Much of the conversation about Big Data surrounds the topic of its actual collection, but unless both your internal and external users can easily consume data, it is worthless.

I was talking with Michel Guillet of Juice Analytics, a provider of products and services that make visualizing Big Data easier, about this very problem.

He shared with me some common myths he sees companies falling for around Big Data:

Myth: Internal users of data want flexibility, not guidance.

Have you ever been to the grocery store and found yourself standing on one of the aisles, overwhelmed by the number of choices?

The same is true of Big Data. The fact is that while your executives and managers may express interest in more data (more metrics, more dimensions, raw data access, more chart choices, etc.) this is an indicator of uncertainty, not of an interest to do more robust analysis. Michel says that when people are unsure of what exactly to do with the data, they figure they might as well as ask for all of it.

Users want to be guided to their answers, and they want the data presented so as to remove uncertainty, not just raise more questions. They won't invest more than a few minutes using data to try to answer their questions.

Investing time on report design and giving the user a clearly guided path of exploration is the way to go.

Myth: Our customers haven't asked for it.

While customers may not ask you for a data product directly, they might be asking for it indirectly. It could be masked in phrases that you, or your sales or support teams, may have heard, such as:

  • How do I compare to the industry average?
  • Can I get more frequent access to my data?
  • Can others in my organization get access?
  • I need to provide a monthly report to my boss.

Michel shared that customers rarely ask for Big Data reporting at the beginning of a project, but they always want it at the end. If you design with this requirement in mind, you will have a better handle on what your systems need to collect and why.

Myth: I can't charge customers for their data.

It's not the data being sold, but the insights, metrics, algorithms, and display baked into the analysis that increases its value. Don't position a data product as "easy access to raw data," but rather as a solution that solves a problem.

Can you easily compare your customers' data to the rest of your customer base? Are third-party sources available that allow for benchmarking?

While your customers do indeed own their data, you can charge for the incremental value added, such as industry-specific metrics, customer benchmarks, and recommendations.

Big Data can be a competitive differentiator for your company if you avoid the hype and develop a measured and purposeful plan for its collection and use.