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The insideBIGDATA IMPACT 50 List for Q4 2019

The team here at insideBIGDATA is deeply entrenched in following the big data ecosystem of companies from around the globe. We’re in close contact with most of the firms making waves in the technology areas of big data, data science, machine learning, AI and deep learning. Our in-box is filled each day with new announcements, commentaries, and insights about what’s driving the success of our industry so we’re in a unique position to publish our quarterly IMPACT 50 List of the most important movers and shakers in our industry. These companies have proven their relevance by the way they’re impacting the enterprise through leading edge products and services. We’re happy to publish this evolving list of the industry’s most impactful companies!

ActiveViam Launches its Data Lab to Help Companies Find Insights into their Future

ActiveViam, a leader of in-memory analytics solutions for operational decision making, announced the creation, within the company, of a new entity specialized in Data Science. This Data Lab, attached to the R&D department of ActiveViam Paris, is dedicated to enhancing the forecasting capacity of its customers and prospects by providing them with richer insights into their markets, operations and customers.

“Above the Trend Line” – Your Industry Rumor Central for 10/7/2019

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 M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz.

Why Data Annotation is the Secret to Hacking AI

In this special guest feature, Michael Goldberg, VP of Marketing at Innodata (NASDAQ: INOD), indicates that even the most technically advanced algorithm cannot address or solve a problem without the right data. We know having access to data is quite valuable, but having access to data with a learnable ‘signal’ consistently added at a massive scale is the biggest competitive advantage nowadays. That’s the power of data annotation.

Quilt Data Launches, Introduces Visual Index to Amazon’s Public Data

Quilt Data, where the world’s data comes together, launched and announced an index to Amazon’s public cloud data (open.quiltdata.com), enabling organizations globally to discover and share petabytes of data. The world’s cloud data is already larger than the world wide web and projected to expand 100 times over in the next five years. For the first time, Quilt enables anyone to search, understand and explore this vast universe of data with a standard web browser.

Best of arXiv.org for AI, Machine Learning, and Deep Learning – August 2019

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.

Lucidworks Fusion 5.0 Features Data Science Toolkit Integration and Microservices Architecture Orchestrated by Kubernetes

Lucidworks, a leader in AI-powered search, announced the release of Fusion 5.0, the latest version of the company’s flagship product. Lucidworks Fusion 5.0 lets customers rapidly develop and deploy AI-powered search and data discovery applications in a modern, Kubernetes-based containerized architecture. This update includes features that simplify implementation for data science teams and developers to create both a more personalized experience for digital commerce customers and also improve employee productivity and engagement in the digital workplace.

No degree? No Problem: US Employers Shifting Hiring Mentality for Data Skills

Job seekers owning demonstrable experience with data might soon overtake those with data science degrees when it comes to the candidates global enterprises are seeking, according to a major survey of global business decision makers commissioned by data and analytics firm Qlik, on behalf of the Data Literacy Project.

Models for Thinking: An Example of Why Data Sciences Increasingly Need the Humanities

Parsing such large-scale data sets – classifying genomic sequences, mapping forms of advertisement, observing online discussions, etc. – is a matter of organization: How do you make sense of, and classify, these clusters of information? The answer, often, is to configure them into abstract but coherent topics.

Interview: KDD2019 Co-General Chairs Ankur Teredesai & Vipin Kumar

During my trip to KDD2019 in August, I had the pleasure of sitting down to chat with the co-chairs of the conference, Ankur Teredesai and Vipin Kumar. In the interview that follows, we discuss the growth of the KDD conference over the years, and also it’s changing focus. KDD is touted as being “the premier interdisciplinary conference bringing together researchers and practitioners from data science, data mining, knowledge discovery, large-scale data analytics, and big data.”