BigData – Digital IT News

Cohesity Announces New AI Enhancements for Visual Data Explorer

Taylor Graham — Tue, 22 Oct 2024 13:30:09 +0000

Cohesity has unveiled a patent-pending visual data exploration feature as part of Cohesity Gaia, its AI-powered search assistant introduced earlier this year. This new capability visually categorizes themes across documents and files within a data set, offering fresh context to the data. The visual data explorer also suggests queries, helping users gain insights more quickly.

With traditional approaches, enterprises often struggle to gain insights across unstructured data and text. This challenge only grows as the amount of unstructured data increases. With unstructured data representing more than 80 percent of all corporate data, companies are often forced to run queries and compile reports based on a small subset of data—the information stored in structured systems. As a result, reports and analyses may be incomplete or inaccurate, with valuable insight still locked inside disparate unstructured systems.

Cohesity Gaia brings the power of generative AI to enterprise data, dramatically improving the speed and quality of insights available for a variety of use cases. The solution indexes and provides insight based on data stored in many popular formats, including emails, documents, PDFs, text files, spreadsheets, HTML, XML, and presentations.

Gain Insights Faster with Auto-Generated Themes and Topics for Thousands of Documents

One of the biggest challenges users face when working with vast datasets is having access to data but not knowing where to begin or what valuable insights can be retrieved. Cohesity Gaia overcomes this by automatically providing a visual representation of the data, sorted by themes, giving users a clear starting point. The new visual explorer uses topic modeling, a set of advanced AI techniques with natural language processing, to instantly identify hidden thematic structures across documents and files. This deep insight and context into the nature of the data offers a framework for better understanding, empowering users to ask more informed and targeted questions as they search.

The Gaia visual data explorer further simplifies this process by allowing users to click through each theme, ask conversational questions, and interact with intelligent, context-aware prompts to quickly find the most relevant information. Aligned with Cohesity’s responsible AI commitment, Gaia gives customers insight into their data while keeping it secure and compliant with regulatory requirements.

Cohesity will host a series of AI workshops to give customers and prospects a hands-on look at the first-of-its-kind visual data explorer and learn more about how Cohesity Gaia can help unlock new insights from their business. For more information on the AI workshops, visit our website.

“By addressing the challenge of managing and extracting insights from unstructured data across disparate systems, Cohesity Gaia and its new visual data explorer have the potential to revolutionize data accessibility for enterprises,” said Chirag Mehta, Principal Cybersecurity Analyst with Constellation Research. “This innovation not only could enhance data security and compliance but could also empower business users of enterprise customers with deeper, more contextual insights, significantly benefiting the decision-making process and operational efficiency.”

Access Vast Amounts of Data Stored in Sharepoint and NAS environments with Generative AI

Cohesity has also expanded support for new workloads and data sources within Gaia. Cohesity customers can now analyze corporate data protected on the Cohesity platform from Microsoft 365 Mail, Microsoft 365 Sharepoint, and Microsoft 365 OneDrive, as well as on-prem or cloud-based file servers, including popular systems like Dell EMC Isilon, Netapp NAS, physical file servers, and Cohesity Smartfiles.

The new visual data explorer feature in Cohesity Gaia visually maps customers’ data sets based on semantic indexing and creates a list of suggested questions and queries, illustrated here using test data.

To learn more about Cohesity Gaia visual data explorer, visit the website here.

Cohesity Data Cloud Updates and GenAI Detection and Recovery

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Liquid Web Launches High-Performance GPU Hosting with NVIDIA

Taylor Graham — Tue, 15 Oct 2024 21:00:01 +0000

Liquid Web introduced its new GPU hosting solution with flexible reserved and hourly pricing options. Tailored for developers needing substantial computational power, this platform is perfect for AI, machine learning (ML), rendering, and other demanding applications.

High-Performance GPU Hosting for Next-Generation Computing

Liquid Web’s GPU hosting services are built to meet the growing demand for environments that can handle high-performance computing (HPC) tasks. With the global AI market expected to grow from approximately $196.63 billion in 2023 to $1.81 trillion by 2030 (Grand View Research), (Research and Markets), the demand for accelerated computational power has never been higher. Leveraging powerful NVIDIA GPUs, this new offering accelerates computing speed, enabling businesses to process data-heavy workloads with greater efficiency.

