Data Democratization: The Time is Now

There was a lot of talk at the Tableau Conference last month about the challenge of getting the right data into Tableau. There’s a process bottleneck between IT and the business that prevents the easy flow of data in the organization. Data democratization is a powerful concept that ultimately enables companies to compete on analytics.

Data Democratization

From EDW to Big Data

It’s hardly a new problem. The business intelligence industry has dreamed of the enterprise data warehouse, and now it dreams of big data and the gold it may become. Ultimately, it’s all to pursue the same goal: to use data as the strategic asset it should be. But something has always come in the way.

The data warehouse got hung up, as tech investor David Black wrote in a recent blog post, Big Data and Data Warehouses, on “a simple little acronym in EDW that is the tip of the mud-trap in which EDW gets bogged: ETL.” That stands for extract, transform, and load, or getting the data from its source to where it’s needed. “Simple, right?” Black writes, “Oh, if only it were.” The difficulty of that little process helps explain why the “glowing promise of the enterprise data warehouse so often ends up with the participants hungry and wounded.”

Now comes big data, which promises to do what the data warehouse couldn’t. Big data’s still young, but so far it’s all about piling up useless mountains of data. Eventually, we hope that enough of it will turn into business gold — and justify the enormous investment. By 2018, $114 billion will have been invested in big data infrastructure, predicts ABI Research. Capgemini finds that “very successful” big data projects amount to just 8%, and only 27% are considered “successful.”

The Critical Link to Data Democratization

The critical link left mostly undiscussed is this: how is all that data going to find its way into the analytics tools? There’s plenty of storage. How do you know what data is what? If you have a question, which part of the lake do you paddle toward? Where do you dip your bucket?

In today’s world, the path between data storage and data consumers is largely a manual process involving a lot of back and forth between data managers and business analysts. It is a time sink for everyone involved, and the results often come in too late to be relevant.

The sooner the data supply chain can be streamlined, and the data democratized for the waiting data consumers, the sooner that data becomes a strategic asset. That’s when consumers can base their analysis on the best data from across the enterprise. That’s when they make the best choices. And that’s when the organization finds out what data can really do.

Making it Real: Amazon.com for Data

The dream of democratized data is nothing short of transformative. What if a self-service semantic data catalog were as simple as shopping on Amazon? The data analyst comes with a question and in minutes finds the right data? Natural language and keyword search helps locate likely sources. The system recommends relevant data. Finally, an ecommerce-like shopping cart delivers it.

It’s not just a dream. It’s what Attivio customers wake up to already.

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