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Five Reasons Why Your Data Science Project Could Fail – And What You Can Do to Avoid It

In this special guest feature, Afrozy Ara, Head of Data Science practice at Incedo, suggests that given the difficulty in running a successful data science project, there are some specific reasons why these kinds of projects fail.

Book Review: Python Data Science Handbook

I recently had a need for a Python language resource to supplement a series of courses on Deep Learning I was evaluating that depended on this widely used language. As a long-time data science practitioner, my language of choice has been R, so I relished the opportunity to dig into Python to see first hand how the other side of the data science world did machine learning. The book I settled on was “Python Data Science Handbook: Essential Tools for Working with Data” by Jake VanderPlas.

The Role of the Modern Data Scientist — And How Everyone Has the Power to Become One

In this contributed article, Arijit Sengupta, Head of Einstein Discovery at Salesforce, explains – given the role of the modern data scientist, everyone has the power to become one. We aren’t that far off from a future when everyone will have the tools to be considered a citizen data scientist.

Probing the Wisdom of Apple, Inc., Crowds Using Alternative Data Sources

In this contributed article, Anasse Bari, clinical assistant professor of computer science at New York University, and software engineer Lihao Liu, provide a detailed look at the competitive analysis they performed for four major smartphone contenders: iPhone X and 8, Samsung Galaxy Note 8, Nokia 8 and Google Pixel 2 using alternative data sources.

DialogTech Helps Businesses that Value Phone Calls Drive Growth with AI and Predictive Analytics

DialogTech, a leading provider of actionable marketing analytics for phone calls, announced the addition of a new team of data scientists to help businesses that value phone calls unlock the full power of artificial intelligence to drive growth.

IBM Unveils a New High-Powered Analytics System for Fast Access to Data Science

IBM (NYSE: IBM) announced the Integrated Analytics System, a new unified data system designed to give users fast, easy access to advanced data science capabilities and the ability to work with their data across private, public or hybrid cloud environments.

Domino Data Lab Accelerates Model Delivery on AWS

Today Domino Data Lab announced general availability of its Domino Model Delivery product. Built to run natively on Amazon Web Services (AWS), this offering makes the process of deploying highly scalable production models faster and more cost effective.

GigaSpaces Empowers Real-Time Data-Driven Organizations with New Insights Platform

GigaSpaces, a leading provider of in-memory computing (IMC) platforms, announced the next-generation of its in-memory computing platform, unifying the company’s flagship in-memory data grid, XAP, with its open-source data science and analytics product, InsightEdge.

2017 Data Connectivity Outlook

Our friends over at Progress revealed some new findings from their 2017 Data Connectivity Outlook global survey. In the 4th annual survey based on responses from 1,200 business and IT professionals around the world, the results validate the explosive growth seen in SaaS data sources and the common challenges faced when trying to connect to data in a hybrid environment.

‘Learning Database’ Speeds Queries from Hours to Seconds

University of Michigan researchers developed software called Verdict that enables existing databases to learn from each query a user submits, finding accurate answers without trawling through the same data again and again. Verdict allows databases to deliver answers more than 200 times faster while maintaining 99 percent accuracy. In a research environment, that could mean getting answers in seconds instead of hours or days.