“We’re thrilled to bring this highly performant platform to developers and innovators at an affordable price,” says Sachin Puri, Chief Growth Officer of Liquid Web. “AI has infinite untapped potential, and we want to empower developers and AI innovators to harness the full power of NVIDIA GPUs. With performance benchmarks that speak for themselves, this solution is the clear choice for accelerating AI workloads and maximizing value. And this is just the beginning — stay tuned as we expand our lineup to deliver even more powerful solutions in the near future.”

“Offering up to 15% better GPU performance over virtualized environments at equal or lower costs, our on-demand NVIDIA-powered servers with pre-configured GPU stack let customers quickly deploy AI/ML and deep learning workloads — maximizing performance and value while focusing on results rather than setup,” says Ryan MacDonald, Chief Technology Officer of Liquid Web.

Key Features of Liquid Web GPU Hosting

Accelerated Performance with NVIDIA GPUs: Leverage top-tier GPUs — including NVIDIA L4, L40S, and H100s — for exceptional processing speeds ideal for AI/ML, large language models (LLMs), deep learning, and data analytics.
Optimized for Data-Intensive Workloads: Enjoy low-latency, high-throughput networking and optimized configurations for demanding applications like scientific research and medical simulations.
On-Demand GPU Metal: Gain full control over your infrastructure with our powerful bare metal API and simple management portal.
Flexible Hosting Plans: Customize GPU accelerated metal hosting to meet your specific performance needs, whether you’re a startup or an enterprise.

Bare Metal GPU Solutions: Optimal for High-Performance Workloads

In the world of AI, machine learning, data analytics, and complex rendering, businesses demand maximum performance and efficiency from their GPU infrastructure. While virtualization technologies, such as NVIDIA’s Multi-Instance GPU (MIG), offer flexibility by partitioning GPU resources, bare metal GPU solutions stand out as the optimal choice for high-performance and latency-sensitive workloads.

Who Will Benefit?

Liquid Web’s GPU hosting is ideal for:

AI and Machine Learning: Accelerate training and inference of deep learning models, deploy real-time AI services, and host pre-trained large language models.
Data Analytics: Speed up big data processing and real-time analytics using GPU-optimized frameworks.
Content Creators: Handle large-scale rendering and video editing tasks efficiently.
Data Scientists: Perform big data analytics, simulations, and complex mathematical rigor with ease.
Game Developers: Speed up development times with enhanced graphics rendering.
Healthcare & Medical Imaging: Enhance diagnostics, image analysis, and simulations requiring high computational power.
High-Performance Computing: Support scientific research, climate modeling, genomics, and complex engineering simulations.

Why Liquid Web?

Liquid Web is known for providing high-performance hosting solutions backed by superior customer service. The new GPU hosting solution continues this tradition by delivering fast, secure, and scalable services for businesses that cannot afford downtime or delays.

“As more businesses integrate AI and machine learning into their workflows, the demand for robust GPU resources is skyrocketing,” adds MacDonald. “We’ve developed a solution that not only addresses this need but does so with the same quality and depth of expertise that our customers have come to rely on.”

Ready to Get Started?

For more information about Liquid Web’s GPU hosting solution or to get started, visit the website here.

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Slingshot AI Empowers Teams with New AI Features for Actionable Insights

Taylor Graham — Thu, 10 Oct 2024 15:00:47 +0000

Slingshot has unveiled new AI capabilities that enable teams to quickly make data-driven business decisions. With Slingshot AI, everyday users can now access clear, actionable insights from all company data sources—tracking performance, processes, people, and profitability across various departments, platforms, and channels—within seconds. These automated insights eliminate the need for manual data analysis, boosting productivity, accelerating decision-making, and allowing teams to focus on strategic tasks that drive business growth.

Companies today have more data than ever before, but their data is only as valuable as the insights it provides to teams. For many companies, data is spread across several systems, channels and gatekeepers. This leaves data inaccessible to teams and unable to offer comprehensive insights into the performance of an organization, departments and projects. Companies also can’t properly run AI when data is siloed like this because the technology needs to easily access data in one place, to learn from and make decisions. In fact, 45% of companies say they haven’t implemented AI because their organization’s data is not yet ready, according to the 2024 Digital Work Trends Report.

Slingshot has been solving for disparate data since its inception by centralizing companies’ data across multiple data sources and systems. By bringing together this data, the work management platform has created an AI foundation for companies, directly in its platform. Now, Slingshot is pairing this centralized data with conversational AI to automate insights for teams, so they can quickly access and analyze data to integrate it into their everyday workflows and decisions.

Quickly understand performance and identify trends to make informed business decisions.

