insideBIGDATA Latest News – 9/1/2022

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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.

Speechmatics launches Language Identification, allowing users to automatically determine the predominant language in a media file  

Speechmatics, a leading autonomous speech recognition technology scaleup has now added Language Identification (Language ID) to its industry leading speech-to-text engine. This latest addition allows customers to automatically identify the predominant language spoken in any media file. Customers will save time and effort on manually reviewing files, safe in the knowledge that they will be provided with an accurate transcription of any media file. 

“Up until now, identifying languages without human intervention has been costly and time consuming for users of speech-to-text,” said Language ID, CEO Katy Wigdahl. “However, with our new Language ID, this will be a thing of the past and allow customers to swiftly identify and transcribe media files – with less hassle and more efficiency. We can’t wait for our customers to use this Language ID and see it deliver accurate and valuable results.’’  

New Observe.AI Reporting & Analytics Drives High-Impact Business Decisions for Contact Centers 

Observe.AI, the robust conversation intelligence platform for boosting contact center performance, announced the launch of Reporting & Analytics – designed to help contact center leaders accelerate the activation of meaningful insights that improve business performance and outcomes. Using the industry’s highest-accuracy conversation intelligence engine, Observe.AI Reporting & Analytics provides business leaders with an integrated, holistic view of contact center performance. It delivers interactive data exploration and visualization with up-to-the-minute insights across key dimensions – including positive and negative customer experience drivers, customer sentiment, agent performance, coaching and revenue opportunities, and compliance.

“When it comes to activating contact center conversation intelligence, Observe.AI stands apart in two key areas. Firstly, the unparalleled accuracy and integrity of our interaction data, which represents a goldmine of customer experience insights. Secondly, we propel contact centers to apply this intelligence faster, with powerful automation to drive positive agent behavioral change at speed and scale,” said Swapnil Jain, CEO and Co-Founder of Observe.AI. 

Teradata Announces VantageCloud Lake for Driving Analytical Innovation at Scale 

Teradata (NYSE: TDC) announced VantageCloud Lake, Teradata’s first product built on an all-new, next-generation cloud-native architecture. Based on the deep history and expertise of Teradata, VantageCloud Lake brings the proven power of Teradata Vantage, now called VantageCloud Enterprise, to a new offering that is born in the cloud – automatically elastic and built to leverage low-cost object store at its core, but still powerful and easy to use and scale (or stop). 

“VantageCloud Lake is the result of a multi-year journey to create a new paradigm for data and analytics – one where superior performance, agility, and value all go hand-in-hand,” said Hillary Ashton, Chief Product Officer at Teradata. “VantageCloud Enterprise – our established Vantage in the cloud offering – is the recognized price performance leader in the market. VantageCloud Lake offers all of those same benefits in a package that is appealing to diverse functions and roles, opening up an entirely new market segment for Teradata. We now support all analytic workload needs at every level in the organization, enabling companies to be more nimble, experimental, and innovative in an easy to use solution without losing the governance and cost visibility that Teradata is known for.” 

Teradata Announces ClearScape Analytics: The Most Powerful, Open, and Connected Cloud Analytics Available in the Industry  

Teradata (NYSE: TDC) announced ClearScape Analytics, the significantly expanded and newly named analytics capabilities that span the entire suite of Vantage products. Teradata Vantage’s industry-leading analytics have long been the cornerstone of the platform’s appeal to enterprise customers for its ability to accelerate data insights and time to value. With these new capabilities, Vantage customers can now take advantage of the most in-database analytic functions anywhere in the market and best-of-breed artificial intelligence/machine learning (AI/ML) model management tools to meet the growing analytic demands of their organizations. 

These newly released features elevate Teradata’s analytics capabilities even further beyond competitors by introducing more than 50 new in-database time series and ML functions, and integrated ModelOps to rapidly operationalize AI/ML initiatives. This new functionality — in combination with the launch of VantageCloud Lake, Teradata’s first product based on all-new, next-generation cloud-native architecture, also announced today — gives customers the ability to activate massive amounts of data and solve complex business challenges with a robust library of open and connected analytics tools that provide autonomy, ease of access, and real-time insights. 

