Data Science and Machine Learning Platforms: Should You Build or Buy?

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Data Science and Machine Learning Platforms: Should You Build or Buy?

Businessman trying to solve a maze questions

As enterprises embrace the potential of data science and machine learning, they face the challenges of operationalizing these processes in their technical environments and choosing investments according to their strategic objectives.

Written By

RTInsights Team

Mar 2, 2020

1 minute read

The question of whether a solution should be built internally or purchased from a vendor is a decision debated across teams.

In this whitepaper, “Data Science and Machine Learning Platforms: Should You Build or Buy?”, sponsored by Anaconda and promoted by RTInsights, you’ll learn about:

The baseline requirements for infrastructure and processes.
The key considerations of the build-versus-buy conundrum as well as a total cost of ownership (TCO) calculator and decision chart.
The requirements for building a platform internally.
A look at Anaconda Team Edition, a secure and governable repository of open-source data science and machine learning packages.

To download the whitepaper, fill in the form on the right.

RTInsights Team

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Data Science and Machine Learning Platforms: Should You Build or Buy?

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