Teams are already bringing together analytics from multiple data sources in Slingshot, including databases and spreadsheets (e.g. Excel and Google Sheets), SaaS systems, Big Data and Cloud data products (e.g. Google Analytics, BigQuery and Snowflake), and financial, marketing and sales tools (e.g. Salesforce Marketing Cloud, HubSpot and Marketo).

With Slingshot AI, teams can ask questions in simple business terms and receive an answer in seconds, based on an interpretation of company data. This AI-driven analysis saves teams hours of searching and sifting through data, so they can focus instead on making the data drive value for the business.

For example, teams can understand how their latest marketing campaign performed across different platforms or identify the most recent customer trends from CRM and sales data, without manually going through any of the data. A marketing team, for instance, may ask, “How much did we spend on advertising last year?” or “How is marketing spend distributed by channel?” Slingshot AI will deliver immediate insights and answers based on company data across departments, platforms and channels.

Create dashboards to visualize data.

Teams can also automate multi-source data visualizations to identify trends, assess performance and forecast the next best steps for the business or a given project. When teams ask questions about business performance and trends, Slingshot AI will create visualizations–or charts, graphs and other types of visuals–based on company data. These data visualizations offer teams a holistic view into data so they can quickly understand patterns that are important for their overall performance and strategy.

These automated visualizations can be easily added to a permanent dashboard within Slingshot, so teams can regularly review them and evaluate performance in real-time.

Empower every employee to be a data analyst.

Historically, data has been managed and analyzed by highly skilled data analysts with years of training. Slingshot enables everyday business users-–or employees without prior data analysis experience–to derive value from data.

Slingshot AI analyzes and visualizes every piece of data and puts it into understandable terms for teams. Slingshot users simply have to ask questions regarding their data, and they will receive actionable responses in seconds. This empowers teams to use data in their day-to-day work, because they understand the meaning behind it and can easily use it to make decisions and drive productivity.

Translate insights directly into action.

Slingshot’s AI capabilities enhance team collaboration and productivity by giving employees better access to both data and discussion highlights.

Data insights and visualizations created with AI can be seamlessly shared with other team members across Slingshot, creating alignment and setting a solid base for discussions and brainstorms. Slingshot AI also enables teams to summarize these discussions and extract action items. For instance, instead of reading through a week-long discussion after being out of the office, a team member can use Slingshot AI to summarize the discussion and understand what they missed in a few minutes. Teams can also automate action items from discussions or meeting notes, and immediately create tasks in Slingshot for team members to complete those action items.

“We’ve spent years building companies’ AI foundations as we created one place where companies can bring together all of their data, and now we’re giving teams the ability to act on that data quickly with automated insights,” said Dean Guida, Founder of Slingshot. “With Slingshot AI, we’re making it easy for every company to be a data-driven organization, to power better decisions, improve productivity, and ultimately, increase business growth.”

Slingshot is available as a desktop app (Mac and Windows) and mobile app (Apple App Store and Google Play) and via slingshot app.io.

Learn how Slingshot AI can unify your business data at the website here.

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Datanised Partners with Aerospike, MongoDB, and Redpanda

Taylor Graham — Fri, 27 Sep 2024 15:00:56 +0000

Datanised has formed strategic partnerships with top NoSQL and data streaming platforms, including Aerospike, MongoDB, and Redpanda. These collaborations enhance the startup’s technology portfolio and elevate its enterprise-focused services.

In today’s digital landscape, enterprises face significant challenges due to a chronic scarcity of specialized technology expertise, which is the most dire in fast-changing technologies such as NoSQL. Datanised was founded in early 2024, to fill this particular expertise gap, as a technology-agnostic partner linking enterprises and vendors judiciously.

Research shows that, in enterprises, a misalignment between business objectives and technology execution increases costs and inefficiencies. Datanised seeks to minimize that ratio.

“We have supported our clients with these technologies before, as independent experts. By becoming those vendors’ partners, we can directly access their respective teams and we can pass on the benefits of that core capacity to our clients,” said Ricardo Borenstein, Co-Founder & CTO at Datanised.

Flexible Technologies And Services Enabling Businesses To Scale

Through their procurement services, managed support, and expert guidance, Datanised have been giving businesses the tools and the confidence to harness the full potential of their technology investments. The company addresses the recent trend of shrinking IT budgets and growing demands head on.

“Our goal is simple: to ensure that businesses have access to the right expertise and cutting-edge solutions today, while staying flexible and scalable for future needs. These new collaborations help us to provide enterprises with expert guidance and technology solutions they need to optimize both their current and future technology investments,” says Hassib Massoumi, Co-Founder & CEO at Datanised.

