BIG DATA MANAGEMENT

World's First Data Storytelling Feed Launched by Yellowfin

Yellowfin | July 05, 2021

Yellowfin, a world-leading vendor in innovative analytics, has released version 9.6 with new upgrades and capabilities that unify actionable dashboards, automated business monitoring, and data storytelling into a unique analytics experience for business users.

Yellowfin Stories, introduced in Yellowfin 8, allows data creation narratives that generate a consistent understanding across a company. Yellowfin combines written, long-form analysis with embedded text, images, video, or snapshots of analytical content for businesses within a governed and secure platform.

The five key areas of enhancement in Yellowfin 9.6 are:

Data Storytelling Feed now allows dashboard designers to integrate the most relevant stories directly onto the dashboard.
Story Templates can now be created based on existing stories from the Data Storytelling Feed, providing repeatability and efficiency to authors and allowing them to customize stories without starting from scratch.
Story Filters are now available for stories, allowing authors to dynamically filter embedded analytic content directly within a story and save this configuration against the published version, optimizing the process of creating recurring stories.
Visualizations have been enhanced on the Chart Builder, enabling analysts to perform deeper customizations with new options for chart axis values and labels, category spacing, and sorting.
SAML Authentication now supports native identity provider configuration, enabling IT and DevOps teams to manage authentication parameters and configuration directly within the platform.


About Yellowfin
Yellowfin is a global BI and analytics software vendor with a suite of world-class products powered by automation. Yellowfin is recognized as an innovator by the world's leading analyst firms. More than 29,000 organizations and over 3 million end-users across 75 countries use Yellowfin every day.

Spotlight

Predictive modeling, machine learning and other advanced analytics applications help dig the business value out of big data systems -- but for many users, it takes a lot of tools and effort.


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BIG DATA MANAGEMENT

HCL Technologies Acquires Hungarian Data Engineering Services Company Starschema

HCL Technologies | January 17, 2022

HCL Technologies (HCL), a leading global technology company, signed a definitive agreement for the acquisition of Starschema, a leading provider of data engineering services, based in Budapest, Hungary. The strategic acquisition will bolster HCL’s capability in digital engineering -- driven by data engineering -- and increase its presence in Central and Eastern Europe. Starschema provides consulting, technology and managed services in data engineering to Global 2000 companies in the U.S. and Europe. The acquisition combines Starschema’s high-value capabilities and data-focused expertise with HCL’s existing presence in industry segments undergoing data-driven transformation. In addition, HCL will strengthen its position in data engineering, which is an integral part of the company’s digital engineering capabilities and next-generation offerings. “Joining HCL will enable us to keep our strategic focus and expand our data engineering capacity to provide a greater breadth and depth of services to clients. As part of HCL’s full spectrum of technology services, we will leverage our expertise in data engineering and emerging data technologies to solve companies’ data challenges, through building fast, scalable solutions that make people more effective and companies more profitable. This strategic move also represents exemplary career growth opportunities for our people.” Tamas Foldi, Founder and CEO, Starschema “Starschema will strengthen our data engineering capabilities, providing us with the ability to leverage its solutions and talent in Central and Eastern Europe,” said Vijay Guntur, President, Engineering and R&D Services, HCL Technologies. “Starschema’s capabilities will further scale HCL’s data engineering competencies at our integrated delivery centers across the world. Engineering talent will continue to remain in high demand, and Starschema offers a specialized talent pool in a strategic growth area for HCL. Following the acquisition, HCL will be able to offer data engineering consulting and near-shore access to digital engineering services to a wide base of clients.” The transaction is subject to regulatory clearance from the Hungarian Ministry of Innovation and Technology and is expected to close in March 2022.

