Tags: Data Democratization

Chief Data Officers and Data Democracy: The Difference Between Theory and Practice

Chief Data Officers have a lot of things on their plates. And one of those things is giving users freer access to the data they need. This is what we call "data democracy." Most CDOs like the idea of data democracy in theory. But in practice, the CDOs we talk to find that efforts to create a data democracy face at least four common barriers:

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Eliminating the Barriers to Data Democracy

There's a lot of talk these days about how to streamline the data supply chain. And the discussions often boil down to how to control an organization's data and how difficult and time consuming it is for business users to access it. As I wrote recently for DataInformed, highly structured systems for managing data like master data management (MDM) and enterprise data warehouses (EDWs) put a kink in the data supply chain.

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Towards Data Democratization: Thoughts on the Gartner BI & Analytics Summit

Some Attivio folks flew to the annual Gartner BI event last week to take the pulse of Business Intelligence, data discovery, and data democratization. We wanted to hear the latest from Gartner thought leaders and the several thousand data practitioners. In the opening keynote, there were 5 key takeaways. I’d like to zero in on numbers 2 and 3.

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Three Reasons That Data-Driven Organizations Need a Semantic Metadata Catalog

About a month ago, I devoted a post to the topic of semantic metadata catalogs.

A semantic metadata catalog is what Attivio produces when it spiders a business’s data sources. A metadata catalog can be searched using natural language search tools.

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Self-Service Data Discovery is the Key to Winning on Analytics

Can we agree that data is the new lodestar? Its accuracy is so potent that businesses that use it well have an indispensible key to success. That’s why data is now called “business’s second language” and even “the new oil.” It’s our best source of insight, confidence, and market leadership today.

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Data Democratization Depends on the Middle Layer of the Data Stack

Every organization recognizes the value of agility — the ability to work with our data iteratively and flexibly, pulling data from any source as needed for insight. To achieve agility, we work and rework the data stack, adjusting and rebuilding and tweaking everything from the data lake to the visualization tools. Too often, though, we fail to achieve agility in terms of the flow of data in the organization.

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Data Dexterity is the Last Mile in Agile BI

For all the talk about competing on analytics, little is said about what that takes. Strong visualization? Speed? Easy to use tools? It takes all that, of course, but one thing comes first: ready access to the data — the right data, for the people who need it, when they need it. As I said in my 5 predictions for BI and Big Data in 2016 post, without access to all your data, competing with analytics is just talk.

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A Semantic Metadata Catalog

We’ve been talking a lot about data democratization lately—what it means and how to achieve it. In practical terms, a data democracy provides unfettered access to all an organization’s data stores for anyone one that needs it. That means someone or something has to have a firm grasp of where all the data lives and understands what it contains.

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5 Predictions for BI and Big Data

As Nate Silver points out often—and humorously—in his book The Signal and the Noise, the world is full of noisy data. Inside the untapped potential of Big Data and Business Intelligence is the signal. When the power of data is fully harnessed, it enables executives to transform productivity and act with certainty. My predictions for 2016 are about the trends that move businesses through the noise to truly leverage information as a strategic asset.

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Enhanced Views Are A Winning Play

Competing on Innovation and Insight

“The only thing better than certain insight is certain insight you don’t have to work hard to find.”

Our view of any business situation is enhanced when every relevant insight is available for consideration.  In the early days of search, our queries determined precisely what we found.  We were limited by the data that was indexed and the terms we searched.

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