Data science

insideBIGDATA Latest News – 8/31/2021

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.

Yugabyte Delivers Industry-First Smart Client Driver for Distributed SQL Database with YugabyteDB 2.9 Release

Yugabyte, the company behind the leading distributed SQL database, announced the general availability of YugabyteDB 2.9. This latest release delivers the industry’s first smart JDBC client driver with an understanding of the distributed architecture of a YugabyteDB cluster. The Yugabyte Smart Driver for SQL pushes the state of SQL forward, allowing applications to get better performance and fault tolerance by connecting to any node in a distributed SQL database cluster without the need for an external load balancer. The client driver is available as open source software under the Apache 2.0 license.

“Cloud native transactional applications need databases that deliver high availability and scale without sacrificing relational database features,” said Karthik Ranganathan, co-founder and CTO, Yugabyte. “Homegrown solutions address this need by replicating data across nodes and deploying one or more load balancers to connect to the nodes. This approach results in complex and brittle applications that are hard to run in production. Yugabyte is on a mission to simplify this. We are proud to be pushing the boundary of relational databases for a cloud native world with innovations like our distributed SQL database and the Yugabyte Smart Driver for SQL.”

The Cognigy Insights analytics suite will enhance the capabilities of the Cognigy.AI platform to make sense of conversational data and facilitate data-driven optimization

Cognigy is pleased to announce the launch of Cognigy Insights, a powerful analytics suite integrated with the Cognigy.AI platform to help enterprises make sense of their conversational data, and give them the means to act upon insights, all within one best-in-class suite.

“Better Conversational AI analytics is one of the key demands to improve customer communication as enterprises optimize their customer journey,” says Sebastian Glock, Senior Technology Evangelist, Cognigy. “Cognigy Insights helps customers make sense of their conversational data and give them the means to act upon insights, all within one best-in-class suite.”

Skai Launches Ask MI, an Intuitive, Search-Based Market Intelligence Solution

Skai, a leading commerce intelligence platform, announced the launch of Ask MI (pronounced “ask me”), an AI-powered, search-based, self-serve market intelligence solution that puts AI-powered consumer and market insights into the hands of everyone. Using natural language, users can type any word, phrase, or question into Ask MI’s intuitive search bar to access easily understood, interactive dashboards that provide powerful insights about the consumers, brands, products, competitors, and innovation within their category. 

“The goal of Ask MI was to use a familiar interface—the ask-and-answer, natural-language search bar—as a portal to transformative, proprietary insights. Whether it’s marketing, sales, product development or other areas, the brands we serve are led by people who need to make fast, informed decisions,” says Kate DuBois, General Manager of Marketing Intelligence at Skai. “Ask MI removes the barriers to leveraging data, empowering all employees to address business problems based on the same source of truth as their teams of analysts. It shortens time to insight and ultimately maximizes return from the organization’s data investment.”

HVR Launches HVR 6.0, Helps Organizations More Readily Adopt DataOps Strategies with Data Democratization

HVR, a leading independent provider of real-time cloud data replication technology, announced HVR 6.0, a scalable and reliable data replication solution that provides the most efficient way to integrate large data volumes in complex environments. With new features and enhanced capabilities, as well as a completely reimagined user interface, HVR 6.0 enables simplified data integration deployments and modern manageability, helping organizations more readily adopt DataOps strategies to fully harness the power of their data.

“Enterprises understand the importance of DataOps and the role it plays in simplifying access to cross-organization operational data. Lack of easy, secure access has been a roadblock for countless data strategies. That roadblock has now been removed,” said Joe deBuzna, VP of products at HVR. “With workflow automation, point-and-click design, built-in security and user-based access control (UBAC), HVR 6.0 is a modern data replication solution that offers a step toward the data democratization organizations need to kickstart their DataOps initiatives and help achieve their data-driven business goals.”

Virtana Integrates with Infinidat to Offer Infrastructure Performance Management (IPM) Solution for Enterprises and Service Providers

Virtana, the AIOps observability company for hybrid cloud, and Infinidat, a leading provider of enterprise-class storage solutions, announced the integration of Virtana VirtualWisdom and Infinidat InfiniBox® to offer comprehensive Infrastructure Performance Management (IPM) tailor-made for large enterprises and service providers. The integration provides deep, cross-domain visibility into mission-critical application workloads that run on InfiniBox storage, while extending Virtana’s industry-leading IPM solution to a broader range of customer environments. It ensures uptime, availability, and performance, combined with advanced capacity forecasting.

