BIG DATA MANAGEMENT

GoodData Adds Advanced Analytics to the Freshworks Marketplace

GoodData | January 06, 2022

GoodData, the leader in data and analytics infrastructure, today announced its new app on the Freshworks Marketplace to provide a powerful and scalable solution designed to accelerate the use and application of analytics for Freshworks customers.

The Freshworks Marketplace hosts apps built by the Freshworks developer community. These apps make use of Freshworks products and partner solutions to create delightful experiences for businesses. The marketplace enables partners to reach Freshworks customers and serve them jointly. Freshworks Inc., (NASDAQ: FRSH) is a leading software company empowering businesses to delight its customers and employees.

With the demand for cloud-native solutions and easy-to-use analytics on the rise, large companies with enterprise-grade data need vendors to provide analytics within their existing architecture. With the integration of GoodData’s analytics tool into its marketplace, Freshworks now provides enterprises with more options to unlock rich insights from within their data. Additionally, Freshworks can tap into GoodData's extensive experience powering analytics innovation in the Customer Experience Management (CX) space. The integration between GoodData and Freshworks will help provide valuable analytics for customer support teams to better understand the strong and weak points of their customer facing team and help to better customer experiences.

“For data leaders to meet the challenges of today’s hyper-competitive market, they have to reinvent the way they think about and utilize data at every layer of their organization. Freshworks recognized the need for its marketplace to offer an analytics platform that tells a customer-centric, accessible story with data, and our solutions make it possible for Freshworks to implement immediately and scale​​. This app will make it easy for enterprises to understand and benefit from modern analytics, and it’s just the beginning of a fruitful partnership between our two cloud-first companies. We are excited to collaborate with Freshworks.”

GoodData founding CEO Roman Stanek

Freshworks helps some of the largest, industry-leading companies in the world — ranging from healthcare to financial services, and more — realize value from their software. Already providing customers with low-code development and ​​custom apps within their marketplace to extend their product capabilities at scale, Freshworks now partners with GoodData to provide customers with more options to unlock their inherent value of data as a strategic asset.

“Analytics is a key part of improving user experience for any technology. As we continue to grow, we need an ISV partner who not only understands our business model but also one that could purpose-build apps for the modern business software users,” said Hérve Danzelaud, VP of Global Partnerships at Freshworks. “GoodData’s state-of-the-art analytics stack is the perfect tool to quickly bring nearly real-time analytics into our current offerings and helps enterprises to access vital insights in this new age of data.”

The marketplace app is the first step in an ongoing partnership between GoodData and Freshworks, and the companies will continue to work together to provide actionable and easy to use analytics to Freshworks customers. The partnership will expand Freshworks’ offering with advanced analytics and business insights.

About GoodData
GoodData is on a mission to break data silos. Real-time, open, secure, and scalable, GoodData’s leading composable data and analytics platform provides a single source of truth across organizations and to their customers. To this day, GoodData has helped more than 140,000 of the world’s top businesses deliver on their analytics goals and scale their use cases — from self-service and embeddable analytics, to machine learning and IoT.

Spotlight

Data is increasing in importance to most organizations. In 451 Research’s Voice of the Enterprise: Data & Analytics, Data Platforms survey, 82% of participants indicated that data will be more important to the decision-making process at their organization over the next 12 months. Leveraging this data comes with challenges that s


