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Agile Analytics

Agile analytics is a paradigm for exploring data that focuses on finding value in a dataset rather than proving hypotheses by using a free-form adaptive approach. The rise of agile development methodologies has created a whole field that focuses on adaptability and collaboration over the traditionally structured development cycle.

How Agile Analytics works?

Agile analytics focuses on a swiftly iterative one-after-the-other cycle that focuses on finding value rather than proving a hypothesis. This paradigm examines multiple data points speedily and in a more experimental fashion to find new interpretations and unexpected answers. The method prioritizes offering value rather than a set process and is used to analyze data that isn’t always fully organized or clean.

What can I use Agile Analytics for?

One major application for agile analytics is in the financial industry. When looking for evidence of malfeasance or illegal activities, investigators cannot always find a linear paper trail to prove a crime was committed. Agile analytics allow for a more open analysis of data, which can show different anomalous activities that can be connected, even if not obvious at first.

What’s agile analytics? How is it different from just plain analytics?

Generally speaking, when someone refers to “Agile” anything, they are usually referring to a disciplined, iterative, feedback oriented approach. See the full article for more details.

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