“IT leaders are in a perpetual hunt for improved uptime, availability, and performance of critical applications,” commented Jon Cyr, VP of Product Management at Virtana. “Any downtime or miscue at the enterprise level can put customers and millions of dollars at risk. Infinidat’s game-changing innovation in the storage industry and their organic growth in cloud solutions makes them a great partner. Their advanced storage services and flexible, ‘on-demand’ consumption model will help us mutually deliver exactly what customers are asking for, across both private, on-prem and public cloud-based environments, pushing the storage industry to evolve to meet the new challenges of a truly hybrid-cloud world.”

Worthix Unveils Advanced, AI-Based Customer Insight Capabilities With Worthix 2.0 Platform™

Worthix, the conversation-based AI technology tool for customer decision intelligence able to power one-on-one conversations with customers in any language and at any scale, announced the availability of Worthix 2.0, a new platform with advanced features – including the Worthix Decision Lab – that enables companies to identify the elements of an experience, external influences and mechanisms, such as social proof, to pinpoint the exact moment and reason behind a purchase decision.

“With global markets undergoing change at a pace unprecedented even a year ago, companies have never had a greater need for dependable data on what’s really driving their customers’ purchases, and corresponding insights around the most business-critical actions to take and when in order to stay competitive,” said Guilherme Cerqueira, CEO and Co-founder, Worthix. “The new capabilities we’re delivering with the Worthix 2.0 Platform will allow companies to reach a new level of engagement with their customers and identify what elements of the customer experience make the greatest impact. Aligning their investment priorities to customers’ needs will help companies reach higher levels of overall business success.”

Lytics Releases Lytics Cloud Connect to Add Reverse ETL Capabilities to Their Industry Leading Customer Data Platform

Lytics, a leading customer data platform, announced the release of a new product called Lytics Cloud Connect, a reverse ETL (extract, transform, load) extension to its existing CDP lineup. Cloud Connect allows IT departments, data analysts, and developers to run SQL queries directly against their data warehouse as segment definitions, no need for ingesting or moving data around. These segments can then be activated in all key marketing channels with just a click or two through Lytics’ robust and proven network of integrations. The result is an enhanced customer experience, improved security and faster time-to-value.

“Cloud Connect is an important step forward in accelerating those who work with consumer data and drive brand marketing and ad buys, to move toward first-party behavioral data collection,” said James McDermott, CEO and Cofounder, Lytics. Cloud Connect makes it very easy for Lytics customers to connect the customer data in their warehouses like Google Cloud Platform or Snowflake, more directly to action systems like Salesforce, Zendesk and hundreds of others. People need to start thinking about the CDP as a suite of tools that allows developers to query the data warehouse and combine those results with real-time behavioral insights with decisioning, to better engage users with relevant and personal experiences.”

Analytics IQ Launches Data Shop on Narrative’s Data Streaming Platform

AnalyticsIQ, a leading predictive analytics innovator and marketing data creator, announced the launch of their new e-commerce store for audience data. The store is built with Narrative’s new Data Shops offering, which enables companies to effortlessly spin up a branded data shop that lets data users easily find, purchase, and leverage a variety of proprietary data assets via a familiar e-commerce experience.

“The team at AnalyticsIQ is excited to expand our partnership with Narrative with the launch of our Data Shop,” said Dave Kelly, AnalyticsIQ CEO. “Narrative’s mission of securely and effectively connecting data users with diverse, quality data sources is one we are proud to be a part of and believe Narrative’s suite of Data Shops furthers that mission.”

IBM Unveils On-Chip Accelerated Artificial Intelligence Processor

IBM (NYSE: IBM) unveiled details of the upcoming new IBM Telum Processor, designed to bring deep learning inference to enterprise workloads to help address fraud in real-time. Telum is IBM’s first processor that contains on-chip acceleration for AI inferencing while a transaction is taking place. Three years in development, the breakthrough of this new on-chip hardware acceleration is designed to help customers achieve business insights at scale across banking, finance, trading, insurance applications and customer interactions. A Telum-based system is planned for the first half of 2022.

New Aerospike Petabyte Scale Benchmark Runs Real-Time Operational Workloads on Just 20 AWS Nodes with Intel Processors

Aerospike Inc. unveiled the results of a petabyte-scale benchmark that illustrates its Real-time Data Platform delivering 4 million to 5 million transactions per second (TPS) with sub-millisecond latencies for read-only and mixed workloads on a remarkably small 20-node Amazon Web Services (AWS) cluster fueled by Intel® Xeon Scalable Processors. Achieved in collaboration with AWS and Intel®, the benchmark shows that even with significant data growth and extreme workloads, the Aerospike Database performs with hundreds of nodes less than other databases, saving up to $10M per application in infrastructure costs.

