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In a previous post AI Learning vs Memorizing? I discuss how machine learning developed as a way to overcome certain limitations in the early days of artificial intelligence. Without machine learning, machines would be able to do only what they were told or were programmed to do. Machine learning expands their capabilities beyond what they were merely programmed to do.

As shown below, here are examples of machine learning applications across a wide variety of fields ranging from data security and software development to investing and healthcare.

One of the best ways to understand machine learning is to look at the various applications of machine learning in the real world:

These are only a few of the vast number of machine learning applications that are possible. As machine learning matures, you are likely to see many more real-world applications and consumer products and services driven by machine learning.

Democratizing data involves making it available to personnel throughout an organization and providing them with the tools and training needed to query and analyze that data. In this post, I discuss the potential benefits and drawbacks of data democratization and provide some general guidance for democratizing data.

Benefits of Data Democratization

Potential Drawbacks of Data Democratization

Nearly every organization that democratizes its data properly reports that the benefits of doing so far outweigh any potential drawbacks. However, organizations do need to address the following concerns:

Drivers of Democratization

Traditionally, the IT department has owned the data and was in charge of extracting meaning from it and presenting the information to executives and managers. The development of various technologies, tools, and techniques is driving the movement toward greater democratization of data:

Democratizing Data in Your Organization

Democratizing data is not a simple matter of providing everyone in the organization unfettered access to all of the organization’s data, especially if the organization stores sensitive data. To democratize data safely and effectively, consider the following guidelines:

If your organization currently places the power of its data in the hands of a few, I hope this article encourages you to strongly consider the possibility of democratizing your organization’s data. By placing the power of data and analytics in the hands of the many, you’re likely to be surprised by the resulting increase in innovation and agility. Your organization will be much better equipped to adapt in a competitive landscape that’s constantly changing.

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