Latest news with #Gartner
Channel Post MEA
7 hours ago
- Business
- Channel Post MEA
SAS Announces AI Models and Solutions For Health Care Industry, Payer Organizations
SAS has announced a new solution – SAS Health Cost of Care Analytics – targeted to health care payers and providers to support effective decision making about quality and cost of care. Available in July 2025, SAS Health Cost of Care Analytics taps into health claims data and enables health care organizations to construct and analyze claims as episodes of care by stitching together codes and patterns all along a 'care journey' from detection to treatment to care management. The health care analytics solution built on the data and AI platform SAS Viya can enable more cost-effective treatment pathways, reduce unwarranted admissions, decrease the length of hospital stays and more. SAS will introduce SAS Health Cost of Care Analytics and other data and analytic solutions for health care payers and the industry at AHIP 2025 in Las Vegas. Per Gartner, 'Payers increasingly need sophisticated data and analytics to achieve outcomes such as identifying rising risk populations, improving quality measure performance, managing the total cost of care and personalizing experiences.' SAS Health Cost of Care Analytics supports the industry with unique features that include: Flexible definitions for episodes of care. Users can analyze claims as episodes of care using transparent clinical definitions of their choice and detect associations for a holistic patient view. Users can analyze claims as episodes of care using transparent clinical definitions of their choice and detect associations for a holistic patient view. Value and care outcome measurement. The solution categorizes services and their care costs as being value-added or potentially avoidable. Additionally, expected and risk-adjusted costs are automatically calculated and can then be used as quality/efficiency measures or payment metrics. Other quality metrics, such as length of stay, are also captured. The solution categorizes services and their care costs as being value-added or potentially avoidable. Additionally, expected and risk-adjusted costs are automatically calculated and can then be used as quality/efficiency measures or payment metrics. Other quality metrics, such as length of stay, are also captured. Risk-based calculations to compare provider performance. Using medical claim data and applying user-selected rules, the solution attributes episodes of care to providers, facilitating the measurement of cost and quality of care relative to patient severity or to set reimbursement targets. Using medical claim data and applying user-selected rules, the solution attributes episodes of care to providers, facilitating the measurement of cost and quality of care relative to patient severity or to set reimbursement targets. Analytic insights with simplified data management. The product supports data validation and simplified data ingestion into the SAS Health common data model to create data repositories. 'As health care incentives focus in on value, providers and payers must identify the drivers of cost, quality and outcomes to make decisions about protocols and provider contracts,' said Brett Davis, Senior Manager, Health Care Advisory at SAS. 'Going far beyond traditional claims grouping, SAS Health Cost of Care Analytics generates valuable insights to identify variations and opportunities for improvement when assessing financial risk, all while understanding members in more detail.' Ready-made AI models for health care Also new on the market to support payers and providers are ready-made AI models. Complementing its health care solutions portfolio, SAS' AI models are built from decades of expertise in applying scalable and trustworthy AI to real-world use cases and are designed to tackle business challenges with precision and efficiency. The newly available models include: SAS Medication Adherence Risk : Medication adherence has long been a measure of patient health outcomes and a key factor in regulatory quality assessments (e.g., quality ratings for Medicare Advantage, Medicaid and Exchange). SAS Medication Adherence Risk enables managed care organizations to identify where resources are needed for timely and targeted intervention, resulting in enhanced patient engagement, better health outcomes, improved quality metrics and lower health care costs. : Medication adherence has long been a measure of patient health outcomes and a key factor in regulatory quality assessments (e.g., quality ratings for Medicare Advantage, Medicaid and Exchange). SAS Medication Adherence Risk enables managed care organizations to identify where resources are needed for timely and targeted intervention, resulting in enhanced patient engagement, better health outcomes, improved quality metrics and lower health care costs. SAS Document Analysis : The SAS Document Analysis model is an intelligent document processing pipeline focused on extracting contextual information from scanned document images and generating structured data assets. The AI model converts scanned images into summarized data for medical reviewers, allowing them to evaluate records more effectively and efficiently. The SAS Document Analysis model's enhanced analysis of unstructured claims data has already shown a 400% efficiency gain over manual review in one of the largest U.S. health insurers. : The SAS Document Analysis model is an intelligent document processing pipeline focused on extracting contextual information from scanned document images and generating structured data assets. The AI model converts scanned images into summarized data for medical reviewers, allowing them to evaluate records more effectively and efficiently. The SAS Document Analysis model's enhanced analysis of unstructured claims data has already shown a 400% efficiency gain over manual review in one of the largest U.S. health insurers. SAS Payment Integrity for Health Care Detect and Prevent: The payment integrity models offer capabilities for addressing issues with health billing errors and claim discrepancies, detecting fraud and preventing improper claims. The models are designed to accelerate implementation of SAS solutions that health care programs within private insurance plans and government-funded programs use to meet regulatory compliance requirements, operate transparently, and more efficiently manage and contain costs associated with fraud, waste and abuse.