“With Aerospike, real-time petabyte-scale processing can be effective and affordable for enterprises of any size, not only those with billions in annual revenues,” said Srini Srinivasan, chief product officer and founder, Aerospike. “Selecting Aerospike’s real-time data platform early in a company’s growth cycle not only helps them grow faster, but also eliminates expensive and time-consuming rip-and-replace of databases that fail to scale up to meet ever-growing demands.”

AWS Announces General Availability of Amazon MemoryDB for Redis

Amazon Web Services, Inc. (AWS), an Amazon.com, Inc. company (NASDAQ: AMZN), announced the general availability ofAmazon MemoryDB for Redis, a fully managed, Redis-compatible, in-memory database. Amazon MemoryDB for Redis enables customers to achieve ultra-fast performance with high availability and durability for their most business-critical applications that require sub-millisecond response times. With Amazon MemoryDB for Redis, customers can use the same familiar and flexible Redis data structures and application programming interface (API) they use today without having to separately manage a cache and a durable database, or the required underlying infrastructure. There are no up-front commitments or fees to use Amazon MemoryDB for Redis, and customers pay only for the database capacity used. To get started with Amazon MemoryDB for Redis, visit: https://aws.amazon.com/memorydb.

“More and more customers have told us they need an easier way to build modern applications with microservices, which demand both extreme performance and durability,” said Raju Gulabani, VP of databases and analytics, AWS. “With Amazon MemoryDB for Redis, customers can now simplify their architecture with a durable and ultra-fast in-memory database, free from the hassle of managing a separate cache, database, and the underlying infrastructure, to quickly and easily build and scale applications that require real-time interactivity and reinvent customer experiences.”

Starburst announces new product release including up to 10X performance improvements for Parquet files and Delta Lake tables

Starburst, the analytics anywhere company, announced the availability of the latest version of Starburst Enterprise. The new release provides Starburst customers with net new capabilities alongside more advanced connectivity, improved performance, and more security features. Among the new capabilities, Starburst Cached Views expands the concept of traditional materialized views to be applied to the data mesh. Starburst Cached Views allows domain experts to easily enrich, transform and move data according to their needs. 

“Achieving a successful data mesh architecture requires the ability to access data in disparate systems and sources. Starburst Cached Views enables users to query data from other systems, and transparently cache that data in their own domain for increased performance,” said Matt Fuller, VP, Product and co-founder of Starburst Data. “This can provide significant performance advantages by precalculating complex queries and joins and caching closer to consumers. It can also significantly reduce data egress costs and enable domain experts to create a performant semantic layer.” 

Latest Release of the SnapLogic Platform Empowers IT and Business Teams to Realize the Vision of Self-service Integration and Automation

SnapLogic, provider of the Intelligent Integration Platform, announced its August 2021 product release, featuring new  capabilities that make it faster and easier for IT and business users to unlock the power of self-service integration and automation throughout their organization. Introduced in this release is SnapLogic Flows, a modern, intuitive user experience for non-technical business users, enabling them to develop application integrations and automate data flows in a self-service manner, without the use of code. The release also features new API lifecycle management updates and an enhanced API developer portal, a new ‘zero downtime upgrade’ to minimize any disruption for customers during release updates, and extended ELT support for Databricks’ Delta Lake.

“We’ve packed a number of important new and enhanced features into the August release of the SnapLogic platform,” said Craig Stewart, CTO at SnapLogic. “With the introduction of SnapLogic Flows, we’re adding to our family of purpose-built, easy-to-use interfaces to help non-technical business users realize the vision of self-service, enterprise-wide automation. In addition, our new zero downtime commitment to customers as well as our expanded API management and ELT capabilities enable business and IT groups to work together on a single, powerful platform to drive productivity, collaboration, and results.”

Pepperdata Introduces Observability and Optimization for GPUs Running Big Data Apps

Pepperdata, a leader in big data performance management, announced that the Pepperdata product portfolio now includes the ability to monitor Graphics Processing Units (GPUs) running big data applications like Spark on Kubernetes. Workloads that harness tremendous amounts of data, such as machine learning (ML) and artificial intelligence (AI) applications, require GPUs, which were originally designed to accelerate graphics rendering. That extra processing power comes with a high price tag, and it requires near constant monitoring for resource waste to get the best performance at the lowest possible cost. Pepperdata now monitors GPU performance, providing the visibility needed for Spark applications running on Kubernetes and utilizing the processing power of GPUs. With this new visibility, companies can improve the performance of their Spark apps running on those GPUs and manage costs at a granular level. 

“Spark on Kubernetes is quickly becoming a dominant part of the compute infrastructure as data-intensive ML and AI applications proliferate,” said Ash Munshi, CEO, Pepperdata. “GPUs can handle these workloads, but they are expensive to buy and are power-intensive. Until now, there hasn’t been a way to view and manage the infrastructure and applications, which can lead to unnecessary waste and overspending for big data workloads. With Pepperdata, organizations can properly size their GPU hardware investments and have the confidence that they are utilizing them well.” 

