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The Data Exchange Podcast: Ira Cohen on the evolution of tools for analysts.

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In this episode of the Data Exchange I speak with Ira Cohen: co-founder and Chief Data Scientist at Anodot1, a startup that uses AI for business monitoring. Ira and I have a shared interest in business intelligence software and other tools for analysts. I recently co-wrote a post on the impact of automation in BI tools and I was eager to explore the landscape of tools for analysts with Ira.

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Some recent trends include the introduction of new user interfaces and new modeling techniques. We’ve had tools that open up advanced analytics, statistical modeling, and machine learning to analysts, Ira and I discuss the introduction of tools that allow analysts to run realistic simulations and what-if scenarios.

These new tools are contributing to the evolution of the role of analysts. In a previous episode with Bahman Bahmani, he described training and assigning analysts to focus on tasks such as data preparation and model testing. Along these lines, Ira speculates that we will increasingly see two sets of analysts focused on two different areas:

    ❛ The analyst role is going to get split. There will be analysts focused on data pipelines and there will be analysts tasked with generating insights.

    … For analysts that are supposed to generate the insights, they should go learn the capabilities of machine learning algorithms, so they can leverage them. They don’t have to know how to code them.

    … For the analysts charged with getting more data for their organizations, they will need to learn what are potential sources of data.

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[1] I am an advisor to Anodot.