Yahoo
16 hours ago
- Business
- Yahoo
Accenture (ACN) Q1 Earnings: What To Expect
Global professional services company Accenture (NYSE:ACN) will be reporting earnings this Friday before the bell. Here's what investors should know. Accenture beat analysts' revenue expectations by 3.2% last quarter, reporting revenues of $17.69 billion, up 9% year on year. It was a very strong quarter for the company, with a decent beat of analysts' EPS estimates. Is Accenture a buy or sell going into earnings? Read our full analysis here, it's free. This quarter, analysts are expecting Accenture's revenue to grow 5.4% year on year to $16.61 billion, improving from its flat revenue in the same quarter last year. Adjusted earnings are expected to come in at $2.81 per share. Analysts covering the company have generally reconfirmed their estimates over the last 30 days, suggesting they anticipate the business to stay the course heading into earnings. Accenture has missed Wall Street's revenue estimates three times over the last two years. Looking at Accenture's peers in the it services & consulting segment, some have already reported their Q1 results, giving us a hint as to what we can expect. EPAM delivered year-on-year revenue growth of 11.7%, beating analysts' expectations by 1.6%, and Gartner reported revenues up 4.2%, in line with consensus estimates. EPAM traded up 11.1% following the results while Gartner was also up 2.3%. Read our full analysis of EPAM's results here and Gartner's results here. Investors in the it services & consulting segment have had fairly steady hands going into earnings, with share prices down 1.1% on average over the last month. Accenture is down 3.7% during the same time and is heading into earnings with an average analyst price target of $353.80 (compared to the current share price of $308.49). When a company has more cash than it knows what to do with, buying back its own shares can make a lot of sense–as long as the price is right. Luckily, we've found one, a low-priced stock that is gushing free cash flow AND buying back shares. Click here to claim your Special Free Report on a fallen angel growth story that is already recovering from a setback. Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Al Bawaba
a day ago
- Business
- Al Bawaba
Gartner Predicts 75% of Analytics Content to Use GenAI for Enhanced Contextual Intelligence by 2027
Seventy-five percent of new analytics content will be contextualized for intelligent applications through generative AI (GenAI) by 2027, enabling composable connection between insights and actions, according to Gartner, Inc.'We're moving from an era where analytic tools help business people make decisions, to a future where GenAI-powered analytics becomes perceptive and adaptive,' said Georgia O'Callaghan, Director, Analyst at Gartner. 'This will enable dynamic and autonomous decisions that have the potential to transform enterprise and consumer software, business processes and models.'A Gartner survey of 403 analytics or AI leaders, conducted between October and December 2024, revealed over 50% report their organizations use AI tools for automated insights and natural language queries (NLG) for analytics or AI development. Even with these capabilities, the static nature of current analytics often falls short of delivering in a truly dynamic and automated predicts augmented analytics capabilities will evolve into autonomous analytics platforms by 2027, which will fully manage and execute 20% of business processes. The perceptive future of analytics will deliver benefits by being proactive, collaborative, connected, contextual and continuous (see Figure 1).Figure 1: AI-Powered, Perceptive AnalyticsSource: Gartner (June 2025)'Perceptive analytics will use AI agents and other GenAI-fueled technologies to continuously monitor evolving conditions and perceive the target environment, such as market shifts, customer behavior changes or supply chain disruptions,' said O'Callaghan.'Guidance and analysis can then be autonomously adjusted in response, creating a more resilient and responsive analytical infrastructure. As these capabilities emerge and be adopted by organizations, their potential to reshape business operations and drive growth will only continue to expand.'Perceptive Analytics Overarching RiskAccording to Gartner research, the overarching risk that applies to perceptive analytics is the over reliance on autonomous actions without sufficient validation, which could result in unintended negative consequences, reputational damage and regulatory risk of "agent drift" is a serious concern, where a system's perceptions and actions gradually deviate from desired outcomes due to evolving data or unforeseen interactions. Guardian agents are emerging to deal with this inherent issue in AI systems, according to Gartner. These agents are specifically tasked with monitoring and enforcing policies and rules to ensure the systems operate within a set of guardrails. 'Building guardian agents will need to be a key focal point of new governance initiatives for data and analytics leaders, as agentic and perceptive analytics become the standard way of insight delivery across platforms,' said O'Callaghan.