“Data is only as valuable as its ability to be synthesized for actionable, real-world insights that drive better outcomes,” said Hillary Ashton, Chief Product Officer at Teradata. “Over its 40+ year history, Teradata has been laser-focused on helping customers extract the most value from their data with consistently high performance, unmatched scalability, and a trove of analytic functionality. With the launch of VantageCloud Lake and the availability of ClearScape Analytics across the VantageCloud platform, Teradata is continuing its tradition of listening to its customers and helping them accelerate their digital transformations by providing a data platform that is born in the cloud with end-to-end support for advanced analytics across the cloud ecosystem.” 

Observable Announces Free Teams, an Open and Easy Way for Data Teams to Collaborate with the Largest Community of Data Practitioners

Observable, the rapidly growing data collaboration platform, announced the introduction of free team accounts for data analysts, data scientists, developers, engineers and key decision makers, allowing them to learn from and build on each other’s work openly and publicly. Observable’s new free team offering opens up easy collaboration using the largest collection of industry-leading, public data work occurring in Observable to the platform’s engaged community of more than five million data experts and explorers engaged.

“The democratization of data work and access to tools is crucial to help everyone make sense of the world with data,” said Melody Meckfessel, co-founder and CEO of Observable. “By offering Free Teams, data practitioners at every experience level can create, collaborate and gain insights from their data with the help of Observable’s amazing community of data experts. There are no limits to what’s possible for open, easy data collaboration.”

TDengine 3.0 Introduces Cloud Native Architecture to Simplify Large-scale Time-Series Data Operations in IoT 

TDengine released TDengine™ 3.0, which adds a cloud-native architecture for Kubernetes deployments and other innovations that both scale and simplify the deployment and management of massive time-series data environments. 

“As large-scale IoT deployments generate ever-increasing amounts of data, time series databases are soaring in popularity,” said Jeff Tao, founder, and CEO of TDengine. “TDengine 3.0 delivers an open-source platform specifically designed for these modern time-series operations. It’s easy to deploy and query, and scales to handle the terabytes to petabytes of data generated daily by billions of IoT sensors and data collectors.” 

Privitar Announces General Availability of Privitar Modern Data Provisioning Platform

Privitar announced the general availability of the Privitar Modern Data Provisioning (MDP) Platform, a new data security platform designed to help organizations maximize their use of data effectively and responsibly, within their organizations and beyond. The Privitar Modern Data Provisioning Platform uses a policy-based approach that enables organizations to comply with privacy regulations and protect customer trust with security and privacy capabilities built into data operations.

“We know that businesses get the best outcomes from their data when they address data security and privacy within data provisioning processes,” said Jason du Preez, CEO of Privitar. “We have built the Privitar Modern Data Provisioning Platform to streamline that process and to help businesses operate more effectively. Our policy-centric approach to data provisioning enables users to get safe and meaningful data into the hands of those who need it when they need it. This is a new paradigm that uses context-aware policies to accelerate access to data without compromising on utility, risk, compliance, or customer trust.” 

Acceldata Delivers Comprehensive Data Observability Platform for the Modern Data Stack

Acceldata, a market leader in enterprise data observability for the modern data stack, announced the general availability of its data observability cloud solution. The expanded platform offers data observability options to enterprises regardless of where they are on their data journey – cloud native, multi-cloud, hybrid or on-premises.

Building and operating great data and analytics products requires a rethink and redo of common data management and analytics practices and tools. Fostering collaboration between product teams, business leaders,  data teams and operations focussed teams, and adopting data observability helps create lasting competitive advantage. The Acceldata data observability cloud empowers data teams with multidimensional insights by synthesizing signals from multiple layers, consolidating and analyzing them to deliver superior performance and increase business ROI from data. 

