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Andrew Brust

Andrew J Brust

Andrew Brust has held developer, CTO, analyst, research director, and market strategist positions at organizations ranging from the City of New York and Cap Gemini to Gigaom and Datameer. He has worked with small, medium, and Fortune 1000 clients in numerous industries and with software companies ranging from small ISVs to large clients like Microsoft. The understanding of technology and the way customers use it that resulted from this experience makes his market and product analyses relevant, credible, and empathetic.

Andrew has tracked the Big Data and Analytics industry since its inception, as Gigaom’s Research Director and as ZDNet’s lead blogger for Big Data and Analytics. Andrew co-chairs Visual Studio Live!, one of the nation’s longest-running developer conferences. As a seasoned technical author and speaker in the database field, Andrew understands today’s market in the context of its extensive enterprise underpinnings.

Featured Content

This Radar report will help enterprise buyers become familiar with data science platforms and vendor offerings. Most enterprise organizations now work with high-volume data; data science platforms help them mine that data and codify the findings in predictive models. Results can range from improving strategic decision making to optimizing the customer experience.

This Radar report will help enterprise buyers become familiar with data science platforms and vendor offerings. Enterprise customers manage massive amounts of data and engage in multiple data-related activities, including data science. The goal of enterprise data science is to improve strategic decision making with the help of insights gained through analyzing big data.

Most technologists are accustomed to vendors’ bold—sometimes hyperbolic—claims of how easy the cloud journey can be and the multitude of benefits that organizations that make the journey can expect. It is especially true in the database platform arena—not just for analytics-focused platforms but also for operational databases, the de facto workhorses of modern-day business.

The vendors reviewed in this Radar are streaming specialists and offer something that vendors with broader platforms cannot: a streaming-centric view of data and analytics. From that unique vantage point, streaming isn’t just an option, but rather the primary mode of data ingestion, such that even a batch data modality can fit within it. Data streams are the ingest mechanism and often the egress target as well. Event processing and messaging constitute the data sharing medium. Streams can be used even for data storage rather than just for data in transit. Streaming is a mindset and a paradigm.

The vendors reviewed in this Radar are cloud providers and incumbent enterprise software players who offer a broad range of data, analytics, and other capabilities for enterprise customers. All the platforms in this report are extremely robust and would compete head-to-head with the specialist vendors if considered on a standalone basis.

Data science platforms help enterprises implement data-driven operations by predicting business outcomes through the use of machine learning (ML) and deep learning algorithms. Practitioners using these platforms include data scientists, who have expertise in computer science and statistics, and ML engineers, who focus on the operational aspects of deploying and monitoring models once data scientists have trained and verified them.


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