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7 Key Members of Every Big Data Team

In this contributed article, freelance technology journalist Josh McAllister provides an overview of the seven main staff members you’ll need to put together for a successful and highly efficient Big Data team. When putting together a Big Data team, it’s important that you create an operational structure allowing all members to take advantage of each other’s work. Your company will also need to have the technological infrastructure needed to support its Big Data. This can be done by investing in the right technologies for your business type, size and industry.

Predictive Analytics Solve Retail’s Trickiest Problem: Customer Intent

In this special guest feature, Rachel Wolan, Vice President of Product at Euclid discusses what predictive analytics is really about: helping retailers forecast intent. If we can make smart, data-backed predictions on what customers are likely to do, and when, retail marketers can then deliver a true curated shopping experience.

Interview: John Purrier, CTO at CA Automic

I recently caught up with John Purrier, CTO at CA Automic, to discuss the affect artificial intelligence (AI) will have this year on business processes. John is Chief Technology Officer at CA Automic, a leader in business automation software (acquired by CA Technologies) where he is responsible for driving Automic’s automation strategy.

How Data Scientists Are Wasting Their Time

In this contributed article, Abhi Yadav, Co-founder & CEO at ZyloTech points that while data scientists are flawed and there are lots of ways in which they could improve, so too are machines. It would seem that the best way forward is to work side-by-side, fleshy-arm-in-robotic-arm with the new race of machines and robots that will undoubtedly make our lives easier.

How Big Data Analytics Can Improve Demand-Supply Cycle in Retail?

In this contributed article, James Warner, a business intelligence analyst at NexSoftSys.com, discusses big data uses in the retail industry, specifically about the supply and demand cycle. With big data entering all mainstream industries, analytics is surely going to be different and not limited to projections and predictions. The supply chain in retail is a small example of the vast applicability of big data.

The Drilling Rigs of the Big Data Age

In this contributed article, Navin Chaddha, Managing Director, at Mayfield, a top-tier Silicon Valley venture capital firm with $2.7 billion under management and a 48 year history of investing, outlines 5 big areas of opportunity as well as some trends that are creating the need for a new class of companies that will serve as the drilling rigs of the big data age.

Tips from the Shelves: Proven Methods for Boosting Data Warehouse Speeds

In this special guest feature, Jason Harris, Evangelist at Panoply, discusses how data collection and analysis are further enhanced when including methods for disseminating, analyzing, and distributing data.

Interview: Todd Wright, Senior Product Marketing Manager, Data Management at SAS

I recently caught up with Todd Wright, Senior Product Marketing Manager, Data Management at SAS, to discuss GDPR, the first update to the European privacy and protection laws in 23 years. According to Todd, GDPR is being taken very serious by regulators, to the point that they are considering data protection and privacy as a human rights issue. Data on minors, medical records, sexual orientation, race, age, and weight will be some of the top concerns, as they can all be considered areas that could form a bias towards an individual when processing data.

AI for the Enterprise: The Citizen Data Scientist

In this special guest feature, Rick Rider Product Director, Technology at Infor offers four important areas on which AI software providers can capitalize and place increased focus in order to find success.

Top Skills Data Scientists Need To Learn in 2018

Data scientists are in high demand, taking the number 1 spot in Glassdoor’s Best Jobs in America list in 2016 and 2017, with 4,84 position available and boasting a median base salary of $110,000. According to Jim Webber, Chief Scientist at Neo4j, the following is a short-list of the most essential tech skills for data scientists to adopt this year.