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BIG DATA MANAGEMENT

IBM Watson Advertising Brings AI-Driven Weather Analytics to AWS Data Exchange

IBM Watson | January 10, 2022

IBM Watson Advertising today announced the availability of data from The Weather Company, an IBM Business, on AWS Data Exchange, an Amazon Web Services (AWS) platform. The AWS Data Exchange allows businesses to easily find and subscribe to third-party data in the cloud. Providing data from the world's most accurate weather forecaster1, IBM Watson Advertising's Weather Analytics harness the relationship between weather and consumer behavior using artificial intelligence to extract deep insights to help businesses make more confident, data-driven and insightful enterprise decisions. The weather datasets can help analyze how weather affects consumer purchasing across different categories such as pharmaceuticals, apparel, consumer packaged goods and indoor and outdoor activities. Local data by ZIP code including historical weather data, 15-day forecast weather data, and relative data such as hot, cold, windy and other conditions could also be used to help inform campaigns, supply chain and forecasting decisions. This data can even help surface unique or non-obvious relationships between weather and consumer behavior. "We know that weather can impact nearly everything in daily life -- how we feel, what we do, even what we buy," said Sheri Bachstein, Chief Executive Officer at The Weather Company and General Manager of IBM Watson Advertising. "This expanded relationship with AWS gives more businesses access to the weather data that can drive consumer behavior and purchasing. We are committed to opening up our insights and technology to a broad set of organizations, and giving more companies access to what we know can be growth- and efficiency-driving data and tech." Insights that show locations where weather could affect sales can help businesses drive revenue based on predictive consumer behavior. According to past IBM Watson Advertising research, data revealed that while chocolate candy bar sales generally go up in colder months across the U.S., sales can spike in the Southwest when a higher heat index is expected, and in the Northeast during muggy nights. In another example, while more bug spray is purchased during the summer months, foggy conditions in the Northwest can drive more sales while clear conditions can drive demand in central states. AWS Data Exchange helps make it easy to find, subscribe to, and use third-party data from providers in the cloud. Subscribers can use the AWS console or APIs to load IBM Watson Advertising solutions into a wide variety of AWS analytics and machine learning services. This is the latest example of how IBM is building together with ecosystem partners of all types to create solutions for developers to address the needs of the hybrid cloud era. IBM is committed to a $1 billion investment in its partner ecosystem over the next three years. This investment is already being utilized to support a coalition of enterprises that are helping customers migrate their mission-critical workloads using IBM's open hybrid cloud architecture. About IBM Watson Watson is IBM's AI technology for business, helping organizations to better predict and shape future outcomes, automate complex processes, and optimize employees' time. Watson has evolved from an IBM Research project, to experimentation, to a scaled, open set of products that run anywhere. With more than 40,000 client engagements, Watson is being applied by leading global brands across a variety of industries to transform how people work.

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BIG DATA MANAGEMENT

Komprise Automates Unstructured Data Discovery with Smart Data Workflows

Komprise | May 20, 2022

Komprise, the leader in analytics-driven unstructured data management and mobility, today announced Komprise Smart Data Workflows, a systematic process to discover relevant file and object data across cloud, edge and on-premises datacenters and feed data in native format to AI and machine learning (ML) tools and data lakes. Industry analysts predict that at least 80% of the world’s data will be unstructured by 2025. This data is critical for AI and ML-driven applications and insights, yet much of it is locked away in disparate data storage silos. This creates an unstructured data blind spot, resulting in billions of dollars in missed big data opportunities. Komprise has expanded Deep Analytics Actions to include copy and confine operations based on Deep Analytics queries, added the ability to execute external functions such as running natural language processing functions via API and expanded global tagging and search to support these workflows. Komprise Smart Data Workflows allow you to define and execute a process with as many of these steps needed in any sequence, including external functions at the edge, datacenter or cloud. Komprise Global File Index and Smart Data Workflows together reduce the time it takes to find, enrich and move the right unstructured data by up to 80%. “Komprise has delivered a rapid way to visualize our petabytes of instrument data and then automate processes such as tiering and deletion for optimal savings,” says Jay Smestad, senior director of information technology at PacBio. “Now, the ability to automate workflows so we can further define this data at a more granular level and then feed it into analytics tools to help meet our scientists’ needs is a game changer.” Komprise Smart Data Workflows are relevant across many sectors. Here’s an example from the pharmaceutical industry: 1) Search: Define and execute a custom query across on-prem, edge and cloud data silos to find all data for Project X with Komprise Deep Analytics and the Komprise Global File Index. 2) Execute & Enrich: Execute an external function on Project X data to look for a specific DNA sequence for a mutation and tag such data as "Mutation XYZ". 3) Cull & Mobilize: Move only Project X data tagged with "Mutation XYZ" to the cloud using Komprise Deep Analytics Actions for central processing. 4) Manage Data Lifecycle: Move the data to a lower storage tier for cost savings once the analysis is complete. Other Smart Data Workflow use cases include: Legal Divestiture: Find and tag all files related to a divestiture project and move sensitive data to an object-locked storage bucket and move the rest to a writable bucket. Autonomous Vehicles: Find crash test data related to abrupt stopping of a specific vehicle model and copy this data to the cloud for further analysis. Execute an external function to identify and tag data with Reason = Abrupt Stop and move only the relevant data to the cloud data lakehouse to reduce time and cost associated with moving and analyzing unrelated data. “Whether it’s massive volumes of genomics data, surveillance data, IoT, GDPR or user shares across the enterprise, Komprise Smart Data Workflows orchestrate the information lifecycle of this data in the cloud to efficiently find, enrich and move the data you need for analytics projects. “We are excited to move to this next phase of our product journey, making it much easier to manage and mobilize massive volumes of unstructured data for cost reduction, compliance and business value.” Kumar Goswami, CEO of Komprise About Komprise Komprise is a provider of unstructured data management and mobility software that frees enterprises to easily analyze, mobilize, and monetize the right file and object data across clouds without shackling data to any vendor. With Komprise Intelligent Data Management, you can cut 70% of enterprise storage, backup and cloud costs while making data easily available to cloud-based data lakes and analytics tools.

