Data democratization is more than just accessing data. It is the ongoing process of enabling everybody in an organization, irrespective of their technical know-how, to work with data comfortably, to feel confident talking about it and make data-informed decisions. This interesting information came to us from The Times of India in their article, “Democratising data by building a data universe.”

More than 2.5 quintillion bytes of data are generated every day. No longer is data restricted to only technology firms. Turning all this data into usable intelligence requires training and understanding. This is where technology comes in. By investing in the right technology, an organization may fully realize the value of their data.

Most organizations have little knowledge on how artificial intelligence (AI) systems make the decisions they do, and as a result, how the results are being applied in the various fields that AI and machine learning are being applied. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms.

Explainable AI is used to describe an AI model, its expected impact and potential biases. Why is this important? Because explainability becomes critical when the results can have an impact on data security or safety.

Melody K. Smith

Data Harmony is an award-winning semantic suite that
leverages explainable AI.
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