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insideBIGDATA Latest News – 12/7/2020

In this regular column, we’ll bring you all the latest industry news centered around our main topics of focus: big data, data science, machine learning, AI, and deep learning. Our industry is constantly accelerating with new products and services being announced everyday. Fortunately, we’re in close touch with vendors from this vast ecosystem, so we’re in a unique position to inform you about all that’s new and exciting. Our massive industry database is growing all the time so stay tuned for the latest news items describing technology that may make you and your organization more competitive.

MLCommons Launches and Unites 50+ Global Technology and Academic Leaders in AI and Machine Learning to Accelerate Innovation in ML

MLCommons, an open engineering consortium, launched its industry-academic partnership to accelerate machine learning innovation and broaden access to this critical technology for the public good. The non-profit organization initially formed as MLPerf, now boasts a founding board that includes representatives from Alibaba, Facebook AI, Google, Intel, NVIDIA and Professor Vijay Janapa Reddi of Harvard University; and a broad range of more than 50 founding members. The founding membership includes over 15 startups and small companies that focus on semiconductors, systems, and software from across the globe, as well as researchers from universities like U.C. Berkeley, Stanford, and the University of Toronto.

MLCommons will advance development of, and access to, the latest AI and Machine Learning datasets and models, best practices, benchmarks and metrics. An intent is to enable access to machine learning solutions such as computer vision, natural language processing, and speech recognition by as many people, as fast as possible.

“MLCommons has a clear mission – accelerate Machine Learning innovation to ‘raise all boats’ and increase positive impact on society,” said Peter Mattson, President of MLCommons. “We are excited to build on MLPerf and extend its scope and already impressive impact, by bringing together our global partners across industry and academia to develop technologies that benefit everyone.”

OctoML Announces Early Access for Its Machine Learning Platform for Automated Model Optimization and Deployment

OctoML, the MLOps automation company for superior model performance, portability and productivity, announced early access to Octomizer. Octomizer brings the power and potential of Apache TVM, an open source deep learning compiler project that is becoming a de facto industry standard, to machine learning engineers challenged by model deployment timelines, inferencing and throughput performance issues or high inferencing cloud costs.

Industry analysts estimate that machine learning model costs will double from $50 billion in 2020 to more than $100 billion by 2024. Many machine learning models put into production today cost hundreds of thousands to millions of dollars to train, and training costs represent only a fraction of the ongoing inferencing costs that businesses take on to provide cutting-edge capabilities to their end users.

“In our early engagements with some of the world’s leading tech companies, they’ve been excited about our ability to provide unparalleled model performance improvement,” said Luis Ceze, OctoML co-founder and CEO. “Now we’re excited to open the Octomizer up for early access to a select set of customers and partners with similar model performance, inferencing cost savings or edge deployment needs.”

Comet ML Debuts Collaborative Workspaces for Data Science and MLOps Teams

 Comet ML, a leading provider of machine learning operations (MLOps) solutions that accelerate getting machine learning models into production, announced updates to Comet Workspaces, including the introduction of Interactive Reports, ML Templates and the industry’s first workflow for proactively considering carbon emissions as part of the machine learning process. Today’s updates further empower data scientists and teams to build better models faster, while ensuring that organizations can continue to operate in an environmentally responsible manner.

“While much has been said about the potential of AI and machine learning for business, a majority of that innovation hasn’t translated into value yet,” said Gideon Mendels, Co-founder and CEO, Comet. “The challenges range from lack of defined workflow and processes to inability to collaborate and share insights across teams. That’s why MLOps has arisen as a key concept—defining the people, processes and technologies that will drive wide-spread success with machine learning and AI at scale. But this must also be done responsibly, in a way that considers and addresses significant computing requirements and emissions.”

Mipsology Zebra on Xilinx FPGA Beats GPUs, ASICs for ML Inference Efficiency

Machine learning software innovator Mipsology announced that its Zebra AI inference accelerator achieved the highest efficiency based on the latest MLPerf inference benchmarking. Zebra on a Xilinx Alveo U250 accelerator card achieved more than 2x higher peak performance efficiency compared to all other commercial accelerators.