“Acceldata is a cloud agnostic company that offers data observability solutions for enterprises no matter where  they are on the data journey,” said Rohit Choudhary, founder and CEO, Acceldata. ”As  our mission is to make interactions with data flawless, the Acceldata data observability platform enables enterprises to build and operate great data products by improving efficiency, reducing risk and addressing key challenges such as data sprawl, tech sprawl and reliability of data.”

Scanbuy Announces ExtendedAudiences™ – Act-Alike Audience Extensions of CPG Consumer Purchase Data, Powered by Diveplane

Scanbuy, a global leader in mobile engagement and digital advertising, announced the launch of ExtendedAudiences™ for CPG brands and agencies. ExtendedAudiences™ are privacy-protected, act-alike audience extensions of U.S. consumer CPG purchase data, powered by Diveplane, the company keeping the humanity in artificial intelligence (AI). For the first time in AdTech, Scanbuy will deliver act-alike audiences that are editable, auditable, and scalable, in a transparent, privacy-first manner for data-driven digital marketers. Scanbuy will feature and differentiate on how openly it treats consumer privacy across all its shopping data.

More organizations are embracing AI/ML to support their business operations, which makes more urgent the need for authentic training data that accurately reflects a population. ExtendedAudiences™ data models are designed to extend the benefits of the Interactive Advertising Bureau’s (IAB’s) data transparency standards from deterministic to modeled data sets. A forensic-level audit is available for all stakeholders — including agencies, brands, consumers, data providers, and regulators — at run-time, every time an act-alike model is generated.

“At Scanbuy we are focused on advancing the AdTech data transparency standards that define responsible audience data collection,” said Chai Outmezguine, Chief Executive Officer. “AI and ML-derived value will be critical to our industry’s future. By requiring that all our models be inherently understandable, Scanbuy allows self-attestation data audits to be extended to modeled audiences. Model explainability allows us to determine how predictions are built, protect attributes across data partners, and maintain the data subject’s ultimate privacy and control over usage. We also see a bright future in introducing this transparency to re-enforcement learning techniques that help optimize in-flight campaigns. Together with Diveplane, we are setting a new precedent for privacy, transparency, and auditability.”

Folio Photonics Announces Breakthrough Multi-Layer Optical Disc Storage Technology to Enable Industry-Disruptive Cost, Cybersecurity and Sustainability Benefits

Folio Photonics, a leading pioneer of immutable active archive, announced that it has achieved a significant breakthrough in multi-layer optical disc technology that will enable an unprecedented level of cost, security and sustainability advantage. Leveraging patented advancements in materials science, Folio Photonics has developed the first economically viable, enterprise-scale optical storage discs with dynamic multi-layer write/read capabilities, which will enable the development of radically low-cost/high-capacity disc storage.

“Our talented engineering team – under the leadership of founder and CIO Dr. Kenneth Singer – has pioneered a fresh approach to optical storage that overcomes historical constraints and puts unheard of cost, cybersecurity and sustainability benefits within reach,” said Steven Santamaria, Folio Photonics CEO. “With these advantages, Folio Photonics is poised to reshape the trajectory of archive storage.”

InfluxData Brings Native Data Collection to InfluxDB

InfluxData, creator of a leading time series platform InfluxDB, announced new serverless capabilities to expedite time series data collection, processing, and storage in InfluxDB Cloud. InfluxDB Native Collectors enable developers building with InfluxDB Cloud to subscribe to, process, transform, and store real-time data from messaging and other public and private brokers and queues with a click of a button. Currently available for MQTT, Native Collectors introduce the fastest way to get data from third-party brokers into InfluxDB Cloud without the need for additional software or new code.

Time series data comes from many different sources and widely distributed assets and applications. To make sense of all this data, developers need to consolidate time series data in a central location. However, the pipelines from data sources to the database are complex and require resource-intensive customizations, creating additional challenges for developers. Other systems require an intermediary layer to transfer and transform data from external systems to the cloud. InfluxDB Native Collectors expedites this process by removing that intermediary layer, allowing cloud data sources to connect directly to InfluxDB Cloud so developers can collect, transform, and store time series data in cloud environments directly and without writing new code.

