December 13, 2019
Everyone is talking about open source for advanced analytics, and for good reason. It is a free, collaborative community of innovation that is attracting large numbers of people to both contribute to it and use it.
Open source tools for analytics have been available for decades, but there has been a recent surge in use as more organizations make the move to analyze big data and hire more data scientists to do so. In a recent TDWI survey on artificial intelligence (AI) and machine learning (ML), a majority of respondents felt that open source was important or extremely important to their AI/ML efforts.
Often, open source is used in conjunction with commercial tools. For instance, in the same TDWI survey, 45% of respondents stated that they use both open source and commercial products. Only a small percent of survey respondents (less than 15%) use only open source.
Commercial vendors have recognized the significance of open source and they support it. They have included ways to make their products more open as well as enabling the use of open source in their products. In fact, TDWI often sees companies using open source and commercial products together. This is especially true for organizations that are more advanced in their analytics efforts.
Download this TDWI Pulse Report to learn about the move to open source, the benefits of both open source and commercial products, and how to strike a balance between the two.