With the addition of Aerospike, MongoDB, and Redpanda to their partnership roster, Datanised now offer first-class support for NoSQL and data streaming technologies. These platforms, known for their robustness, scalability, and performance, align well with Datanised’s mission of tailoring high-value solutions for enterprises.

Addressing The Skills Gap In The Market

According to the 2023 IT Skills Gap Report by Forbes Advisor, business that seek to address their IT skills gap fall into three large groups. Less than one third of UK businesses (30%) hire top IT talent; more than one third (34%) invest in IT training for their workforce, and 31% of companies prefer to outsource IT projects to focus on their core work. To each of these groups, Datanised offers a choice between four service levels.

Standard support and periodic consultations suit small to medium-sized enterprises whose in-house teams may need recurring external support. Enhanced support and regular performance-tuning are aimed at ambitious medium to large enterprises that may seek help with strategic data management. The highest level of expertise and ongoing management are practical for large enterprises in need of scalability, as more affordable than the endless hiring for growth. The managed service solution, which includes dedicated teams of database administrators and site reliability engineers, serves enterprises that prefer to outsource their mission-critical operations.

Users of all four service plans, from Standard to Pro+, benefit from customized solutions that Datanised tailors to their needs. All services dynamically evolve, in step with the changes in technology, market or the businesses’ demands.

“Some of our clients require enterprise-level licenses for the databases they use; some need their community editions, for regulatory requirements, exploration, or budgetary constraints. Our support of both proprietary and open source software (OSS) makes Datanised stand out and promises to be in high demand, as enterprises continue to look for flexibility and cost savings across their entire IT infrastructure,” said Hassib Massoumi, Co-Founder & CEO at Datanised.

Datanised offers a range of options—from optimization consulting, through customized solutions and facilitated procurement, to customer care plans, including managed services—while it stays technology and license-type agnostic. This flexible offering, unique in the market, allows Datanised to maximize the value their clients get from their technology investments.

“At Datanised, we know that technology isn’t one-size-fits-all,” said [Company Representative]. “Enterprises need a partner who not only understands the technical nuances, but can also deliver solutions that scale with their business. Our partnerships with Aerospike, MongoDB, and Redpanda bring exactly that – the right blend of innovation and practicality. We want to ensure that businesses working with us can navigate both present challenges and future opportunities with just the right investments in tech.”

Access to Expertise – And More

Another collaboration complements the current partnership drive at Datanised. By combining Anodot’s intelligent cost optimization platform with its own proprietary AI-driven cloud cost optimization tools, Datanised provides its clients with up-to-the-minute insights into how much they spend on any cloud capacity they use. The user-friendly solution helps their clients make data-driven decisions about their data-related costs.

The collaborations with Aerospike, MongoDB, Redpanda and Anodot will enhance all services that Datanised offers to customers, including procurement, technical support, in-house expertise, and training across their tech landscape. “We have just partnered with some of the major cutting-edge technology providers. We will continue to expand our partnerships with similar vendors, to better support our customers – modern enterprises,” says Hassib Massoumi, at Datanised said.

This strategic initiative reaffirms Datanised’s positioning as a trusted layer between enterprises and vendors, known for providing deep expertise, ongoing support, and the latest technology solutions. As their dependable partner in growth, the startup allows companies to focus on what matters most – their core business – while it ensures their database technology keeps pace.

For more information about Datanised and NoSQL specialty expertise, visit the website here.

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ManageEngine Rolls Out Analytics Plus Version 6.0, Spotlight

Taylor Graham — Tue, 24 Sep 2024 18:00:28 +0000

ManageEngine unveiled a major update to its flagship IT analytics platform, Analytics Plus. The new Version 6.0 introduces Spotlight, an AI-powered recommendations engine that provides contextual insights to pinpoint inefficiencies in IT operations and propose corrective actions.

The 2023 State of Analytics Engineering report found that time to business insight is the biggest challenge for nearly 50% of surveyed directors. Spotlight dramatically reduces the time IT managers and CIOs spend analyzing various IT metrics and coming up with remedies to fix structural fault lines in operations. By incorporating decision-intelligence capabilities, Analytics Plus now facilitates contextual decision-making, addressing a crucial gap in traditional analytics software.

