Microsoft & Open Source: What it Means for Analytics

To those who have the perception of Microsoft as a corporate giant far removed from the world of open source software, the news that it has recently become a Platinum member of the Linux Foundation must have come as a total surprise. For those who have been paying attention, it is actually the logical next step in the realization of the long-expressed vision of Microsoft CEO Satya Nadella.

Under Nadella, especially in recent years, Microsoft has shown many signs of warming up to the open source community: the .NET Core project, the SQL Server release for Linux, the incorporation of open source software into Azure: the signs are all there. Azure development has included Linux distributions that compete directly with Windows Servers, and they aren’t just a gesture in the direction of open source: they account for about a third of all Azure server instances. Furthermore, Microsoft is collaborating on a number of projects managed by the Linux Foundation.

Undoubtedly, the Platinum membership in the Linux Foundation alongside other industry giants like Intel, IBM and Oracle will have an impact on many Microsoft products. So what could it mean for our community? How will it affect the world of data analytics?

Arguably, the three most common tools for analytics are SAS, R and Python. Extensive comparisons have been published, and, in most cases, the conclusion is that even with its hefty price tag, SAS is the best enterprise solution. The reasoning is the comprehensive set of features that SAS can provide, its simpler language, and its robust capabilities for handling large volumes of data.

Besides cost, the main complaints about SAS focus on its graphical capabilities and text-processing features—which, it should be noted, are both increasingly relevant in the era of big data. R and Python have solid capabilities in these two areas and have both become must-haves in the toolkit of the modern data scientist.

In 2015, Microsoft acquired Revolution Analytics, a leading commercial distributor of R, and announced the plan to use the software to offer big data applications to cloud and desktop customers. The pledge to contribute to the further development of R has not been forgotten: we have seen the deployment of numerous R-related products, like SQL Server R Services, which helped to bridge one of R’s deficiencies in database connectivity; R Server in Azure; and R Tools for Visual Studio.

Most notably, Revolution R, which is now branded as Microsoft R Open, has remained open source.

We live in a Microsoft Windows-dominated corporate world. Clearly, the adoption of open source software could become much smoother if supported by Microsoft. At the same time, a boost in development support for tools like R could turn it into a much stronger contender to licensed software, which can only benefit analysts, who would be provided with a much richer and more deeply interconnected ecosystem.

As a leading analytics services provider, Evalueserve closely monitors market trends so we can adapt our offerings to the evolving needs of our clients. We’ve witnessed the increasing interest in the open source community among our clients. To give just two examples: a leading retail bank recently migrated a large portion of its reporting and analytics processes from SAS to R; and a large US-based energy retailer began experimentation with Hadoop and Python. That is why we have continued to invest in talent development in numerous tools: our reputed Data Scientist Trainee Program has solid components of R and Python at its core.

It remains to be seen where Microsoft R Open and the other support for open source software will take Microsoft and the corporate world, but it will certainly be a unique and interesting journey that we are happy to be part of.

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