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DFIN Acquires Guardum, Strengthening Global Data Privacy and Redaction Capabilities

DFIN | December 14, 2021

Donnelley Financial Solutions , a leading risk and compliance company, today announced it has acquired Guardum, a leading data security and privacy software provider that helps companies locate, secure, and control data. The acquisition strengthens DFIN's software solutions portfolio by making data security a competitive differentiator, enhancing regulatory compliance, safeguarding privacy, and improving data accuracy. Guardum helps to solve one of the most pressing data problems companies face today: quickly locating personal information — in many languages — among vast stores of corporate data, implementing an agile workflow across data governance and GRC, and redacting that information either temporarily or permanently. A Powerful Combination One of Guardum's strengths is its ability to examine semi-structured and unstructured data in native document format — eliminating the need to convert files. This is extremely useful during the due diligence phase of an acquisition. DFIN's Venue virtual data room, with Guardum's privacy tools, allows companies to meet global deal regulations and confidentially accelerate transactions by safeguarding critical documents and market sensitive information, tax data, employee personal data, and more. In addition, regulations and guidelines involving personal data are becoming more stringent. The California Consumer Privacy Act (CCPA) and General Data Protection Regulations ((EU) 2016/679 GDPR) are two examples of government regulations that have increased the burden on many companies. As global regulators continue to create and modify data compliance rules, the need for data security will only increase. "DFIN's industry-leading software solutions address the most challenging regulatory and compliance issues that companies face," said Craig Clay, president of Global Capital Markets at DFIN. "Incorporating Guardum's data security and public information technology into our platform creates privacy intelligence by identifying and protecting our clients' sensitive data, automating time-consuming processes, and reducing the risk of exposing sensitive data to comply with the growing number of privacy regulations in an ever-changing digital world." "DFIN has a stellar reputation for providing the highest quality software solutions that help companies tackle their risk and compliance needs. Working together, we will develop software solutions that will help lower overall compliance spending and significantly mitigate risk for organizations throughout the globe." Rob Westmacott, co-founder at Guardum Eliminating the need for manual review processes allows executives to focus on higher priority aspects of any transaction. Businesses can now benefit from the following: Speed and Efficiency: Up to 93 percent faster in helping to find and redact data (versus manual) Cost Reduction: Improved operational compliance, process, and efficiencies Scale: Eases the burden on Information Technology departments since the technology is highly scalable, easy to use, and integrates with other applications Enhanced Security: Enhanced overall security extending beyond general-purpose discovery or classification tools These capabilities and benefits are a top priority for executives responsible for mergers and acquisitions; data protection officers; and compliance and legal experts; as well as human resources; security; and environmental, social, and governance (ESG) teams. About Donnelley Financial Solutions (DFIN) DFIN is a leading global risk and compliance solutions company. We provide domain expertise, enterprise software and data analytics for every stage of our clients' business and investment lifecycles. Markets fluctuate, regulations evolve, technology advances, and through it all, DFIN delivers confidence with the right solutions in moments that matter.