For instance, Analytics Plus can analyze correlations between the age of IT assets, their frequency of failure, and the mean time to repair. Based on these parameters, it suggests the optimal time frame for asset replacement. This approach ensures that organizations neither dispose of assets prematurely, losing usable value, nor retain them for too long, negatively impacting employee productivity. With the introduction of Spotlight, ManageEngine reinforces its commitment to enhancing IT operations through intelligent, data-driven solutions.

“While traditional analytics tools excel at providing a platform for analyzing any type of data, they often lack the necessary context of the data they are analyzing. Deriving meaningful and context-specific insights is becoming increasingly challenging due to a significant disconnect: the people performing the analysis are skilled at mining data but often lack the IT context, making it difficult to translate findings into actionable business decisions,” said Samantha Hall, service delivery manager, Leathams Ltd., a UK-based food supplying company.

Analytics Plus’ built-in AI engine is programmed to study common IT processes and identify solutions to achieve desired results more quickly. Spotlight acts like an assistant, constantly monitoring for bottlenecks or operational inefficiencies and offering tips for corrective action. By bringing in IT context and leveraging AI capabilities, Analytics Plus ensures that organizations can address issues more effectively and efficiently.

“Organizations no longer want to spend hours mining data for actionable insights. They require ready-made strategies that they can implement immediately to see rapid results,” said Rakesh Jayaprakash, product manager and chief analytics evangelist at ManageEngine. He added, “There are sufficient tools in the market that promise automation and remediation for day-to-day network and application failures, but there’s a lack of focus on strategic decision-making. This is the gap Spotlight aims to bridge.”

Root Cause Analysis

Quick decision-making is only half the journey; IT managers and CIOs also need a way to backtest their decisions to ensure a new strategy or model will achieve the desired results. In addition to decision intelligence capabilities, ManageEngine is introducing the Root Cause Analysis feature, which automatically identifies the top factors contributing to a particular trend. This feature allows IT managers and CIOs to verify whether their changes or decisions are having a positive impact.

For instance, if tools are implemented for auto-remediation of L1 network issues, Root Cause Analysis can look at the increased uptime and highlight the reduction in L1 network issues as the major contributor to better network uptime.

No-Code Auto-ML for Deep Analysis

The new version of Analytics Plus empowers IT teams to create custom machine learning (ML) models without writing a single line of code. Traditionally, developing and deploying ML models was restricted to experts. However, Analytics Plus’ no-code ML platform democratizes this process, allowing IT managers to develop ML models directly on the data they are familiar with.

With this capability, IT managers can build ML models for prediction and classification, such as a predictive model to derive the probability of ticket escalations based on various factors or related events. This approach ensures the development of highly specific and accurate models because they are built on the organization’s unique data and validated by the very people who use it daily.

Unified IT Metrics Library

Analytics Plus serves as a command center and decision hub for IT by contextually analyzing all IT data, enabling organizations to cross-correlate metrics and identify interdependencies. Analytics Plus version 6.0 introduces the Unified IT Metrics Library, listing all KPIs from an IT environment in a single view, effectively acting as a comprehensive directory of metrics. This makes searchability and reusability easier, breaking down silos created by various IT tools and serving as a single source of truth for any metric that IT teams need to track.

“Traditional IT data analysis is often confined within individual tools. For instance, resolution time of incidents is limited to IT service management, while mean time to repair a device is restricted to IT operations management. This inhibits cross-correlation and prevents organizations from obtaining a complete picture of their IT infrastructure. By analyzing all these metrics together in a centralized platform, organizations can unlock significant value,” said Jayaprakash.

The Unified IT Metrics Library democratizes data by making a catalog of KPIs readily available for technicians to conduct their analyses, which can also be consumed by other IT applications for contextual integration. This comprehensive approach enhances governance and ensures that all relevant metrics are easily accessible and managed effectively, driving quick decision-making.

In addition to these key features, Analytics Plus version 6.0 includes a range of productive enhancements such as multivariate forecasting, workflow charts, support for distributed processing (on-premises) and more than 10 new integrations with popular IT tools. To learn more about Analytics Plus version 6.0 and Spotlight, visit the website here.

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HEAVY.AI and Vultr Partner to Boost Big Data Analytics with GPU Cloud Infrastructure

Taylor Graham — Tue, 10 Sep 2024 18:00:50 +0000

Vultr announced a partnership with HEAVY.AI, a provider of GPU-accelerated analytics platforms. By incorporating Vultr’s global NVIDIA GPU cloud infrastructure, HEAVY.AI can now interactively query and visualize large datasets, allowing customers in various industries to make quicker and more efficient decisions.