Efficiency of Computation (source: MLPerf and Internet data)

“We are very proud that our architecture proved to be the most efficient for computing neural networks out of all the existing solutions tested, and in ML Perf’s ‘closed’ category which has the highest requirements,” said Ludovic Larzul, CEO and founder, Mipsology. “We beat behemoths like NVIDIA, Google, AWS, and Alibaba, and extremely well-funded startups like Groq, without having to design a specific chip and by tapping the power of FPGA reprogrammable logic. Perhaps the industry needs to stop over-relying on only increasing peak TOPS. What is the point of huge, expensive silicon with 400+ TOPS if nobody can use the majority of it?”

Pricefx Reimagines Pricing Software with Important Product Enhancements

Pricefx, the global leader in cloud-native pricing software, announced the new face of its pricing platform. Unity UI is a sleek, dynamic new look for all of Pricefx’s industry-leading pricing modules. The company has also launched PriceOptimizer AI, a next-generation price optimization solution powered by transparent and predictive machine learning and multi-agent AI. Finally, Pricefx introduced new Accelerators, pre-defined solution building blocks that quickly and easily incorporate best practice functionality. With these new enhancements, Pricefx is now more streamlined, powerful and agile than ever before. Now, businesses using Pricefx can get more done and price more effectively with fewer clicks.

“2020 revealed the critical importance of pricing in a digital-first world and Pricefx invested heavily in developing and refining our pricing platform to ensure that businesses around the world can successfully use our software to build a path to growth,” said Marcin Cichon, CEO and co-founder at Pricefx. “From the new, modern user interface to the groundbreaking AI-powered price optimizer and the pre-built Accelerators, Pricefx is delivering impressive product functionality to the market. We continue to live our commitment to providing customers fast, flexible and friendly solutions that help them achieve revenue and profit goals faster than ever.”

Dgraph Labs Launches Slash Enterprise: Fully Hosted, Serverless Version of World’s Most Advanced Graph Database

Dgraph Labs, creators of the world’s most advanced graph database, announced the launch of Slash Enterprise, the first fully-managed, serverless solution for enterprises managing workloads with terabytes of data in production that can now run on dedicated, multi-zone clusters with high availability deployed on AWS, Azure, or GCP. Designed for mission-critical workloads at scale, and easily deployed to your cloud, Slash Enterprise can scale from zero to billions of records effortlessly with no single point of failure. 

“A native graph database is the only solution for developers who need iteration speed and flexibility within GraphQL,” said Dgraph Labs founder and CEO Manish Jain. “Slash Enterprise is what developers in the most demanding production environments need with that speed, scale and flexibility built in.”

Monte Carlo Releases Data Observability Platform to Unlock the Potential of the Modern Data Stack

Monte Carlo, the data observability company, announced the launch of the Monte Carlo Data Observability Platform, the first end-to-end solution to prevent broken data pipelines. Monte Carlo’s solution delivers the power of data observability, giving data engineering and analytics teams the ability to solve the costly problem of data downtime.

“The fastest thing that can destroy an executive’s trust in data is for it to be wrong — we make sure that doesn’t happen,” said Barr Moses, CEO and co-founder of Monte Carlo. “Over the last few years, businesses have moved from hoarding data to putting it to work for them. In my conversations with hundreds of data professionals I was struck by the fact that organizations were investing millions of dollars and strategic energy in data, but the people at the front lines couldn’t use it or didn’t trust it. With Monte Carlo’s Data Observability Platform, data teams can unlock the potential of their data and finally trust it to deliver value for their companies.”

GigaSpaces Drives Digital Transformation with the Launch of InsightEdge Portfolio, a New Suite of In-Memory Computing Platforms

GigaSpaces announced the InsightEdge portfolio, a new suite of in-memory computing platforms, designed to drive enterprise digital transformation with unparalleled speed, performance and scale. Combined with AIOps functionality, GigaSpaces delivers the easiest to deploy, and manage, portfolio of software platforms that meet the most challenging enterprise data and analytics processing needs. As more companies launch new digital services to thrive in today’s digital economy, they can drastically reduce time-to-market, ensure rapid application response times and the highest performance levels, with lower total-cost-of ownership.

