Exploring Analytics & AI in 2020: A Detailed Primer

It is often said that data is the most valuable asset a business can have; the oil of a digital era. But data itself, while interesting, often leaves out a variety of important details – creating a need for analytics. And how we complete these analytics has evolved – and will continue to do so; particularly with the rapid proliferation of AI tools and technologies.

What is analytics? [Separate article]

What are the benefits of analytics?

Data analytics allows companies to institute data-driven decision making which allows companies to minimize bias and gut feel while making both important corporate decisions and making fast operational decisions. For example; with Data Analytics, a business can classify customers according to patterns found in data to understand their customers’ perspective. Read more

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Synthetic Data: An Introduction & 10 Tools [2020 Update]

Synthetic data, as the name suggests, is data that is artificially created rather than being generated by actual events. It is often created with the help of algorithms and is used for a wide range of activities, including as test data for new products and tools, for model validation, and in AI needs.

The questions that this post sets out to answer include:

Why is synthetic data important and what are some use cases for it?

How does synthetic data perform compared to real data?

What are some benefits associated with synthetic data?

What are some basics of synthetic data creation?

What are some challenges associated with synthetic data?

What are some tools related to synthetic data?

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