“Partnering with Vultr has allowed us to leverage their highly performant, global NVIDIA GPU cloud infrastructure to provide our customers with better access to unparalleled speed and efficiency,” said Jon Kondo, CEO of HEAVY.AI. “This integration ensures that our platform continues to deliver the rapid insights and cost savings that are critical for our customers’ success.”

Now, thanks to Vultr’s advanced GPU infrastructure, HEAVY.AI can deliver the best performance at an affordable price. The NVIDIA GH200 Grace Hopper Superchip joins NVIDIA A100 Tensor Core GPUs and Vultr Bare Metal instances to form a powerful trio that drives faster insights via HEAVY.AI’s platform. With the NVIDIA GH200 running on Vultr Cloud, HEAVY.AI can deliver 5X or greater price performance when compared to 8XA100 instances, completing industry-standard analytic SQL benchmarks such as TPC-H100 in less than 4.5 seconds, and executing 11 of the 22 queries in less than 100 milliseconds.

“Vultr is one of the first cloud providers to offer the revolutionary NVIDIA GH200 Grace Hopper Superchip,” said Todd Mostak, Co-Founder and CTO of HEAVY.AI. “By tapping into the immense GPU compute and CPU-GPU bandwidth that is unique to the NVIDIA GH200, we now can offer our customers even greater performance and scale while significantly reducing costs, empowering businesses to derive insights faster and more efficiently than ever before.”

Building on its mission to democratize access to big data analytics, HEAVY.AI offers a comprehensive software suite that allows organizations to query, analyze, and visualize complex datasets, with a particular focus on location and time series data. With performance that is often orders of magnitude faster than CPU-based solutions, HEAVY.AI provides analysts, data scientists, data engineers, and geospatial professionals across industries with a complete view of their data, helping them understand the “what, when, and where” with unparalleled clarity.

Through its collaborations with NVIDIA and now Vultr, HEAVY.AI has optimized its platform for the latest NVIDIA hardware to provide best-in-class performance, providing significant advantages to industries that rely on fast data processing. Specifically:

Energy: accelerating big data analytics for sectors such as renewable energy for wind, solar, and biomass.
Telecommunications: expediting faster and deeper understanding of LTE and 5G networks, and enhancing customer experiences.
Urban planning & smart cities: accelerating the sector with GeoAI solutions, which analyze urban data to optimize infrastructure, transportation, and public services; and driving advanced utility analytics on big smart meter, IoT, and Earth observation datasets, for hidden risks visualization, and uninterrupted uptime.
Environmental monitoring, geospatial intelligence, and disaster response: analyzing satellite and drone data to detect changes in land use; assessing damage from natural disasters faster; and automatic change detection and socio-economic analysis.

“As enterprises across sectors look to train and scale their models, they are looking for industry and use case-specific solutions to help them accelerate growth and innovation,” said Kevin Cochrane, CMO of Vultr. “Our partnership with HEAVY.AI is yet another example of Vultr being committed to unlocking the next frontier of GPU-accelerated analytics for some of the most data-intensive workloads across key sectors.”

This news follows the company’s recent launch of its industry cloud solution, which delivers industry-vertical, cutting-edge cloud computing solutions that meet specific industry needs and regulatory requirements. Through its partnership with HEAVY.AI, Vultr is reaffirming its commitment to both empowering customers across verticals and building an ecosystem of best-of-breed technologies, tools, and services that enable them to easily build and scale cloud-native and AI-native initiatives.

To learn more about the HEAVY.AI and Vultr partnership, visit the website here.

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Mobi.Ai Unveils Mobi IDS, Industry First Search and Discovery Tool

Taylor Graham — Fri, 06 Sep 2024 17:30:50 +0000

Mobi.ai has launched its groundbreaking search and discovery technology, Mobi Intent Driven Search (IDS). This innovative system integrates intuitive, natural language search with generative AI, leveraging Mobi’s proprietary database of over 40 million fully enriched global points of interest. By combining this vast content store with its advanced AI, Mobi IDS delivers optimal destinations, accommodations, and experiences for travelers, catering specifically to the needs of companies in the travel, tourism, and hospitality sectors.

AI is upending the industry and fundamentally changing how travel companies are interacting with customers. A recent report, The Promise of Travel in the Age of AI, produced by McKinsey and Skift Research, found that organizations that take advantage of the latest technological advancements “have the potential to see a 15 to 25 percent earnings improvement.”