“Enterprises are accelerating their digital transformation initiatives as they move to online services, migrate to the cloud, introduce operational BI, and launch new data-driven applications,” said Adi Paz, CEO at GigaSpaces. “Our new InsightEdge portfolio redefines in-memory computing by combining the required extreme performance speed and scale with the easiest to deploy and manage platforms across on-premise, cloud, hybrid and multi-cloud environments to support our customers’ needs – today, tomorrow and into the future.”

Broadcom Unveils the Industry’s First Open AIOps Platform Delivering a New Level of Full-Stack Observability for Hybrid Clouds

Broadcom Inc. (NASDAQ:AVGO) announced the availability of the latest generation of AIOps from Broadcom, an open platform with artificial intelligence, machine learning and end-to-end observability that helps organizations achieve operational excellence. AIOps allows business and IT leaders to manage critical KPIs that align IT outputs to business outcomes, driving digital agility, while proactively ensuring enhanced customer and positive employee experiences.

“Imagine a lens that provides a clear and fully integrated view of your business with IT providing valuable intelligence that drives informed decision-making. This is no longer a wish list, this is a reality for our customers through the new Broadcom AIOps solution,” said Serge Lucio, vice president and general manager, Enterprise Software Division, Broadcom. “AIOps from Broadcom provides enterprises with comprehensive observability across user experience, applications, infrastructure and networks delivering digital agility, actionable insights and intelligent automation— all enhancing business outcomes and customer experience.”

AWS Announces Five Industrial Machine Learning Services

Amazon Web Services, Inc. (AWS), an Amazon.com company (NASDAQ: AMZN), announced Amazon Monitron, Amazon Lookout for Equipment, the AWS Panorama Appliance, the AWS Panorama SDK, and Amazon Lookout for Vision. Together, these five new machine learning services help industrial and manufacturing customers embed intelligence in their production processes in order to improve operational efficiency, quality control, security, and workplace safety. The services combine sophisticated machine learning, sensor analysis, and computer vision capabilities to address common technical challenges faced by industrial customers, and represent the most comprehensive suite of cloud-to-edge industrial machine learning services available. This is why more than a hundred thousand customers are using AWS for machine learning, and why customers of all sizes and across all industries are using AWS services to make machine learning core to their business strategy. To learn more about AWS’s new industrial machine learning services, visit https://aws.amazon.com/industrial/.

Elastic Announces Innovations Across its Solutions to Optimize Search and Enhance Performance and Monitoring  Capabilities

Elastic (NYSE: ESTC) (“Elastic”), the company behind Elasticsearch and the Elastic Stack, announced new capabilities and updates across its Elastic Enterprise Search, Observability, and Security solutions that deliver powerful new features to reduce storage costs without compromising performance, proactively monitor and manage digital web experiences, and visualize data with drag-and-drop ease.

“These critical new capabilities illustrate Elastic’s ongoing commitment to helping customers adapt to new work environments at speed and scale,” said Kevin Kluge, SVP, Engineering, Elastic. “By helping them reduce storage costs without compromising performance, proactively monitor and manage digital web experiences, and rapidly visualize data, Elastic makes it possible for customers to accelerate their data to insights journeys faster than ever before.”

Lore IO Announces New Life Sciences Cloud Analytics Packages – Enables Emerging Pharma Organizations to Improve Data Management and Onboarding to Speed Drug Launch Readiness

Lore IO Inc., providers of an AI-powered common data model that enables faster vendor data onboarding and unified data views, announced the immediate availability of Lore IO Life Sciences Cloud Analytics Packages, a set of build-as-you-grow offerings that help pharmaceutical organizations shorten development cycles and speed drug readiness from clinical trials to product launch. Spanning Clinical Operations, Medical Affairs, Market Access, and Commercial Operations, each Lore IO Life Sciences Cloud Analytics solution provides a simple, flexible approach that ensures data is unified and accessible for business teams, providing them with unprecedented agility, so they are ready to act the moment drugs get fast tracked or when they receive breakthrough drug/orphan drug designation.

