on the go. Can your mobile BI apps truly do this? If not, what improvements need to be made?

This post (list) was originally published on IT Business Edge as a slideshow and is re-posted here.

Kumar Ramamurthy

Vice President, Chief Technologist - Enterprise Information Management (EIM) Practice, Virtusa. Kumar has over fifteen years of experience in enterprise data architecture, database related technologies, software platforms and architecture assessments. Kumar is primarily involved in consulting engagements and assessments for Virtusa at existing and new EIM clients. He also has overall responsibility for delivery assurance from the EIM practice at Virtusa. Kumar has proven ability in consulting, selling, driving, delivering large scale EIM development/maintenance projects both in the enterprise and ISV spaces, while ably bridging the technical and business worlds to ensure the delivery of the best, most accurate business solutions to clients. He is particularly knowledgeable in Kimball and Inmon related DW architectures. He is adept at Data Integration, BI, Data Governance, Database Performance tuning, data modeling and MDM areas. Kumar has a Masters in Computer Science from Bharathiar University, Coimbatore, India. When he is not creating EIM solutions, Kumar spends time with his son and enjoys golf at his Arkansas home.

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