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Interview: Ashley Kramer, VP Product Management at Alteryx

I recently caught up with Ashley Kramer, VP Product Management for Alteryx during the company’s Inspire 2018 conference in Anaheim, California, to get an update on her company’s direction. Alteryx is a leader in self-service data analytics, one of the fastest growing software markets.

“Above the Trend Line” – Your Industry Rumor Central for 6/11/2018

Above the Trend Line: your industry rumor central is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items grouped by category such as people movements, funding news, financial results, industry alignments, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz.

Increasing Analytic Project Success

In this special guest feature, Erik Ottem, Director of Product Marketing, Data Center Systems at Western Digital, discusses how to build a better data lake, equipped with elements such as scaling measures, object storage adapters and ultimately enough performance to handle large analytic workloads.

Alteryx Reveals Newest Platform Release at Inspire 2018

Alteryx, Inc., revolutionizing business through data science and analytics, today announced the general availability of the newest version of the Alteryx platform. The release delivers new features across the platform to improve the analytic experience for IT, business analysts and data scientists, altering how they collaborate and scale analytics across the organization, find and connect to data, and ultimately drive business-changing insights.

Best of arXiv.org for AI, Machine Learning, and Deep Learning – May 2018

In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.

TOP 10 insideBIGDATA Articles for May 2018

In this continuing regular feature, we give all our valued readers a monthly heads-up for the top 10 most viewed articles appearing on insideBIGDATA. Over the past several months, we’ve heard from many of our followers that this feature will enable them to catch up with important news and features flowing across our many channels. We’re happy to oblige! We understand that busy big data professionals can’t check the site everyday.

Data Science 101: Handling Missing Data (Revisited)

I recently received the following question on data science methods from an avid reader of insideBIGDATA who hails from Taiwan. I think the topics are very relevant to many folks in our audience so I decided to run it here in our Data Science 101 channel. The issue of missing data is one most data scientists see quite frequently.

Deep Learning Course Student Launches Big Data Visualization Software Company

Richard Sheng is the co-founder of QuantumViz, a big data visualization software company that allows data scientists and analysts to find insights in massive data sets, and create amazing data stories in 3D, VR, or AR. Richard worked in data science previous to taking the Deep Learning course with NYC Data Science Academy but now works as the CEO and co-founder of QuantumViz, which was his final project of the course.

Data Science: A Business Lynchpin, Not an Experiment

In this special guest feature, co-founder and CEO of Domino Data Lab, discusses how too many organizations still view data science a technical skill, acquired simply by hiring a few data scientists. By doing so, they are not building the critical organizational muscle necessary to leverage predictive models as an enduring competitive advantage.

Best of arXiv.org for AI, Machine Learning, and Deep Learning – April 2018

In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.