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BUSINESS INTELLIGENCE

Domo Launches Data Apps to Fill the Gaps of Traditional BI and Analytics

Domo | March 24, 2022

Today Domo announced Data Apps, new low-code data tools for everyone across an organization, designed to bring the benefit of data-driven decisions and actions to those who are underserved by traditional business intelligence (BI) and analytics. A Data App, which combines data, analytics and workflows, is experienced as a personalized standalone experience on a mobile device or embedded into existing apps and processes where work is already happening. Unlike traditional BI, which is designed for executives, managers and data analysts and requires a level of data literacy to interpret and apply insights, Data Apps are designed for any role in an organization and are built so any person can be guided by data to the optimal decisions and actions for achieving specific business outcomes. For example, an employee on the manufacturing floor can leverage a Data App on a work tablet to ensure the company’s quality and safety goals are met throughout their role in the production process. Or a shift manager in a coffee shop can get real-time insights on their phone into customer satisfaction scores and make necessary adjustments on-the-fly to improve the customer experience. The continued push for digital transformation across all areas of business is highlighting the urgent need for new data tools. Despite all the modernization efforts around business intelligence, data is still not being effectively leveraged in most organizations. In fact, no more than 20% of enterprise decision-makers who could be using business intelligence (BI) applications hands on are doing so. The other 80% still rely on the data and analytics skills of those 20% who do use BI applications, according to The Future of BI, Forrester Research Inc., February 23, 2022. And recent research sponsored by Domo showed the lack of proper tools is one of the key barriers that keeps organizations from using data more holistically. “It is time for organizations to move beyond thinking of data as charts and graphs and towards adopting customized intelligent apps that not only deliver insights but drive action and support the needs of workers right where the work gets done. Our focus with Data Apps is supporting the white spaces in organizations where traditional BI and enterprise software applications like CRM and ERP have traditionally not reached. We’re making it easy for customers to put data to work for everyone by leveraging Domo as a low-code data app platform to build apps and improve business processes and outcomes everywhere work gets done.” John Mellor, Domo CEO “Organizations face challenges in finding an approach to Data Apps that enables digital transformation. They seek solutions that allow organizations to easily compile, aggregate and share data across trusted networks - both inside and outside organizations, while giving each team member personalized data and automation needed for the business to move forward with more agility,” said R “Ray" Wang, founder and principal analyst, Constellation Research, Inc. Because of Domo’s robust data integration capabilities with more than 1,000+ native connectors built and managed by Domo, Data Apps can easily leverage data from existing systems – regardless of where data lives whether it be in a cloud data warehouse or data lake, or a core application like SAP, Salesforce or NetSuite. As a result, Data Apps are designed to deliver business value at record speed and scale, and what used to take weeks and months, now takes hours or days. “For decades analytics tools have been focused on solving the wrong problem. There will always be a place for ad hoc analyses, but organizations can better meet their day-to-day analytic needs with more directed, purpose-built analytical applications that are embedded into operational processes for line-of-business personnel - whether they be store managers, stock room team members or customer service representatives,” said David Menninger, senior vice president and research director, Ventana Research. “Using a platform like Domo’s to develop and distribute analytics apps helps eliminate time-consuming tasks such as data integration and management, allowing organizations to be more agile and responsive to existing business requirements and new market requirements as they arise.” As part of today’s announcement, Domo launched four solution accelerators, highly configurable Data Apps designed to support common business processes that have not been solved with traditional BI or enterprise software. These accelerators leverage the full capabilities of the Domo platform for data integration, analytics and distribution and are specifically for customers in retail, CPG and financial services. These first four solutions are as follows: Retail Store Performance and Operations – designed as a mobile app for executives, ops leaders, field and store employees to create the best customer experiences and drive sales and margin performance in the stores Retail-Vendor Brand Performance & Insight Sharing – designed for real-time collaboration around point-of-sale data, inventory and market data to help retailers and their vendor partners profitably grow their respective businesses Supply Chain Collaboration and Operations – a cross-functional supply chain problem solving tool that allows manufacturing, retail and logistics people to collaborate to improve supply chain visibility and efficiency to minimize cost Banking Customer Profitability and Behavior Analytics – designed to give financial services organizations such as banks, credit unions and mortgage companies near real-time insight into customer preferences so they can drive more valuable, longer-term relationships with customers Additional Announcements Domo also announced today new updates to the Domo platform that allow customers to leverage data at speed and scale. These announcements include new multi-cloud enhancements, a new governance toolkit, new integrations with Microsoft Office Suite and Teams, and more. About Domo Domo transforms business by putting data to work for everyone. Domo’s low-code data app platform goes beyond traditional business intelligence and analytics to enable anyone to create data apps to power any action in their business, right where work gets done. With Domo’s fully integrated cloud-native platform, critical business processes can now be optimized in days instead of months or more.

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BIG DATA MANAGEMENT

Semantix Introduces Data & AI Marketplace to Semantix Data Platform

Semantix | April 07, 2022

Semantix, Latin America’s first fully integrated data platform, announced today the availability of a Data & AI Marketplace, consisting of a new array of features that significantly streamline the analytical journey for users of the Semantix Data Platform (known as SDP). The Data & AI Marketplace provides an app store-like experience that puts frequently used data sets and pre-packaged, vertical specific algorithms at the fingertips of data scientists and business analysts around the world. “Data scientists and business analysts shouldn’t need a doctorate in software engineering to glean insights from complex data sets. The SDP was purpose-built as an end-to-end solution for the analytical journey and these new features give our community of users the tools and resources that can make their journey easier and faster than it’s ever been before.” Leonardo Santos, co-founder and CEO of Semantix The new features in the SDP are broken into two separate categories – data sets and vertical specific algorithms. The data sets are a variety of pre-packaged, highly applicable data sets that users can leverage to train their machine learning algorithms and corollate with other proprietary data assets. These data sets include frequently used data on weather, diseases, stocks trade activity, consumer behavior and more. The vertical specific algorithms are meant to automate and streamline commonly analyzed business functions and use cases. For example, there is available today in SDP algorithms and dashboards for customer churn and retention, demand forecasting, predictive maintenance and more. Fueling Innovation for Public Journey Ahead Innovation is at the center of Semantix’s core values as a company. The SDP Marketplace is another milestone in Semantix’s ongoing commitment to push the envelope of innovation as it makes its way to the public market. In November of 2021, Semantix announced that it entered into a definitive agreement to merge with Alpha Capital (NASDAQ: ASPC), a special purpose acquisition company (“SPAC”) focused on technology. The announcement marked the first time a Latin American-focused technology SPAC had merged with a target company and highlights its growing position as a leading global innovator in the data and analytics space. About Semantix Semantix is Latin America’s first fully integrated data software platform. Semantix has more than 300 clients with operations in approximately 15 countries using Semantix’s software and services to enhance their businesses. The company was founded in 2010 by CEO Leonardo Santos.