“Data is born in the cloud at an exponential rate, but existing data pipeline tools that integrate multi-vendor cloud services are expensive, complex, and a burden for developers to manage,” said Rick Spencer, Vice President of Products, InfluxData. “With Native Collectors, we’re expediting device to cloud data transfers so developers can focus on building and scaling applications with their time series data. These updates enable InfluxDB Cloud to become a serverless consumer of data through easily configured topic subscriptions, greatly simplifying time series data pipelines and applications alike.” Provides Deeper Insight into the Modern Data Stack with Knowledge-Graph-Powered Data Lineage, the enterprise data catalog for the modern data stack, announced Eureka Explorer™ Lineage, a new automated column-level technical lineage experience powered by’s knowledge graph. Explorer Lineage enables all members of an organization’s data team to make data-driven decisions faster with full visibility into the modern data stack. With an easy-to-follow, interactive user interface, Explorer Lineage can show where data is sourced, how it’s aggregated, and any transformations it undergoes along its journey.  

Data lineage is an application of metadata that provides visibility into where data originates, how and where it’s applied, and whether it’s been manipulated. Lineage provides critical context for data applications and can improve the resiliency and reliability of data and analytics supply chains.

“Most catalog-native data lineage solutions struggle to interrelate data lineage with essential business concepts,” said Jon Loyens, chief product officer and co-founder at “What’s missing is the semantic relevance only a knowledge graph can provide. Explorer Lineage gives your organization visibility into its data with complete context, providing knowledge and meaning, and that visibility helps ensure accurate, complete, and trustworthy data is being used to drive your business forward.”

Anyscale Unveils Ray 2.0 and Anyscale Innovations

Anyscale, the company behind Ray, the unified framework for scalable computing, announced Ray 2.0 and the enterprise-ready capabilities and roadmap for Anyscale’s managed Ray platform. The accelerated adoption of Ray is driven by the growing gap between the demands of machine learning (ML) applications and the limitations of a single processor or a single server. In the past few years alone, the computational requirements for ML training have been growing between 10 to 35 times every 18 months. This fact, combined with the engineering complexity of scaling these workloads, has led to over 85 percent of AI projects failing in production. Ray tackles the cost and complexity of scaling head-on and is the fastest growing open-source, unified distributed framework for scaling AI and Python applications.

“Ray and the Anyscale platform have made tremendous progress in advancing the scaling of machine learning and Python workloads,” said Anyscale CEO, Robert Nishihara. “Thousands of organizations already rely on Ray for their AI initiatives and dozens of them are showcasing their use cases and breakthroughs at this year’s Ray Summit. With new innovations in Ray 2.0 and Anyscale’s platform, we are further accelerating our efforts to ensure Ray is easily accessible to any developer and to organizations of all sizes.” 

Granulate, an Intel Company, to Launch a Free Solution for Autonomous Kubernetes Cost Optimization

Granulate, an Intel Company, developer of autonomous, continuous workload optimization solutions, announced the upcoming launch of its latest free cost-reduction solution, gMaestro, a continuous workload and pod rightsizing tool for Kubernetes cost optimization. Granulate’s gMaestro provides DevOps, SREs, and FinOps teams full visibility into their K8s clusters allowing them to eliminate over-provisioning and reduce costs by up to 60%. Kubernetes have played a key role in managing containerized environments and reducing development times, yet cost and resource management remain a challenge. The costs of over-provisioning, as well as mismanaged and idle resources have climbed and become a major financial burden for companies globally.

gMaestro, which can be installed with a single line of code, provides visibility into inefficiencies within Kubernetes clusters. Users can automatically apply HPA, CPU, and Memory request changes that can be employed to save up to 60%. The fully autonomous capability will be generally available next month, enabling all gMaestro users to implement the recommendations with a click of a button.  