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Pathr.ai Unveils New Spatial Intelligence Analytics Tools for Retailers to Help Drive In-Store Profitability, Increase ROI

Pathr.ai | January 15, 2022

Pathr.ai, the industry's first and only artificial intelligence (AI) powered spatial intelligence platform, today announced three powerful new spatial intelligence analytics tools focused on helping retailers drive in-store profitability. Pathr.ai’s CPG Display Tool, True Conversion Rate Tool, and Brand Effect vs. Location Tool are all designed to deliver previously unavailable business insights that empower retailers to obtain higher levels of revenue and make stronger business decisions for their physical stores. “Retailers today lack in-store analytics around customer behavior - critical information that can lead to increased profitability and improved business outcomes. We designed our new tools to address some of the most pressing concerns for retailers,” said George Shaw, CEO and Founder of Pathr.ai. “In addition to our Brand Effect vs. Location Tool and True Conversion Rate Tool, now, for the first time ever, retailers will be able to assess the effectiveness of CPG brands at their stores with our CPG Display Tool.” Pathr.ai’s new tools include: CPG Display Tool: For the first time ever, retailers have a solution that helps them assess the effectiveness of CPG brands at their stores with store-level data to directly measure and maximize the impact of Category Management efforts. By analyzing shopper traffic and dwell impressions within various store departments, retailers can enhance their strategic CPG brand partnerships by offering them valuable data to improve their merchandise placement and marketing promotions. This information also allows CPG brands to better understand how their products are performing in different areas of a store and can be a potentially lucrative new data source for retailers. True Conversion Rate Tool: Allows retailers to quantify group size dynamics in their locations (ex: families, couples, or singles) and delivers a more accurate buyer conversion rate for retailers. This is a huge departure from how the conversion rate is typically calculated, with most retailers measuring individuals, not groups. If a family of 4 enters a retail location, usually only one person from that family will pay for a product, not all 4. In addition to a more accurate conversion rate, this data can also be used to inform merchandising and in-store promotion initiatives. Brand Effect vs. Location Tool: Lets retailers assess how effective their store-within-a-store brands and locations are performing. For example, retailers can leverage this data to understand the full business impact of their store-within-a-store, assessing if that location resulted in traffic to other areas or if it outperformed conventional sections of their store. Retailers can quantify traffic and dwell times around store-within-a-store locations to benchmark rents for each area and guide potential adjustments in location and surrounding store signage to improve performance. “Spatial Intelligence can be a powerful asset to retailers focused on maximizing their profits and improving operational efficiencies critical to their success. We’ve created our insight tools to empower retailers to make business decisions in an accurate and data-driven way, and ultimately share that insight with their CPG supplier base.” Alan Flohr, Chief Revenue Officer of Pathr.ai Pathr.ai integrates and collects data from a retailer’s existing camera infrastructure. It measures customer movement inside a physical space anonymously - allowing companies to comply with GDPR and CCPA standards and achieve positive business results in an unbiased way. About Pathr.ai Pathr.ai is the industry’s first AI-powered spatial intelligence software company that uses anonymous location data from available and existing infrastructure to observe human behavior in any physical space. Its sophisticated technology turns raw behavioral and spatial data from existing sensors into actionable and applied business learnings - allowing companies to drive the business results that matter most to the growth of their companies in real-time. Founded in 2019, Pathr.ai is headquartered in Mountain View, California.

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Spotlight

Data is increasing in importance to most organizations. In 451 Research’s Voice of the Enterprise: Data & Analytics, Data Platforms survey, 82% of participants indicated that data will be more important to the decision-making process at their organization over the next 12 months. Leveraging this data comes with challenges that s

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