I recently learned a new term, Productized Analytics, that summarizes many of the desires our clients have expressed over the last year. Companies often refer to this future state as Analytics-as-a-Service (AaaS). Regardless of the term, the idea is simple: Many vendors are developing specific solutions for well-defined, narrow use cases. Organizations want the ability and option to use these solutions – to quickly plug them into their analytic technology stack – when the need arises. It sounds like a great idea, but what prevents companies from doing this?
Data is always the problem
If we take a look at which AaaS solutions have worked well in the past, we will quickly notice that most of those solutions require data from outside the organization. The marketing area is filled with AaaS solutions. Why? Because marketing data often resides in external systems like Google, Adobe, or Hubspot. These solutions were built for the digital age, have well-defined schemas, and are easy to access. It is quite a different story if you are trying to leverage AaaS solutions using internal data. Internal data is messy. It includes mainframes and systems that were not built for the digital age. It includes ‘Frankenstein’ systems, with so many modifications bolted on no one knows what the system even does. Internal data is the reason AaaS cannot succeed without a drastic change.
Enter the Data Lake
Let’s be honest, the data warehouse does not have all the data we need to be successful. Without easy access to a consolidated data environment, AaaS will never succeed. AaaS requires easy, quick access to data, not point-to-point, long data integration cycles. If companies want to take advantage of AaaS offerings, they must first get their data in order. Leveraging solutions like Hadoop, AWS, or Azure, the data lake can serve as the primary connection point between internal data and AaaS solutions. Imagine a day when you have a specific narrow business problem, a vendor has a specific, narrow solution, and all you need is to give them access to an API that serves up the data they need to produce insights. The day is not that far. It won’t happen overnight, but investing wisely in the data lake, not just in technology but also in process and governance, provides more opportunities to leverage AaaS solutions. This proves true not only for external AaaS solutions but also internal groups that need quick, easy access to the wealth of internal data. It is time to start thinking about and treating data as a product, and organizations should put in place the organizational structure, technology, process, and talent required to do so. It is important to remember, big leaps require small initial steps.
Data drives all solutions. Without easy access to internal data, AaaS options are limited. There is no silver bullet. Internal data will always be messy, governance problems will always exist. But there are solutions available, specifically data lake solutions, that provide opportunities to make data more accessible and increase opportunities to leverage AaaS solutions. Thinking of data as a product, and making the necessary internal changes, can create competitive advantages in the near future.