“The first commercialization of any drug launch can pose numerous complications that may prolong bringing a drug to market,” said Janardan Prasad, Head of Life Sciences at Lore IO. “Deployment resource shortages, long lead times, and high costs have prevented many emerging biopharma and diagnostics organizations from performing the data analysis needed to make informed decisions and expedite commercial success during each step of the drug development process. As a modular, end-to-end analytics platform, Lore IO Life Science Cloud Analytics solutions enable drug and device providers to easily onboard data and begin extracting value within weeks so they can significantly speed the commercialization of their product launch.”

Cartesiam Transforms Edge AI Development for Industrial IoT

Cartesiam, a company that creates artificial intelligence (AI) software for embedded systems, announced the availability of NanoEdge™ AI Studio V2, the first integrated development environment (IDE) that simplifies creation of machine learning, inference, and now classification libraries for direct implementation on Arm Cortex-M microcontrollers (MCUs). Thousands of commercially available industrial IoT (IIoT) embedded devices are already in production with NanoEdge AI Studio V1 for anomaly detection. With the addition of classification libraries to NanoEdge AI Studio V2, developers can now more easily go beyond anomaly detection to qualify problems directly in endpoints.

“Cartesiam makes tools for embedded developers, offering an intuitive push-button approach that requires no background in data science, opening AI to the billions of resource-constrained embedded devices built with Arm Cortex-M MCUs,” said Joël Rubino, CEO and co-founder, Cartesiam. “We initially designed NanoEdge AI Studio to meet demand from our customers in predictive maintenance, who, having accumulated data on the use of their equipment, asked us to help them easily qualify their events as well as to anticipate them. The new version of our IDE allows those customers — and any other embedded designer — to effortlessly develop a classification library without the usual challenges associated with signal processing and machine learning skills. This dramatically reduces costs and speeds time to market.”

Deci Collaborates with Intel to Achieve 11.8x Accelerated Inference Speed at MLPerf

Deci, the deep learning company building the next generation of AI, announced its inference results that were submitted to the open division of the MLPerf v0.7 inference benchmark (full results here). On several popular Intel CPUs, Deci’s AutoNAC (Automated Neural Architecture Construction) technology accelerated the inference speed of the well-known ResNet-50 neural network. It reduced the submitted models’ latency by a factor of up to 11.8x and increased throughput by up to 11x– all while preserving the model’s accuracy within 1%.

“Billions of dollars have been spent on building dedicated AI chips, some of which are focused on computer vision inference,” says Yonatan Geifman, CEO and co-founder of Deci. “At MLPerf we demonstrated that Deci’s AutoNAC algorithmic acceleration, together with Intel’s OpenVINO toolkit, enables the use of standard CPUs for deep learning inference at scale.”

Unbabel Launches COMET, Opening New Trail for Ultra-Accurate Machine Translation 

Unbabel, the AI-powered, human-refined translation platform that enables multilingual customer service at scale, announced the release of COMET (Crosslingual Optimized Metric for Evaluation of Translation), an open-source neural framework and metric for Machine Translation (MT) evaluation that has been validated as a top performing metric by the 2020 Fifth Conference on Machine Translation (WMT20). COMET reduces the need for human review, enabling rapid assessment and deployment of accurate machine translation models for the benefit of Unbabel’s customer service customers.

“We are launching COMET as an open-source, ready-to-use, trained model because it can greatly help drive and accelerate MT research and development to levels of accuracy not seen before. We believe that COMET should be adopted as a new standard measure for assessing the quality of MT systems across multiple languages,” said Alon Lavie, vice president of language technologies at Unbabel, co-creator of METEOR and consulting professor at Carnegie Mellon University. “Unbabel is deeply committed to maintaining its leadership in this space and removing the misconception that MT means low quality when it comes to translation.”