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DATA SCIENCE

DataRobot Core Unveiled, Complete with Capabilities for the Expert Data Scientist

DataRobot | December 17, 2021

DataRobot today announced DataRobot Core, a comprehensive offering that broadens its AI Cloud platform for code-first data science experts. DataRobot also announced its latest platform release, extending the capabilities of AI Cloud for all users with broader and more sophisticated analytical capabilities for data scientists, enhanced decision intelligence, and new features to manage and scale operations in production. The unprecedented demand for AI, combined with the complexity in delivering AI to production, has created significant delays in data science initiatives for all businesses at a time when AI has never been more vital to business outcomes: 87% of organizations continue to struggle with long deployment timelines, while data scientists spend at least 50% of their time on non-strategic model deployment. To scale quickly and remain agile, data science teams need the tools and product capabilities to deliver high-impact results, faster. DataRobot Core brings together a complete portfolio of purpose-built capabilities that give data scientists ultimate flexibility in how they deliver AI to the business, enabling faster experimentation and rapid time to value, while making teams more efficient and effective at driving clear business impact from AI: Platform: Unified environment with first-class, embedded and multilanguage notebook experience; Composable ML to seamlessly pivot between code-first and automated model generation; code-centric pipelines on top of Apache Spark; open API to enable programmatic access to the full AI Cloud platform; and built for the modern enterprise with support for the reliability, governance, compliance and scale needs across industries. Resources: Extensive portfolio of accelerators, third-party integrations and libraries to expedite AI delivery and drive efficiency, along with evolving education resources to advance skills and enable data scientists to stay at the cutting edge. Community: Shared knowledge and access to the unique expertise of the DataRobot team, industry experts and thousands of community members from DataRobot customers representing some of the largest and most successful AI implementations in the world. DataRobot’s team of over 300 data scientists are pioneering efforts in AI, with applied expertise across more than a million active projects for customers across industries on a global scale. Leveraging DataRobot AI Cloud, full service direct mortgage lender Embrace Home Loans eliminated 43 million lines of code, freeing up their data scientists to build even more complex and strategic solutions. “DataRobot has been transformational for our business,” said Keith Portman, Chief Analytics Officer at Embrace Home Loans. “DataRobot’s AI Cloud platform enabled us to double our return on marketing investment spend and maintain a notebook-first approach. Our data scientists can now build complex models with flexibility and seamless integration, gaining back hours of time.” Alongside Core, the launch of DataRobot 7.3 introduces over 80 new features and capabilities designed for all users to enable AI-driven decisions across all lines of business, within a single platform. DataRobot 7.3 offers: Expanded Support for Diverse Use Cases. Giving data science teams native, out-of-the-box flexibility across data types, users can now run anomaly detection with images and leverage the next generation of Text AI, as well as comprehensive tools, including Multimodal Clustering, Time-Series Segmented Modeling and Multilabel Classification. Better, Faster Decisions with Decision Intelligence. Teams can rapidly deploy models that combine complex rules and business logic with post-process prediction scores with simple APIs, and build fully customized AI applications in a matter of minutes with no coding required. Enhanced Performance Monitoring, Compliance and Regulatory Capabilities. Automated compliance documentation now extends to custom models built outside of DataRobot, streamlining regulation readiness for all users. With all models in production, users can easily evaluate and compare challenger models against live models, and clearly see if a model should be replaced in order to maintain peak performance for the business. “For organizations today, translating data and AI into tangible outcomes is critical in order to remain competitive and thrive,” said Nenshad Bardoliwalla, Chief Product Officer at DataRobot. “DataRobot Core and 7.3 are designed to meet increasing demand and scale, and empower the largest number of AI creators, from code-centric data science teams to business analysts and decision makers, to experiment fast and collaborate effectively on the same platform. Together, these solutions provide the much-needed flexibility, speed and control that brings trustworthy AI solutions to life for every organization.” In support of DataRobot Core, DataRobot is also announcing an expanded partnership with AtScale to deliver more comprehensive data access and feature modeling to customers. AtScale brings its semantic layer technology to DataRobot Core, simplifying connections from DataRobot to a broad range of cloud data platforms and providing a powerful modeling canvas for feature engineering. Together, DataRobot and AtScale deliver complete services for organizations to operationalize AI/ML workloads with support for a wide range of data platforms, protocols and visualization platforms. About DataRobot DataRobot AI Cloud is the next generation of AI. DataRobot's AI Cloud vision is to bring together all data types, all users, and all environments to deliver critical business insights for every organization. DataRobot is trusted by global customers across industries and verticals, including a third of the Fortune 50.

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