“Organizations are taking a hard look at their budgets due to the current economic realities and looking for any opportunity to reduce costs,” said Asaf Ezra, CEO of Granulate. “Part of our goal at Granulate has been to democratize solutions for the engineering community by making optimizations easy to achieve and even fully autonomous. We are fortunate that as an Intel company we can continue bringing new tools to the market to further that vision.” announces the launch of its proprietary DynamicNLP™, a first in the enterprise Conversational AI space, a leading enterprise-grade Conversational AI platform trusted by 1000+ enterprises globally, announced the launch of its proprietary DynamicNLP™, a first in the enterprise Conversational AI space to enable enterprises to go-live within minutes with lower operational costs and an intent accuracy of over 97%.

According to the future of conversational AI from Deloitte, training AI agents with manual methods can take as long as six to nine months, making it one of the most common setup challenges faced by enterprises. DynamicNLP™ eliminates the tedious process of training and labeling Natural Language Processing (NLP) models manually. This enables Dynamic AI agents to learn on the fly, helping enterprises to set up Conversational AI flows within minutes, and reduce training data-related costs and efforts. DynamicNLP™ comes with a pre-trained model built using billions of anonymized conversations, which helps in the reduction of unidentified utterances by up to 60%, making the AI agents more human-like and scalable across industries with wider use-cases.

Commenting on the launch, Raghu Ravinutala, co-founder and CEO, said, DynamicNLP™ is a first of its kind proprietary technology in the global enterprise Conversational AI industry; a breakthrough innovation that can help enterprises save time, effort, and operational cost while accelerating their go-live strategy. It enables our pre-trained Dynamic AI agents to deliver superlative moments of truth across the entirety of customers’ and employees’ life cycles. As global tech innovators, we see our DynamicNLP™ as a significant step forward in realizing the true potential of NLP as a game-changing technology.”

Verta Gains Significant Momentum with the Addition of New Enterprise-Focused Capabilities to its MLOps Platform

Verta, a leading provider of Artificial Intelligence (AI) model management and operations solutions, announced continued momentum with enhanced enterprise-focused capabilities added to its MLOps platform. The new updates include additions to Verta’s native integration ecosystem and subsequent capabilities around enterprise security, privacy and access controls, model risk management, and the pursuit of responsible AI. These updates can improve ML model production time by 30x, a feat that furthers Verta’s commitment to solving challenges organizations face with running intelligent products in production in efficient and safer ways at scale.

“The focus of ModelOps is steadily evolving from model experimentation to operational AI where business value is ultimately realized,” said Manasi Vartak, CEO and Founder of Verta. “The consequences and technology ecosystem of AI operating in a production setting are far different from when and where the models are built.   We continue to innovate and deliver on our roadmap to provide organizations with a platform to maintain operational excellence and perform to their service-level agreements (SLA), system reliability and high availability requirements, model performance expectations, and governance policies and procedures.”

Arcion Releases the Next Evolution of Real-Time CDC Data Pipeline Technology

Arcion, creator of the cloud-native, CDC-based data replication platform, announced a major new product release that extends the platform’s capabilities to include native log reader with Oracle databases, automated DDL-based schema evolution, and on-the-fly column transformations. Combining with the end-to-end multi-threaded architectural design, Arcion is able to bring a 10x faster log extraction experience to Oracle users. The company also has expanded its range of source and target connectivity to include BigQuery, Azure-managed SQL Server, and Imply.

“Arcion is committed to investing in continuous innovation based on our customers’ needs,” said Arcion CEO Gary Hagmueller. “Our goal is to be the first choice in one-stop, whole-product solutions for large-scale data replication. Today, we’re the only distributed, end-to-end multi-threaded CDC data replication platform on the market that makes it possible to design and deploy streaming pipelines in just minutes, with zero code and minimal engineering resources to maintain.”

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