The market for data science and machine learning platforms is in flux. According to a new report by the research outfit Gartner, the more established players are being usurped by nimble players capable of adapting quickly to growing market demands.
Indeed, the Gartner 2018 “Magic Quadrant for Data Science and Machine-Learning Platforms” ranked smaller players such as H2O.ai and KNIME above more established players such as IBM, Microsoft, SAP and even SAS, a software company that practically invented the term “advanced analytics.”
And the analysts fully expect changes to continue, saying they’re seeing a maturity in analytics programs and a demand for data science tools from non-data scientists such as application developers. Indeed, investment in the market for data science and machine learning platforms is on the rise: Revenue grew by 9.3% in 2016 to $2.4 billion. Compare that to the overall business intelligence market, which saw a 4.5% growth in revenue in 2016.
The uptick of interest in data science and machine learning platforms is driving an increasingly crowded market. Cloud vendors such as Google and Amazon didn’t make the cut for one reason or another but are developing competing technology in this market. Nontraditional players are expanding their analytics portfolio or are edging their way in. The analysts pointed to a couple of examples, including Salesforce with the launch of its Einstein technology, and Workday, the human capital management and financial software vendor, with its acquisition of Platfora, a big data analytics company.
The rapid changes in the market are a signal to CIOs to keep a close eye on things. Gartner advises that CIOs stay abreast of how their current vendors are keeping up with this fast-moving market. If their IT organizations are considering an investment with new vendors, they need to investigate how new data science and machine learning platforms would complement rather than compete with existing platforms, according to the report.
The report analyzed 16 vendors that integrate the basic tools needed to build a data science solution, such as accessing and preparing the data, and offer the platforms that provide ways to implement a data science solution into business processes, infrastructure and products. Unlike last year, this year’s report teases out machine learning, calling it a “subset of data science” that requires “specific attention when evaluating these platforms.”
The Magic Quadrant, an actual four-by-four chart, ranks vendors on their completeness of vision and ability to execute. It then labels the vendors as a challenger, niche player, visionary or leader. Vendors deemed to be the most robust are categorized as leaders in the market. And the leaders are Alteryx, SAS, KNIME, RapidMiner and H2O.ai. Although in this field, those leaders almost certainly are looking over their shoulders at challengers TIBCO Software and MathWorks.