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Morningstar Launches Analytics Lab, a Data Science Platform for Finance Professionals

Morningstar Launches Analytics Lab, a Data Science Platform for Finance Professionals

New Capability in Morningstar Direct Allows Users to Create Custom “Notebooks” From Morningstar Data and Research

Morningstar, Inc., a leading provider of independent investment research, announced the launch of Analytics Lab, a new capability for data scientists and analysts in its investment analysis platform, Morningstar Direct, following the launch of the interactive research functionality last year. Analytics Lab lets users programmatically investigate Morningstar data and research more deeply to discover new opportunities for investing success.

Analytics Lab gives users access to the development platform behind the prebuilt Morningstar research and data sets, enabling users to create custom notebooks in a hosted environment, combining the powers of Morningstar data with Python programming language.

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“Investors need to extract meaningful insights from immense amounts of data every day. Analytics Lab opens the door to Morningstar’s core data and research, enabling users to discover new opportunities for investing success much more efficiently in a flexible environment,” said Frannie Besztery, head of Morningstar Direct. “Our data, analytics, and communication capabilities create a platform that’s completely new to the Morningstar universe which will empower our clients like never before.”

For those familiar with Python, the module evolves from a prebuilt analysis tool to a fully customizable and personalized platform. Users can now explore and discover Morningstar data with flexibility and leverage previously created Data Sets, Lists and Search Criteria, and Performance Reports from Morningstar Direct. As a result, Analytics Lab allows users with coding and analytical skills to automate their workflows faster than ever before and share these results with other Morningstar Direct users at their firm.

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Analytics Lab incudes features to simplify the often-lengthy process of finding data and developing code including drag-and-drop capabilities to automatically insert code, robust Python documentation, sample queries, and tutorial notebooks help new users find and navigate Morningstar’s data.

Coding skills aren’t a prerequisite to benefit from Analytics Lab’s technological power. Morningstar’s library of prebuilt research and data sets, couples multi-faceted data sets with automated analysis, allowing clients to quickly visualize meaningful insights and turn research into action. For example, the firm diversity data set can analyze the presence of diversity within an asset management firm’s ownership, board, employee workforce, company policies, and hired service providers. Since the initial launch last year, Morningstar released 13 data sets, on various industry trends and will be launching data sets about U.S. fund fee trends, active and passive fund analysis, ESG topics, and more.

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