The sparkle and shine on all the new data-analytics software and services can sometimes blind enterprise shoppers. But the number of big-data successes is dishearteningly close to nil, according to some analysts. Experts say technology alone can’t make a business data-driven; a cultural shift is in order, but it’s hard work. Do certain technologies come with a free gift of culture enhancements inside the box?

People feel there’s a vast technical chasm between themselves and data science. Data cataloging is gaining popularity as a tool for humanizing it. Plain-English labeling, annotation and search help close the chasm. Diverse users begin to feel more comfortable with data. They start trusting it and regularly incorporating it into decision making across the business, according to Stephanie McReynolds (pictured), vice president of marketing at Alation Inc.

Alation’s consultations with customers don’t begin and end with a technical demo. “It’s as much about how do our products support psychological comfort with data, as well as how do they support the actual workflow of getting that query completed or getting that data certified,” McReynolds said.

Alation is a six-year-old company with more than 100 customers. One customer — Scout24 AG, headquartered in Munich Germany — has 70 percent of the company doing self-service analytics. These are non-data scientists actually driving business outcomes with data, McReynolds pointed out.

McReynolds sat down with Peter Burris (@plburris) during a CUBE Conversation at theCUBE Studio in Palo Alto, California. They discussed how data cataloging is sparking cultural shifts in organizations. (* Disclosure below.)

This week, theCUBE spotlights Alation in our Startup of the Week Feature.

Data catalog is analytics acrobat

A number of organizations are maneuvering Alation’s data catalog to support interesting new paradigms for collaboration, networking, etc. Among them are Munich Reinsurance Co. and Pfizer Inc. “There’s an internal community that is using the data catalog as a collaboration platform and kind of as a social-networking platform for the data nerds,” McReynolds stated.

Even people brand new to data analytics can get juice from the platform right away. A product manager, for example, might not know how to write SQL query or validate data for quality and consistency. He or she can go to the data catalog and find trusted resources, like written reports or raw data someone has certified or used effectively in the past. 

Behavioral tracking puts analytics within the reach of laymen. Users can see through the catalog pages who has used data and how, whether it’s validated, etc. This “social influence” helps build trust in data across organizations, McReynolds explained.

Munich Reinsurance made the catalog into a collaboration platform for actuaries and knowledgeable individuals in the business. The goal is to define what data products could support entirely new business units.

Pfizer concocted a new drug-discovery aid with Alation’s data catalog, Tableau and a data-science platform. The integrated analytics workbench helps researchers treat patients with rare variants of ailments like heart disease. Machine-learning algorithms in tandem with the data catalog can catch one or two percent of aberrant patients. Pfizer can then deliver appropriate drugs to them. 

“These are two great examples of organizations that a couple years ago started with the data catalog but have driven so many more initiatives than just analyst productivity off of that implementation,” McReynolds said.

Data-driven: The fast track to transformation

Over the past five years, companies have spent $3.2 trillion on innovation, according to Accenture LLC’s report “Discover Where Value’s Hiding: How to Unlock the Value of Your Innovation Investments.” The return on investment in these projects declined by 27 percent over the same period, Mike Moore, senior principal at Accenture, recently told theCUBE. Many companies are attempting digital transformation in spots without the push of the whole company behind them.

“That’s really not enough to get new customers in this day and age,” Moore said.

A paltry 14 percent of companies are actually making gains through their innovation projects, according to the report. One thing they tend to have in common is that they are data-driven. “High-growth companies generate, share and deploy data to deliver new product and service innovations safely and securely,” the report said.

Another feature of the high-growth elite is that they are inclusive. They take an approach to innovation that incorporates a broad range of stakeholders.

RevAlation is data-driven drum circle

Alation and its customers have created a network of best-practice sharing. Alation users are freely exchanging ideas, tips and success stories. The goal is to paint a clear picture of what data-driven culture looks like.

“If you can start to share best practices in terms of how you create a data-driven culture across organizations, you can begin to really get breakthrough speed in making this transformation to a data driven organization,” McReynolds said.

The company recently kicked off a series of meetings called RevAlation. It provides a space for Alation users to pool their knowledge, not just about tech, but every aspect of data-driven business.

“They’re actually talking about how do we improve the data literacy of our organizations, and what are the programs in place that leverage the data catalog to do that.” McReynolds said.

Many business people still fear that they lack the technical chops to make decisions with data, according to McReynolds. Alation believes data cataloging  can close the gap between access to data and actually trusting it.

“We have the highest number of data-catalog customers of any other vendor I’m familiar with in the space,” McReynolds stated. (Alation just raised $50 million in Series C funding to further its leadership in the market.)

A future is in sight where people use and trust data cataloging the same way they do Google. “That evolution in data needs to happen for our organizations to broadly see analytic-driven outcomes just as in our consumer life … Google had to show us … a kind of answer machine on the internet,” McReynolds concluded.