Jeff Cotrupe has joined the Product Marketing team at MongoDB as Senior Solutions Marketing Manager, responsible for driving solutions marketing and GTM content positioning UVP of product/services portfolio to a senior audience. Jeff is a core part of an energetic and globally distributed team reporting to Senior Director, Products and Solutions, based in the UK. MongoDB is the first database company to go public in more than two decades (NASDAQ: $MDB), its business growing at ~50% YoY, with the technology and vision to take on the multibillion-dollar incumbents as it disrupts and reshapes an entire industry.
“As an analyst I had forecast a total market opportunity of $67.89 billion in big data and analytics by 2019, growing to nearly $111 billion by 2022,” said Cotrupe. “I am excited to be at a truly global company capturing a sizable and growing share of that opportunity!”
The Retail Death Star (a euphemism for whoever you think it is) has such a glowing reputation for its acumen with data that other companies clamor to know how the Death Star does it. Personal experience suggests myth does not match reality…and two rising stars signal that e-commerce just got a LOT more competitive. Read the full piece here.
To conduct an audit to determine exactly what personal data (as defined in the GDPR) you are currently collecting, where you are storing it and how long you are retaining it–and destroying any personal data you cannot justify for essential business purposes.
That, while the GDPR applies to personal data held on citizens of the EU, organizations would do well to consider implementing data privacy best practices with regards to personal data on citizens of every region.
To train every employee on privacy, because a company’s posture on privacy is only as strong as its weakest link.
“Everyone wants analytic insights to make smarter, faster decisions–but before we reap the benefits of analytics, we must first sow good data,” said Cotrupe. Separating the wheat from the chaff requires effective data preparation: ETL and data mashups, data wrangling, data blending, however you say it or brand it, he added. “We assert that, partly as a result of the mountains of data bearing down on companies—and partly due to the methods companies are currently using—data science and IT are spending up to 80% of their time on data preparation before they ever get to analyze the data to obtain the analytic insights their organizations crave.”
This Stratecast event analyzes data issues companies are facing; how the explosion of new data sources is adding to the challenges; and barriers to adoption of data preparation; and presents a blueprint for data preparation.
IDG’s Infoworld has published Jeff Cotrupe’s blog post, The wonders of AI—or the shortcomings of search? “AI fires the imagination with visions of driverless cars and pilotless planes, and intelligence that is not merely artificial but increasingly alternative: machines imbued with so much human capacity that they can think for themselves—and, while we’re not really looking—for us,” said Cotrupe in the piece. “Much of the value AI is delivering today, however, is far removed from the dare-I-say-sexy AI activities described above.” AI cuts through the clutter, he said, to provide not endless pages of search results to wade through, but with specific recommendations tailored to you as the seeker of knowledge—or simply as the seeker of where to find the best Chicago-style pizza while away from home on a business trip.(!) “AI also means not having to search,” said Cotrupe, presenting you with choices (or content, or opportunities) you didn’t ask for—that you didn’t have to ask for. That predictive capability is a clear differentiator.
While both questioning and extolling the virtues of AI, however, Cotrupe has a warning for readers of the piece: “A quiet voice in a corner of my consciousness says…we should proceed with caution.”
Readers can find Cotrupe on a regular basis here at the Accelerating Growth Strategies through Big Data and Analytics blog on Infoworld.
“When it comes to real-time analytics, feeds and speeds are important, but the key point is this: if an organization has any employee, anywhere, who needs to take an important action but cannot because he or she is ‘waiting for data,’ the organization needs faster data,” said Jeff Cotrupe in a recent Stratecast report. The report, Everyone Wants “Real-time Analytic Insights”–but Which Architecture Will Get You There?, asserts that broad agreement exists that real-time analytics are essential to the survival and prosperity of the organization. In particular, financial markets, adtech, cybersecurity, and others now find themselves competing in ‘the millisecond economy,’ where survival is no longer possible without putting the freshest insights at the fingertips of their people.
Hyperbole and a lack of clarity about what to deploy, however, represent significant barriers to entry. The array of technology choices, the lack of clarity around those choices, and the organizational positioning and politics surrounding those choices constitute a barrier to adoption—creating confusion and indecision in the marketplace.
The report equips organizations to make the right decisions in this environment by analyzing Apache open source technologies that form the foundation of many real-time analytics deployments today; optimal architectures for real-time analytics; and strategies of some of the companies Cotrupe and Stratecast consider the leading providers in the space–and offers definitive recommendations on how buyers should proceed.
Jeff Cotrupe’s report, Innovating Financial Services in the Big Data Era, outlines the challenges and opportunities financial institutions face in 2018 and beyond. The analysis includes how these companies are evolving alongside emerging data trends; the ROI they are obtaining from actionable analytics; where spending is occurring today; and where it needs to be focused going forward. Technologies and issues analyzed include AI, blockchain, privacy and the GDPR, security, the IoT, data governance, risk management, and compliance. The analysis also includes case study snapshots of best practices in the industry at Barclays Bank, VISA, Wells Fargo, BNY Mellon, EY, Allstate, and Cheyne Capital.
The report is featured in media articles including in Fintech Innovation (Effective big data analytics management crucial for FSI growth) and in CXO Today (How Big Data Is Changing Banking And Finance), and is generating significant activity on Twitter and LinkedIn.