Oracle Announces Availability of New Integrated, High-performance Analytics Engine for MySQL Database Service

Oracle announced the availability of the Oracle MySQL Database Service with the MySQL Analytics Engine. The service is optimized for and exclusively available in Oracle Cloud Infrastructure (OCI). This is the only MySQL offering in the industry that provides database administrators and application developers with a single, unified platform for both Online Transaction Processing (OLTP) and Online Analytics Processing (OLAP) workloads – letting them build and run modern applications faster and more securely. The MySQL Analytics Engine, developed for the MySQL Database Service by the Oracle MySQL engineering team, is a new, in-memory analytic accelerator that scales to thousands of cores, supports real-time analytics, and is 2.7X faster and 1/3 the cost of AWS Redshift.

“MySQL is the most popular database among developers and is widely used by companies across industries. But, until today, MySQL users have been forced to move their data into separate incompatible data warehouses for analytics leading to higher costs and delayed answers,” said Edward Screven, chief corporate architect, Oracle. “With the MySQL engineering team’s latest innovations, Oracle is the only provider that offers developers and database administrators a single, unified platform that can easily run high performance real-time analytics against their MySQL database without requiring any change to their MySQL applications – making Oracle Cloud Infrastructure the best place to run MySQL applications.”

Iguazio Achieves AWS Outposts Ready Designation to Help Enterprises Accelerate AI Deployment in Hybrid Environments

Iguazio, the Data Science Platform built for production and real-time machine learning (ML) applications, announced that it has achieved the AWS Outposts Ready designation, part of the Amazon Web Services (AWS) Service Ready Program. This is a notable development for AWS and Iguazio customers who can utilize Amazon SageMaker to develop artificial intelligence (AI) models and data pipelines, and easily deploy and manage these in production using the Iguazio Data Science Platform on AWS and now also on AWS Outposts, benefiting from the same high performance at scale in hybrid AWS environments. 

“Our customers want flexible, high-performance solutions for operationalizing machine learning, solutions that abstract away infrastructure, and provide the same consistent experience across hybrid environments” said Asaf Somekh, Co-Founder and CEO of Iguazio. “The seamless integration with AWS Outposts enables us to provide our customers with an enhanced solution that is fully integrated within businesses’ AWS Outposts environments, allowing them to choose where their applications reside based on data security and business considerations, and not performance or ease of use.”

ScaleOut Software Announces the Availability of ScaleOut GeoServer® Pro

ScaleOut Software announced ScaleOut GeoServer® Pro, a new software product release that integrates site-to-site data replication with fully coherent data access for its battle-tested ScaleOut StateServer® in-memory data grid (IMDG) and distributed cache. This release extends the company’s ScaleOut GeoServer® DR product, which provides asynchronous, site-to-site data replication to protect against site-wide failures and currently is in production use.

“With the release of ScaleOut GeoServer Pro, we are excited to offer our customers breakthrough capabilities for multi-site storage of their fast-changing data,” said Dr. William L. Bain, founder and CEO of ScaleOut Software. “Now they can take advantage of our industry-leading technology that replicates data across sites to protect against data center failures while making fully coordinated use of the sites.”

Aerospike Adds Expressions to Next-Generation NoSQL Database 5

Aerospike Inc., a leader in next-generation, real-time NoSQL data solutions, unveiled Cross-Datacenter Replication (XDR) expressions in Aerospike Database 5. Earlier this year, Aerospike released Database 5 with enhanced Cross-Datacenter Replication (XDR), enabling data to be dynamically routed between two or more geographically distributed clusters. Now, with the addition of expressions to XDR, Aerospike Database 5 easily routes just the right data to the right target at the right time. The dynamic, fine-grain control of expressions optimizes server, cloud and bandwidth resources—and helps global organizations better comply with a wave of new privacy regulations.

“Modern decisioning applications require massive amounts of data at a moment’s notice. Far too often, organizations try to keep up by duplicating and moving huge amounts of data, increasing complexity and compliance risks—skyrocketing costs,” said Srini Srinivasan, chief product officer and founder, Aerospike. “Expressions in Aerospike Database 5 XDR delivers control without complexity, simplifying compliance and data requirements throughout the application stack.”

GE Digital’s Proficy Analytics Solutions Provide Plant Engineers with Machine Learning and Analytics for Closed-Loop Optimization

GE Digital announced the release of two new Proficy Analytics solutions, Proficy CSense 8.0 and Proficy Sensor Health. These unique software applications offer industrial companies a path to drive efficient operations, increase product quality, minimize downtime, and reduce risk related to compliance and safety.