“Search is changing in a big way with major browsers and most online travel agencies (OTA) embracing large language models like ChatGPT to offer natural language search,” said Mobi CEO and founder Anna Jaffe. “At Mobi, we leverage generative AI and LLMs to power natural language capabilities and understand guest travel intents. We then use a multimodal approach, combining our proprietary content with advanced planning and optimization AI, to deliver fast, accurate recommendations that meet guests’ specific requirements and desires.”

Mobi IDS ingests, cleans and structures data from multiple sources to provide real-time and accurate information about anything and everything surrounding any location or property, from dining and transportation options to activities, attractions, wildlife and more. This unlocks the ability to offer experience-led searches and provide specific recommendations for any customer query.

By enabling guests to ask personal questions with natural language, guests will share incredible insight into their likes, dislikes and behavior. These personal details can then be used to improve brands’ communications and marketing tactics. Mobi IDS can even integrate with client loyalty systems and booking engines to drive engagement and increase revenue capture.

“Most travelers know what they want to do on their next vacation, they simply don’t know where to go to pursue their passions,” said Mobi’s VP of Product Harriet Brown, who worked on the team that built and scaled the product behind Google Flights. “With IDS, hospitality companies don’t need to predict what a customer might want, they can listen to their intentions and provide a highly tailored recommendation of destination, property and activities to create their ideal adventure. This deep personalization will delight and inspire customers, and go a long way in building emotional loyalty.”

The basic implementation of Mobi IDS can be completed in just six weeks with custom enrichment of all client properties completed over the next two months. “Getting started with Mobi IDS is easy,” said Peng Yu, Mobi CTO and co-founder. “We’ve built a data pipeline capable of ingesting unstructured or structured data of any kind. We can accommodate any business logic or customer rules in configuration and we have a ready-made testing environment. This infrastructure is designed to get our clients from inspiration to implementation to value as quickly as possible.”

To learn more about Mobi IDC, visit the website here.

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Databricks Built-on Partner Program Newest Partner is Engine Data

Taylor Graham — Thu, 29 Aug 2024 15:00:56 +0000

Engine Data Science is excited to reveal its strategic alliance with Databricks through its Built-on Partner Program. This partnership represents a crucial step forward in our goal to provide state-of-the-art data science solutions and foster innovation in the Retail and CPG sectors.

By joining the Built-on Partner Program, Engine validates its underlying architecture with Databricks, utilizing best practices and modern patterns. This partnership demonstrates our ability to leverage Databricks’ Data Intelligence Platform to scale our SaaS offerings and enhance our capabilities in big data processing, machine learning, and artificial intelligence.

“Databricks is committed to bringing the power of data intelligence to every business,” said Sarah Branfman, Vice President of ISV Partner Sales. “Retailers need fast, powerful insights that drive decisive action and results for their business. Our partnership with Engine highlights our joint commitment to deliver a unified platform for data, analytics, and AI that powers those insights and scales as our customers do.”

This partnership will focus on Delta Sharing and Serverless, two major innovations by Databricks that enable Engine to drive efficiency and help organizations harness the full potential of their data. By combining Databricks’ scalable and secure platform with Engine’s deep CPG + Retail domain knowledge, the collaboration aims to deliver deeper customer integration and unparalleled access to data across customer clouds.

“We are excited to join the Databricks Built-on Partner Program and be the first to do so in our industry,” said Nick Dozier, CEO of Engine, “This strategic partnership underscores Engine’s commitment to harnessing next generation Data and AI technologies to drive customer success. I personally cannot wait to show our customers, partners, and the rest of the industry, the technology, and solutions that we are building, it’s going to change everything!”

To learn more about Databricks Built-on Partner Program, visit the website here.

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CAII Chooses SureImpact as its Impact Management Platform

Taylor Graham — Mon, 26 Aug 2024 20:00:24 +0000

SureImpact, Inc. announced its selection by the Collaborative Arts Impact Initiative (CAII) to assist member arts organizations in accurately tracking, measuring, and conveying their unique public value.

The Collaborative Arts Impact Initiative is an innovative collective aimed at transforming how the arts communicate their significance. The initial CAII pilot will involve 15 non-profit arts organizations. The software platform is designed to be scalable for arts organizations worldwide. Led by Meleca Creative Advisors, in partnership with Measurement Resources Company, the sole purpose of this initiative is to empower non-profit arts organizations to redefine their impact stories. This reframing aims to more clearly define the essential role of the arts in promoting community empathy, creativity, kindness, and job preparedness – qualities crucial to society’s flourishing.