Miami Herald
2 days ago
- Business
- Miami Herald
GoodData Recognized in 2025 Gartner(R) Magic Quadrant(TM) for Analytics and BI Platforms
GoodData recognized by Gartner® for ability to execute and completeness of vision. SAN FRANCISCO, CA / ACCESS Newswire / June 18, 2025 / GoodData, the AI-native analytics platform, today announced its inclusion in the 2025 Gartner® Magic Quadrant™ for Analytics and Business Intelligence Platforms. Recognized as a Niche Player, GoodData was acknowledged for its ability to execute and completeness of vision. At the core of GoodData's platform is its composability strategy, powered by open source technology, multi-tenancy framework, and an open semantic layer, giving data teams the ability to define metrics once and reuse them across every dashboard, application, or tool in the enterprise. This ensures consistent, governed insights at scale while aligning analytics with business logic and objectives. "GoodData was built for a world where analytics isn't a nice-to-have. It is a critical part of the enterprise data landscape, and we believe that our inclusion in the Gartner Magic Quadrant is a testament to the demand for interoperable analytics platforms that treat analytics as code and fit seamlessly into the modern DevOps and product development lifecycle." Roman Stanek, CEO and Founder of GoodData. With its analytics-as-code approach, GoodData enables development teams to build and extend data experiences like any other software component. This empowers teams to automate development with CI/CD pipelines, fully customize the user experience through APIs and embedded components, and ensure trust in the data through automated testing and version control. Additionally, GoodData's commitment to interoperability sets it apart. Native features like FlexConnect and metadata ingestion from third-party BI tools allow teams to unify data across silos and ecosystems without duplicating or moving data. The platform's zero-copy architecture enhances performance while maintaining data integrity and governance. "GoodData's flexibility to integrate into any backend setup has proven to provide maximum flexibility for our engineering needs." VP, Product in the Banking sector; from Gartner® Peer Insights™ review "The future of BI is not in monolithic dashboards - it's in flexible, embedded, and governed insights that live where decisions are made. By focusing on analytics-as-code and end-to-end composability, we're equipping data and product teams with the tools they need to innovate faster and smarter." Ryan Dolley, VP of Product Strategy at GoodData In our opinion, GoodData's position in the Magic Quadrant underscores a market shift toward developer-centric analytics platforms that seamlessly integrate into today's complex data stacks and product environments. Read the full Gartner® Magic Quadrant™ report to see a complete analysis of GoodData's strengths and cautions. GARTNER is a registered trademark and service mark of Gartner and Magic Quadrant and Peer Insights are a registered trademark, of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved. Gartner Peer Insights content consists of the opinions of individual end users based on their own experiences with the vendors listed on the platform, should not be construed as statements of fact, nor do they represent the views of Gartner or its affiliates. Gartner does not endorse any vendor, product or service depicted in this content nor makes any warranties, expressed or implied, with respect to this content, about its accuracy or completeness, including any warranties of merchantability or fitness for a particular purpose. Gartner does not endorse any vendor, product or service depicted in its research publications and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. About GoodData GoodData is the AI-native analytics platform built for speed, scale, and trust, helping companies deliver real-time insights - embedded, branded, and everywhere your users need them. Founded in 2007, and with offices in both the U.S. and Europe, GoodData serves over 140,000 of the world's top companies and 3.2 million users, helping them drive meaningful change and maximize the value of their data. For more information, visit GoodData's website and follow GoodData on LinkedIn, YouTube, and Medium. GoodData Contactpress@ ©2025, GoodData Corporation. All rights reserved. GoodData and the GoodData logo are registered trademarks of GoodData Corporation in the United States and other jurisdictions. Other names used herein may be trademarks of their respective owners. SOURCE: GoodData