“We have worked closely with many customers to create specific solutions to meet their analytics needs and drive digital transformation,” said Richard Kenedi, General Manager, Manufacturing and Digital Plant, GE Digital. “One of the things that we learned was that a lot of customers have challenges with sensors. Sensors can be the weakest link in the data chain.  A bad sensor means bad data, and bad data results, no alarm, and possibly a bad decision or missing a critical deviation.”

CLARA Analytics Unveils Its AI-Based Litigation Avoidance Solution for Commercial Auto 

CLARA Analytics (“CLARA”), a leading provider of artificial intelligence (AI) technology in the commercial insurance industry, announced that it has expanded its proven litigation product into the commercial auto line. CLARA Litigation for Commercial Auto applies revolutionary AI and machine learning techniques to identify claims at the risk of attorney involvement and litigation. This enables claims teams to proactively focus their efforts on mitigating the factors that cause claims to escalate. 

“CLARA Litigation for Commercial Auto is very exciting for us because it marks the first of many new products we’re developing for challenges that span various commercial lines of insurance,” said Gary Hagmueller, CEO of CLARA Analytics. “With CLARA Litigation, we’re delivering the sophisticated underlying technology that currently drives value in workers’ compensation to help our customers fix the important but underperforming commercial auto line.”

Corsight AI Launches Real-Time Facial Recognition Technology that Accurately Identifies Individuals at an Unmatched Speed Under Any Condition

Corsight AI, a leading facial recognition technology provider, announced the launch of its facial recognition technology. The technology is able to compliantly identify individuals on watchlists even under the most challenging conditions, overcoming common issues such as face coverings and harsh environments, at an unmatched speed and accuracy.

“In today’s unusual environment, there is no higher priority than protecting citizens around the world from harm,” said Rob Watts, CEO of Corsight. “We have developed a silver bullet with this technology, proving that facial recognition technology is a force for good. From helping identify dementia patients to protecting victims of domestic abuse, our technology, thanks to its speed and accuracy, can help change not only how organizations currently leverage facial recognition, but how society perceives it, too. We want to change the narrative surrounding the technology and help demonstrate how community-based deployment can be positive for all.”

Collibra Introduces Unparalleled Access to Trusted Data with Collibra Data Intelligence Cloud

Collibra, the Data Intelligence company, announced new enhancements to the Collibra Data Intelligence Cloud that improve access to critical data and solidify the company’s position as the system of engagement for global data teams. The updates are designed to help data citizens seamlessly find, access and understand data in more places – including Collibra Everywhere – in order to achieve meaningful business results.

“The Collibra Data Intelligence Cloud is a one-stop-shop that connects people with the data they need, when they need it,“ said Jim Cushman, chief product officer for Collibra. “Digital transformation is critical in today’s business environment, and these new enhancements to our unique, platform approach will make organizations more agile by streamlining processes and enabling improved collaboration.”

Teradata Launches New ‘DataDNA’ Data Forensics Tool

Teradata (NYSE: TDC), the cloud data analytics platform company, announced the availability of Teradata DataDNA – an automated service that produces data lineage and usage analytics. Using the power of Vantage, the company’s flagship hybrid multi-cloud data analytics software platform, DataDNA delivers transparency into an organization’s data assets and their utilization across the ecosystem, regardless of platform or technology, to ensure maximum analytic value is being derived throughout the enterprise. By giving businesses full insight into their data – including whether data is used, how it is used, and by whom – DataDNA enables customers to use data as their greatest asset, eliminating data redundancy, reducing cost, accelerating data integration, assisting in regulatory compliance, and increasing the return on investment.

“At Teradata, we have a deep understanding of analytic ecosystems and how data flows through an organization. That’s why we’re leveraging our expertise to help our customers better understand and manage their data assets across any platform,” said Niels Brandt, Vice President, Customer Success & Consulting at Teradata. “By automating data management, our customers will reduce their reliance on IT specialists for repetitive and low impact data management tasks; thereby releasing their productive time for increased collaboration, training and high-value services. And as more of our customers move to Vantage in the cloud, DataDNA provides insight to support ecosystem simplification and helps to identify data dependencies for accelerated migration plans and activities.”