“Partnering with SureImpact will assist arts organizations in collecting impact data aligned with a shared measurement framework. This data will seamlessly integrate into our collaborative dashboard, providing a comprehensive quantification of the arts’ overall impact and public value,” stated Angela Meleca, CEO of Meleca Creative Advisors and the visionary behind the CAII. “We aim to enable each arts organization to capture their impact in real-time and contribute to a collective narrative that highlights the essential contributions of the arts to society. With SureImpact, our goal is to convert impact into increased investments for the arts.”

Given the concerning decrease in arts funding, with a 19% decline in public support over the past two decades when adjusted for inflation, the CAII aims to show that organizations that can prove their impact with data attract more investment and achieve better results.

“This collective impact initiative stands as a testament to the transformative power of collective action and measurable results in the arts sector,” said Sheri Chaney Jones, CEO of SureImpact and Founder of Measurement Resources Company. “We are honored to partner with the Collaborative Arts Impact Initiative to help them use impact data to reshape and retell their story, reclaim relevance in communities, and raise additional revenue to ensure long-term sustainability.”

The partnership between SureImpact and the Collaborative Arts Impact Initiative marks a significant step forward in demonstrating the indispensable role of the arts in society. By harnessing the power of real-time impact data, CAII and its member organizations are poised to not only reshape their narrative but also drive increased investment and support for the arts. This initiative is more than just a response to declining funding; it is a proactive effort to ensure the arts remain a vital and sustainable force for community development and societal well-being.

To learn more about the Collaborative Arts Impact Initiative (CAII), visit the website here.

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BMC Study Reveals Opportunities for Enterprises to Leverage Emergent Data

Taylor Graham — Thu, 25 Jul 2024 19:00:34 +0000

BMC has published findings and analysis from its survey and report, Putting the “Ops” in DataOps: Success Factors for Operationalizing Data. This second annual survey of IT decision-makers offers insights into how enterprises can evaluate and improve their data maturity strategies to gain a competitive edge. Additionally, a complementary data maturity assessment helps companies assess their current status and offers recommended next steps.

As organizations strive to capitalize on their ever-growing data trove to scale their operations and improve business outcomes, the study found that only 17% of data ingested or landed consists of emergent data types, and only 9% of that data is processed or analyzed. This signals a significant opportunity to benefit from emergent data types critical for initiatives like generative AI, LLMs, FinOps, and sustainability.

To help enterprises better understand and assess their data and DataOps strategy, the study defined four maturity levels, including:

Developing – discovery phase with strategies in their infancy, and practices and architecture not closely aligned to business outcomes.
Functional – growth phase with strategies primarily developed and some high-priority practices and architecture linked to business outcomes.
Proficient – adolescent phase representing a fully established strategy with nearly all practices and architecture linked to critical business outcomes.
Exceptional – innovation phase with a perpetually optimized strategy, practices, and architecture that generates competitive differentiation and business value.

DataOps strategy is closely aligned with data management maturity. Of those respondents with exceptional data management maturity, 27% stated they use DataOps methodologies across their organization to support all data-driven activities. In comparison, those with proficient maturity levels reported 19%, and functional and developing levels stated 15% and 10%, respectively. Even among organizations with exceptional data maturity, only 41% report having “high maturity” for data pipeline and application workflow orchestration functions.

Higher data management and DataOps maturity are linked to higher reported adoption and success with data-driven activities. Seventy-five percent (75%) of those with mature practices have a Chief Data Officer, while only 54% with less mature practices do.

Challenges Obstruct Flow of Data

Multiple challenges continue to impact the flow of data in businesses, including those related to people, processes, and technology. These include a lack of skills (48%), human error and mistakes (43%), limitations on scalability (40%), and a lack of technology automation (43%). A lack of automation can exacerbate a lack of skills, while an appropriate use of automation can amplify skills already available.

“AI and data are in a cosmic dance, and data challenges are increasing dramatically in the AI era,” said Ram Chakravarti, chief technology officer at BMC. “This study highlights how organizations with mature data practices can achieve better business outcomes. Implementing DataOps methodologies to enhance collaboration and operational efficiency, maintaining high data quality through pragmatic investments, and developing robust data pipeline orchestration systems can help unlock value at scale.”

BMC commissioned 451 Research, part of S&P Global Market Intelligence, to conduct the survey in late 2023, sourcing insights from 1,100 IT, data, and business professionals from large enterprises in diverse global regions across multiple industries in eleven countries.

To learn how to better understand and assess emergent data, download Putting the “Ops” in DataOps: Success factors for operationalizing data here.

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