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Infographic: Big Data in 2018 (So Far)

Our friends over at Unravel Data put together an interesting infographic that makes strides in capturing the state-of-big-data in 2018 at this point in the year and showing how customers are deploying big data. Among many findings – Spark, Kafka, and TensorFlow are the hottest big data apps, while Pig, Cascading and Flume are not seeing much usage. Enjoy!

Visualization Best Practices for Business Analysts

In this contributed article, freelance human Avery Phillips discusses what you need to know about ensuring visualization is an asset and not a point of confusion for an organization. What visualization does is clarify what would often otherwise be complicated and murky given the way that large amounts of data can be hard to classify.

MathWorks Expands Deep Learning Capabilities in Release 2018b of the MATLAB and Simulink Product Families

MathWorks introduced Release 2018b of MATLAB and Simulink. The release contains significant enhancements for deep learning, along with new capabilities and bug fixes across the product families. The new Deep Learning Toolbox, which replaces Neural Network Toolbox, provides engineers and scientists with a framework for designing and implementing deep neural networks.

The 2018 State of Data Management

Profisee, a global leading modern data management technology company, released the results of its first annual data management report, “The 2018 State of Data Management.” The survey, conducted between January and April of 2018, aims to provide insights into data management, strategy, challenges, trends, benchmarks and ‘how others are doing it’. It is Profisee’s hope that data management professionals across the global data management community can use this information to help drive new initiatives.

DarwinAI Emerges from Stealth with Powerful Design, Optimization and Explainability Platform for Deep Learning

DarwinAI, a Waterloo, Canada startup creating next generation technologies for Artificial Intelligence development, announced it is emerging out of stealth with $3M in seed funding. The team’s Generative Synthesis platform leverages AI to reduce the complexity and guesswork in designing efficient, high performance deep neural networks for real world applications.

Google’s New Big Data View of Ethereum: What to Know

In this contributed article, technology writer and blogger Kayla Matthews discusses how Google wants to make all blockchain data associated with Ethereum easily accessible for people to study. It’s doing that by making all Ethereum data sets available through BigQuery, Google’s enterprise-level and highly scalable data warehouse geared towards data analysts.

Alegion Announces Next-Generation Training Data Platform for Enterprise AI Initiatives

Alegion, a training data platform for artificial intelligence (AI) and machine learning initiatives, announced the release of its next-generation platform with new features designed to enhance the quality and efficiency of large-scale machine learning initiatives and deliver model confidence for enterprise AI systems.

SAP Helps Business Users Make Fast, Confident Decisions with One Simple Cloud for All Analytics

SAP SE (NYSE: SAP) announced SAP Analytics Cloud is now available with new machine learning features to uncover correlations in an organization’s data and help users make faster, more confident decisions.

Pure Storage Introduces Data Hub Architecture

Pure Storage (NYSE: PSTG), the all-flash storage platform that helps innovators build a better world with data, introduced a data hub, the company’s vision to modernize storage architecture for unstructured, data-intensive workloads. Built on Pure Storage FlashBladeTM, Pure’s data hub is designed to be truly data centric and enable organizations to effectively utilize today’s most critical currency – data.

Ethics and the Pursuit of AI

In this contributed article, marketing specialist Sophie Ross discusses the center-stage question: What are the ethical implications of artificial intelligence and its applications? She suggests that there has to be a balanced approach to any technology. Humans should have ultimate control over the use, misuse and abuse of the technology so that the ultimate accountability can be fixed for any excesses.