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Getting Data Scientists to Live in an IT World

In this special guest feature, Dale Kim, Senior Director, Product Marketing at Hazelcast, discusses how data scientists are a bit unique in that they have technical skills and deal heavily with data yet are not necessarily tightly integrated with the rest of the IT team. Many do not consider themselves to be coders, and do not naturally embed themselves into the IT culture and the software development lifecycle.

Companies Are Bringing Data Back from the Cloud. Now They Need a Place to Put It

In this special guest feature, Shridar Subramanian, Vice President of Global Product Management and Marketing at StorageCraft, discusses the trend called “cloud data repatriation,” and how it appears to be gaining steam. A rethinking is happening where companies are looking to return at least some of their core data and applications to their on-premises data centers.

When Milliseconds Matter: Optimize Real-Time Data Sources Before It’s Too Late

In this special guest feature, Sam Mahalingam, Chief Technology Officer, at Altair Knowledge Works, believes that when milliseconds matter, it’s important to optimize real-time data sources before it’s too late. Sometimes, when fractions of a second matter, you don’t have the time for reports to be drafted, or meticulous lines of code to be built to construct a query. You need operators on the front lines unencumbered with the ability to drill down deep and spot these issues before they impact your bottom line.

9 Practical Actions to Improve Machine Learning for Fraud Prevention

In this special guest feature, Arjun Kakkar, Vice President Strategy and Operations at Ekata, provides 9 practical and actionable principles for product managers and business leaders working to use machine learning for fraud detection. The unique characteristics of online fraud detection, including the availability of large and diverse data sets with known outcomes, repeating patterns, and a need for quick decisions, make it a good candidate for machine learning.

How will AI Shape the Future of the Legal Services Industry

In this special guest feature, Stewart Dunlop, a content manager working with LegalZoom, highlights the fact that artificial intelligence has been predicted to be of value to many different industries, and perhaps one of the most feasible applications will be within legal services. This is due to several factors, which will be explained further in the article, but perhaps the most important is the fact that one of AI’s biggest strengths is data collection and analysis

Four Big Factors Shaping the Future of Data Science

In this special guest feature, Ryohei Fujimaki, Ph.D., Founder and CEO of dotData, discusses how AI and ML are having a profound impact on enterprise digital transformation becoming crucial as a competitive advantage and even for survival. As the field grows, four trends emerge, shaping data science in the next five years.

Considerations for Effective AI in Mobile Networks

In this special guest feature, Tom Luke, VP at Tutela, explores the different sources of data on offer to mobile network operators, and why it’s important for AI to be fed with lawful, ethical and robust big data in order to be effective.

How to Choose the Right Organizational Model for Data Science and Analytics

In this special guest feature, Martijn Theuwissen, a co-founder at DataCamp, highlights how the most competitive companies prioritize developing data fluency across their workforce to improve outcomes. Organizations that aren’t able to effectively make use of their available data today are already behind the curve.

Accessible and Affordable – Big Data for Small Business

In this special guest feature, David Zimmerman, CEO of LC Technology International, Inc., believes that small business owners that feel big data is just for the “big players” are in for a surprise when they check out the latest small business analytics tools. These tools are more accessible both in terms of cost and their actual user interfaces, making them usable by people with only moderate technical skill.

Turning IT Upside Down In a Machine Learning World

In this special guest feature, Chris Heineken, CEO and Co-founder of Atrium, suggests that as Machine Learning (ML) is growing in the IT and cloud space, understanding how to best utilize its capabilities will change the approach to implementing new IT investments. The systems of intelligence characterized by augmented ML, robust analytics, and workflow-based frameworks biased towards action, will dominate the mindset of those looking to place their organizations at the top end of the IT systems ‘bell curve.’