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2016 Was a Big Year for Big Data

In this contributed article, tech writer Linda Gimmeson takes a short look back to 2016 to highlight a shortlist of ways that Big Data has made a significant impact in today’s society.

4 Pros and Cons of the Medical IoT

In this contributed article, technology writer and blogger Kayla Matthews provides 4 pros and cons of the medical IoT. IoT has the potential to change the medical industry from the ground up, though time has not yet determined if that change is going to be a positive or negative one.

BlueData Brings DevOps Agility to Data Science Operations with Spark, R, and Python

BlueData, provider of a leading Big-Data-as-a-Service (BDaaS) software platform, announced the new winter release for the BlueData EPIC software platform. This new release delivers several new enhancements for data science operations, bringing DevOps agility and collaboration to data science teams as well as support for new machine learning use cases.

Interview: Paulo Sampaio, Data Scientist at EDITED

I recently caught up with Paulo Sampaio, Data Scientist at EDITED, to talk about applying machine learning, neural networks, natural language processing, and big data analytics to the retail industry. Paulo and his team are applying neural networks, machine learning and other models to analyze over 520 million products in real-time across 42 countries to make gradual distinctions in clothing styles, sizes and categories.

Are You Prepared for the Data Discovery Requirements to Meet EU’s New Costly GDPR Privacy Requirements?

In this contributed article, Stuart Tarmy and Aarthi Sivasankaran of ROKITT focuses on the global reach of GDPR. GDPR has impact on many other areas such as personal data scope, customer consents, disclosure, new rights, accountability, data protection organization, data security, 3rd party processing, etc.

Cazena Announces New Data Science Sandbox as a Service

Cazena unveiled its Data Science Sandbox as a Service. The service is designed to deliver significantly faster outcomes from data science and analytics programs. Now, data scientists can run a wide range of analytics in a flexible cloud environment without having to build, manage or maintain the underlying technology.

The Downside of Converting Full-Text PDFs to XML for Text Mining

To get the best results from text mining projects, researchers need access to full-text articles. However, when researchers obtain full-text articles through company subscriptions or document delivery, the documents are often provided as PDFs, a suboptimal format for use with text mining software. The burden is then on researchers to convert the PDFs to XML. But that can be inefficient and costly. Read on as Michael Iarrobino, Product Manager at Copyright Clearance Center, explains the pitfalls of converting full-text PDFs to XML for text mining.

IoT: From the Lens of the Enterprise

In this contributed article, Don DeLoach, CEO and President of Infobright, examines the three different types of vendors that have emerged within an IoT-centric landscape.

data.world Secures Nearly $19 Million in Venture Capital Funding

data.world, the social network for data people, today announced it has closed $18.7 million in venture capital funding at double the valuation of its previous round. This second round brings the total amount of capital raised to $32.7 million and places data.world among the technology sector’s top-5 venture-backed Certified B Corporations of all time. The new capital will be used to fund rapid progress toward the company’s mission to build the most meaningful, collaborative, and abundant data resource in the world.

Bigger is Better: Why Enterprise Analytics Needs Scale

In this special guest feature, Andrew Pease, Principal Business Solutions Manager at SAS, discusses why enterprise analytics must incorporate scale and its relation to speed and innovation within an organization.