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Q&A: Visualization Tools Fall Short Without Power of a Platform Behind Them

Today's BI users aren't looking for just a visualization tool. They want and need an analytics platform that includes governance and analytics, among other features.

Research firm Gartner recently identified "governed data discovery" as a key area for BI vendors. What is governed data discovery and how are vendors addressing this area of BI? In this interview, we talk with Qlik VP of global product marketing James Fisher about how a true platform solution goes beyond beautiful visualizations to provide governance, along with collaboration, decentralized self-service BI, and analytics.

BI This Week: What is "governed data discovery" and why is it important?

James Fisher: Gartner identified "governed data discovery" as one of the top areas in which today's BI providers must deliver in this year's Magic Quadrant for Business Intelligence and Analytics Platforms.

To some, governance just means security, but in reality it is so much more than that. With rules-based offerings, organizations can set up access and restrictions based on their own unique requirements. Meanwhile, libraries for data architecture, dimensions, and even visualizations can ensure that users are always looking and making decisions on the right data, the same data, and data they have access to. Libraries can also make sure that they share insights they uncover with only people who are allowed to see it. Perhaps the best part about having more governance is that governance actually becomes a tool to empower the organization, putting more confidence in decision-making processes.

We should also be clear that the data discovery piece is more than just a visualization tool. To deliver governed data discovery, a platform approach is needed that expands beyond self-service visualization to guided and embedded analytics.

What is the solution to supporting the open exploration of data that users demand while still allowing IT to maintain some semblance of control over data?

The key is to understand the true needs of individual users. Not all users require the same access, nor should they all be granted the same access. Some users want to play around with data architecture, and publish and deploy apps. Others may feel more comfortable in a controlled environment where they can simply drag and drop visualizations based on pre-defined dimensions and measures, or even be limited to simply consuming and exploring an application that has already been designed for them.

Part of the job of the IT staff is to determine who should be given access and how much access a user truly needs to be effective. That may vary depending on data source, application, topic area, or even the security of the network connection at any moment in time.

It's most important, however, that access constraints should at no point limit the user's ability to do freeform analysis. All data must be treated equal, and the systems should support users in how they want to perform analysis, not force them to structure it in advance.

Building on the question above, how can IT avoid the issue of "shadow IT" and so-called "spreadmarts" while still keeping users happy?

As we've seen over and over again, if users aren't happy with the solutions provided, they'll go out and find a better one on their own. This was very much apparent with the BYOD trend -- users found that their personal devices were actually more powerful than the devices they were provided at work.

IT can avoid this issue by empowering all of their users with the ability to answer not just "what happened," but "why it happened" and even "what is likely to happen next." Furthermore, by embracing a true platform rather than a visualization tool, IT can ensure that the solutions will grow to meet the evolving needs of the user base, ensuring they never "hit a wall."

Has the challenge of data governance changed over time with the evolution of technologies such as advanced visualization?

Traditionally, BI tools were restricted to users in the back office who were trained in data science and advanced analytics. When users needed answers to their questions, they went to these experts, told them what they needed, and then waited for the experts to come back with an answer.

The emergence of self-service visualization tools has shifted the paradigm. Now users want access to the data themselves so they can search, explore, and find answers to their questions in real time. As data tools spread out to the edge of the enterprise, IT must now control and empower a larger group of constituents. To meet these needs, IT needs a flexible governance strategy that allows them to control data, as well as specify who can see it and alter it and much more.

What advances have been made in helping users make sense of data from multiple sources?

Many organizations struggle to make sense of multiple, complex data sources -- and as a result tell only a part of the story. Data analytics can't be successful if users don't have access to all their data, and if they can't explore it in a natural, freeform, and intuitive way. This includes both internal data and third-party data that can provide deeper insights for users.

Associative data models are a great example of a technology that not only pulls from multiple data sources but also helps highlight relationships between data sources so users can see how information is linked. They can thus gain a more complete view without having to know how to structure the data before the analysis starts.

What is happening with mobile and BI right now in the context of visualization software?

I often say I don't believe in mobile BI -- BI should just be mobile. By that I mean that mobility should not be a separate part of your BI strategy. Instead, it should be completely ingrained in every step.

The reality is that decisions rarely happen in the comfort of your office. Users need to be able to access, explore, and visualize data on the fly so they can truly realize the benefits of insights at the point of decision, thus driving better outcomes. To achieve that, BI tools must be built on mobile from the ground up, and be responsive in their design. They also must work on any device with any form factor, rather than relying on separate mobile applications or requiring specific builds for mobile devices.

Your company has said that "the next generation of BI is all about platform provision, not tools -- enterprises are looking for more sustainability on the backend, including data management and governance." Can you expand on that statement?

Users today are not just looking for a visualization tool -- they want and need an analytics platform.

Unfortunately, the market is infiltrated by offerings that come up short. Large established "stack" vendors have BI offerings that are too inflexible. Meanwhile, visualization tools are too lightweight and don't have governance and enterprise manageability.

There's more to analytics than just visualization. Users need a modern solution from the ground up that delivers beautiful visualizations and is mobile and collaborative. They need a solution with enterprise-class governance and manageability, that supports centrally-deployed guided analytics, decentralized self-service, and embedded analytics in Web and enterprise applications.

Has user collaboration around data gotten easier recently? Why?

New innovations around storytelling have definitely changed the game when it comes to collaboration. Data analysis typically happens in a vacuum, whereas decision making is often a group activity. Storytelling allows users to share their insights and take colleagues on a data journey so they can defend their hypothesis and drive consensus. A key feature of this is the ability to enable users to dive into the raw data in real time so they can answer any questions or objections on the spot, rather than being derailed by curious coworkers and needing yet another meeting.

What does Qlik bring to this discussion?

Qlik supports a full spectrum of use cases with centrally deployed guided analytics, self-service data discovery, and embedded analytics in any enterprise or Web application. We provide agility for the business from upstream data sourcing and preparation to visualization and analytics, and on to downstream collaboration and reporting. Most important, this is all available within a governed framework that drives enterprise scalability and trust for IT.

With Qlik, no data is left behind. That makes our data big. We don't make anyone pre-determine the type of analysis they may want to do and then join the data to support that pre-conceived approach. We believe in equal opportunity for all data. We take it all in any form -- you're free to explore and use it in any way you'd like.

Because all of this data is automatically linked through our Qlik Indexing (QIX) Engine, you can also understand the full story in your data through freeform exploration. It's a value people find after they start using Qlik -- the unique ability to expose the full, true story within the data.

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