Yahoo
2 days ago
- Business
- Yahoo
Sigma is on the Gartner® Magic Quadrant™ for Analytics and Business Intelligence
This is the first time Sigma has been recognized. SAN FRANCISCO, June 18, 2025--(BUSINESS WIRE)--Sigma, the industry-leading analytics platform with unique cloud data platform write-back capabilities, today announced its recognition in the 2025 Gartner® Magic Quadrant™ for Analytics & Business Intelligence Platforms as a Niche Player. Sigma's first-time recognition in the 2025 Magic Quadrant comes on the heels of being named the 2025 Databricks Business Intelligence Partner of the Year and for the third year in a row, Snowflake's Business Intelligence Data Cloud Product Partner of the Year. Sigma believes this first-time placement confirms what more than 1,400 customers already know: Sigma is leading the next generation of business intelligence. "Sigma was built for this moment—the convergence of AI, cloud-scale data, and the need for business agility," said Mike Palmer, CEO of Sigma. "Our 1,400-plus customers enjoy the freedom of true self-service analytics, smarter decisions through governed AI, and a platform that turns data into action through data apps." Unlike traditional platforms, Sigma puts the cloud data warehouse at the center to deliver unmatched performance, scale, and flexibility. The platform enables teams to build robust data models, analyze data at scale, and tap into warehouse-native AI—all without moving data or sacrificing governance. Sigma's spreadsheet interface makes self-service analytics a reality for business users, while more technical users can work in SQL or Python alongside them. And with Sigma's generative intelligence interface, Ask Sigma, customers can build AI into their data workflows and ask complex data questions that receive auditable answers. Sigma also makes it easier than ever to turn complex business processes into interactive, data-driven apps that combine live data, workflows, and user input directly on the customer's cloud data warehouse. As of June 18, 2025, Sigma holds a 4.8 out of 5 rating on Gartner® Peer Insights™ from 97 all time ratings, with 92% of customers recommending the platform. Examples of customers who have leveraged Sigma to improve business decisions can be found here. Access the full Gartner® Magic Quadrant™ for Analytics & Business Intelligence Platforms to see why Sigma was recognized. Gartner Disclaimer Gartner does not endorse any vendor, product or service depicted in our research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, Peer Insights and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved. Gartner, Voice of the Customer for Analytics and Business Intelligence Platforms, 20 Dec 2024. Gartner, Magic Quadrant for Analytics and Business Intelligence Platforms, 13 June 2025, Anirudh Ganeshan, Edgar Macari, Jamie O'Brien, Kurt Schlegel, Christopher Long About Sigma Sigma is business intelligence built for the cloud. With a spreadsheet UI, business users can work in the formulas and functions they already know, while more technical users can write SQL and apply AI models to data. Sigma queries the cloud warehouse directly, making it incredibly fast and secure—data never leaves the warehouse, and Sigma can analyze billions of rows in seconds. Beyond dashboards and reports, teams use Sigma to build custom data apps, which integrate live data with end user input. Sigma is the first analytics platform to enable data write-back, and continues to lead the market with innovation across AI, reporting, and embedded analytics. View source version on Contacts press@ Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
