InfoWorld’s Matt Asay recently examined the issues the business world faces in democratizing data at all levels of the company.

Pointing to the state of big data technologies, Asay wrote: “Yet I can’t help but feel that big data doesn’t go far enough if it remains a tool for the data elite.”

Locked in the Hands of a Few?

Izenda Tech Blog logoOthers see the same challenge in democratizing data in organizations.

“For years, the BI and data analytics conversation was framed around how to aggregate massive volumes of data and then unleash the data scientists to find the value. Today, despite the information deluge, enterprise decision makers are often unable to access the data in a useful way,” Mare Lucas, COO of Serendipity, writes.

He continues: “The tools are designed for those who speak the language of algorithms and statistical analysis. It’s simply too hard for the everyday user to “ask” the data any questions — from the routine to the insightful. The end result? The speed of big data moves at a slower pace … and the power is locked in the hands of the few.”

Data Literacy Doesn’t Mean Limiting Access

Kris Hammond of Narrative Science, in a post on democratizing data, focuses on “data literacy,” meaning understanding data as it is presented via open initiatives and freely accessible APIs. Hammond, however, emphasizes that data literacy is a good thing only if being data literate is not a precondition to getting access to data.

“Democratization requires that we provide people with an easy way to understand the data. It requires sharing information in a form that everyone can read and understand. It requires timely communication about what is happening in a relevant and personal way. It means giving people the stories that are trapped in the data so they can do something with the information,” Hammond writes.

Hammond uses the example of standardized tests in education. With masses of data about student performance to consider, it would be absurd, Hammond argues, to train every teacher, administrator and parent how to analyze that data.

“Of course, if the analysis is the same in most cases, it means that the work of looking at the data, extracting facts from it, and then transforming those facts into a narrative can be done by an intelligent system. Rather than force everyone in the world to be a data scientist and communications expert, why not just teach the machine to do it so that the work can be done at scale?” Hammond writes.

The Potential of Democratizing Data

What is the potential from democratizing data? Grace Nasri writes in The Huffington Post: “According to an EMC study, the world’s information is more than doubling every two years. At the same time, 99 percent of the world’s data is not being analyzed and 96 percent of all data isn’t easily accessible.

“Data for data’s sake is powerless. It’s only when end-users are given access to the data to gain insights, see trends and make predictions that the data can actually tell a story. In this way, data becomes a bridge to knowledge.”

Izenda’s software platform seamlessly embeds real-time business intelligence at the end-users’ fingertips, within the application they are comfortable using.

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