Model N’s Fall 2020 Release for High Tech Offers Expanded AI/ML, Price Optimization and Channel Network Features

Model N, Inc.(NYSE: MODN), a leader in cloud revenue management solutions, announced new revenue management and channel performance capabilities as part of its Fall 2020 high tech product release, including expanded artificial intelligence (AI) and machine learning (ML) capabilities for deal optimization and channel intelligence.

“Our Fall 2020 product release is truly in sync with what is happening in high tech, supporting the industry by delivering next-generation features and functionality,” commented Suresh Kannan, Chief Product Officer at Model N. “Model N is one of the first revenue management providers to introduce and extend price optimization and AI/ML solutions for the complete revenue lifecycle.”

New Ataccama ONE Platform Consolidates All Data Management and Governance Functions into a Single AI-Infused Platform

Ataccama, a leading provider of self-driving data management and governance solutions, announced the second generation of its Ataccama ONE platform, which consolidates data quality, master data management, data catalog, data governance, data integration, and other data management capabilities into a single platform to maintain data integrity across organizations. Scheduled for general availability in February, the unified solution enables unparalleled automation through an AI-powered self-driving capability. It removes the limitations of monotonous, time-intensive tasks while providing improved agility that businesses require to drive innovation, enhanced trust and security to ensure data governance, and more flexibility in where data resides including support for cloud and on-premises environments.

“The rapid push for digital transformation in today’s new normal makes it clear that data is every organization’s most strategic asset, but data is only as useful as the way you manage it,” said Michal Klaus, CEO of Ataccama. “Today companies are burdened with dozens of single-purpose data management tools, crushed by the monotonous task of moving data from one to the next and exposed to increasing risks to data security and integrity at every step. With the second generation of Ataccama ONE, organizations have a single platform that streamlines the entire data management and governance lifecycle and uses AI to learn and automate repetitive functions and prevent mistakes. It’s time for enterprises to benefit from self-driving data management and governance and see what they can really do when risk is reduced and talent is liberated.”

Penguin Computing Unveils Innovative HPC, AI & Analytics, Cloud, and Data Solutions to Extend Customers’ Technical Reach

Penguin Computing, a subsidiary of SMART Global Holdings, Inc. (NASDAQ: SGH) and leader in high-performance computing (HPC), artificial intelligence (AI), and enterprise data center solutions, announced a series of new solutions and four technology practices to help customers modernize their enterprises with the power of emerging technologies and software-defined architectures for data-intensive, HPC, AI, and cloud-native applications.

“The rapid evolution of our market is creating new and valuable technologies at an ever increasing rate,” said Sid Mair, president of Penguin Computing.  “The solutions that we are launching today provide our customers the platform needed to effectively leverage these technologies to transform their technical computing infrastructure.”

Databricks Launches SQL Analytics to Enable Cloud Data Warehousing on Data Lakes

Databricks, the data and AI company, announced the launch of SQL Analytics, which for the first time enables data analysts to perform workloads previously meant only for a data warehouse on a data lake. This expands the traditional scope of the data lake from data science and machine learning to include all data workloads including Business Intelligence (BI) and SQL. Now, organizations can empower data teams across data engineering, data science, and data analytics to work on a single source of truth for data. SQL Analytics realizes Databricks’ vision for a lakehouse architecture that combines data warehousing performance with data lake economics, resulting in up to 9x better price/performance than traditional cloud data warehouses.

“It is no longer a matter of if organizations will move their data to the cloud, but when. A lakehouse architecture built on a data lake is the ideal data architecture for data-driven organizations and this launch gives our customers a far superior option when it comes to their data strategy,” said Ali Ghodsi, CEO and co-founder of Databricks. “We’ve worked with thousands of customers to understand where they want to take their data strategy, and the answer is overwhelmingly in favor of data lakes. The fact is that they have massive amounts of data in their data lakes and with SQL Analytics, they now can actually query that data by connecting directly to their BI tools like Tableau.” 

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