Rockset Releases Rollups for Up To 100X More Cost-Effective Real-Time Analytics on Streaming Data

Rockset, the real-time analytics company, unveiled a major product release that makes real-time analytics on streaming data from sources like Apache Kafka, Amazon Kinesis, Amazon DynamoDB, and data lakes a lot more accessible and affordable for every enterprise. With this launch, customers can use standard SQL to perform real-time data transformations and pre-aggregations continuously as new data is ingested from any source — a game-changing new feature that represents an industry-first in the analytics database landscape. This significantly reduces engineering effort on real-time data pipelines, while cutting both storage and compute costs for real-time analytics at cloud scale. As a result, any developer can build real-time, interactive dashboards and data-intensive applications on massive data streams in record time, at a fraction of the cost.

“Your modern cloud data stack is incomplete without a real-time database purpose-built for ingesting, transforming, and analyzing streaming data. Warehouses simply don’t cut it — they are built for batch analytics and become prohibitively slow and expensive for high volume streaming data,” said Venkat Venkataramani, CEO and co-founder at Rockset. “Transforming massive torrents of raw data streams to accurate high-quality aggregates is essential for achieving real-time analytics at cloud scale. With this release, Rockset makes building massively scalable real-time aggregations as simple as writing a simple SQL query, and a lot more budget-friendly.”

Cloudera Introduces Cloudera DataFlow for the Public Cloud

Cloudera, (NYSE: CLDR), the enterprise data cloud company, announced the launch of Cloudera DataFlow for the Public Cloud, a cloud-native service for data flows to process hybrid streaming workloads on the Cloudera Data Platform (CDP). With Cloudera DataFlow for the Public Cloud, users can now automate complex data flow operations, boost the operational efficiency of streaming data flows with auto-scaling capabilities, and cut down on cloud costs by eliminating infrastructure sizing guesswork.

“Cloudera DataFlow automates and manages cloud-native data flows on Kubernetes – and it is something only we offer,” said Dinesh Chandrasekhar, Head of Product Marketing, Data-in-Motion at Cloudera. “Now it is easy for our customers to boost the operational efficiency of their streaming workloads and save on infrastructure costs in the public cloud.”

Alternative Data Firm, M Science, Launches Critical Retail Intelligence Data Tool

M Science, pioneer in data-driven research and analytics, announced the launch of their Retail and Consumer Brands Intelligence Platform. This new platform provides business-critical insights to the industry as it navigates post-COVID-19 consumer behavior and as the ecommerce landscape continues to rapidly evolve. Leveraging tested analytic models and a myriad of data inputs, this new solution delivers insights to more than a dozen industries including Animals & Pet Supplies, Apparel, Garden & Home, Sporting Goods and Toys & Games. The platform’s focus on ecommerce insights makes it a valuable tool for traditional retailers and brands as well as DTC and online-only players.

“With access to M Science’s intelligence, clients will gain insights that are traditionally very difficult to determine – such as specific item-level consumer preferences and market share among competitors,” noted Elizabeth Coleman, Head of Product at M Science. “This information will be more valuable than ever, answering key questions about how the pandemic has altered shopping habits. Our solution can provide guidance around product sales and category performance, which customers to target and when, and trends that are winning in the marketplace.” 

RTB House Releases Update to its Deep Learning AI Engine, Delivers a Full-Funnel View of Consumer Behavior

RTB House, a global company that provides state-of-the-art marketing solutions for top brands worldwide, announced an update to its Deep Learning AI Engine, enabling brands to have a full-funnel, actionable view of consumers throughout their path-to-purchase — increasingly important in a cookieless world. RTB House’s full-funnel solution, a core focus of the recent engine updates, is able to recognize a consumers’ stage within the sales funnel in real-time, resulting in more relevant communication with customers and prospects. Leveraging the RTB House Deep Learning AI Engine, brand marketers are empowered to build more durable brand awareness and deeper connections and engagement at every stage of the consumer’s path-to-purchase.

“This past year has seen explosive growth in eCommerce, and as such, our customers are increasingly looking for full-funnel solutions – to understand consumer behavior and reach audiences appropriately no matter what stage in the buying journey they are in,” said Gary Burtka, VP of US operations at RTB House. “We help brands determine where consumers are within the funnel, what segment they fall into, what ads are best to show each segment, and what products will resonate the best with each consumer. The updates to our Deep Learning AI Engine over this past year have been substantial in offering our customers additional value with proven results that exceed their expectations.”

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