Somesh Saxena’s Post

It has been over 2 years since Gartner started a research in Data Observability market. I have seen this technology growing tremendously. Not really a surprise, because it bridges a gap that traditional monitoring tools cannot do. If you think GenAI is #1 technology in the market catching the spotlight, I will say Data Observability is #2.  Take a look at the Gartner new research “Market Guide for Data Observability Tools”, that provides the market definition ( 4 critical features + 5 observation categories), market direction (growing in demand and expending in coverage areas), market analysis (different from data quality solutions, and APM tools), and market segments (standalone/pure player and embedded capabilities), and representative vendors.  Big thank you to my co-authors Jason Medd, Lydia Ferguson, Michael J. Simone! “Market Guide for Data Observability Tools”: Access the research from https://lnkd.in/gTMXj9fu  (Available for Gartner members only) #dataobservability #datamanagement #gartnerda #dataquality #GartnerDnA

“If you think GenAI is #1 technology in the market catching the spotlight, I will say Data Observability is #2.”- Melody Chien Based on the interest and engagement we at #acceldata are seeing from enterprises, there’s definitely a case for it. Thank you Melody Chien Jason Medd Lydia Ferguson Michael J. Simone for this comprehensive analysis on Data Observability.

We love to talk about AI, but I agree with Melody Chien. Here is what she has to say: "If you think GenAI is #1 technology in the market catching the spotlight, I will say Data Observability is #2." Although AI has the #1 spotlight, I would argue that Data Observability shares that spotlight as it pertains to importance and critical functionality. The only way you have a strong and reliable AI tool is by investing in your data through data observability. It has to be enterprise grade and have the capabilities to see across the entire data journey no matter how complex it might be. Businesses don't want to be left behind in the AI race, but the word of caution is to not overlook the foundation data observability will help build. Investing the time and effort in it will bear the fruit you expect with the innovation of your new AI tools. Bad data leads to...bad outputs leads to...loss of credibility...leads to loss of market share...and on and on and on. #dataobservability #datareliability #acceldata #dataquality #AI #gooddata #baddata #models #llms #data

If you think GenAI is #1 technology in the market catching the spotlight, I will say Data Observability is #2 Melody Chien took the words out of my mouth with this one. Every CDO/CIO I speak to is concerned with one thing: making the organization AI-ready, and that naturally pushes Data Observability to the top of their agenda. Gartner strikes again with the first-ever market guide for Data Observability! My key takeaways: - Adoption of Data Observability is growing, fast. By 2026, 50% of enterprises implementing distributed data architectures will have adopted data observability tools to improve visibility over the state of the data landscape, up from less than 20% in 2024. - Gartner sees two categories of vendors: embedded (point solutions) and standalone (independent vendors). I see two categories in the standalone part: Platforms (like Sifflet) and point solutions. - The scope of Data Observability and the expectation from enterprises are also growing. Gartner identifies 5 main areas of coverage (incl. FinOps & users/usage utilization) vs two previously (data flow & data content monitoring). This is the power of holistic Data Observability, specifically platforms like Sifflet. You’ll have to read the report to find out more. Stoked that Sifflet is once again mentioned in Gartner research and the first ever market guide. Well done to Melody Chien Jason Medd, Lydia Ferguson, Michael J. Simone for a great research piece. #dataobservability

Insights from Gartner’s recent research on Data Observability tools! 📊 "Data Observability" may not be a hot topic for most in the way #GenAI is currently however in the era of data-driven decision making, ensuring the health and reliability of our data is more crucial than ever. Gartner’s report highlights the growing importance of data observability in maintaining data quality, uncovering hidden data issues, and enhancing overall data trust. It's great to see the advancement of tooling in this area, however, when it comes to successful enterprise Data Strategy, a tool on its own, will never solve the actual problem. 🔍 Key takeaways for Data Observability: 💡 Proactive Data Monitoring: Shifting from reactive to proactive monitoring to catch anomalies early. 💡 Improved Data Quality: Ensuring data consistency and reliability across all platforms. 💡 Enhanced Data Lineage: Understanding the flow and transformation of data for better transparency and governance. 💡 Boosted Efficiency: Leveraging AI and machine learning to automate data quality checks and streamline operations. As we continue to deliver robust Data & AI strategies in Spark, integrating data observability best practice remain a core priority. #DataObservability #DataQuality #AI #MachineLearning #GartnerReport #DataDriven

Just finished the Gartner D&A Summit. The world of D&A is changing very fast and it is not just fuelled by GenAI. It was great to see sessions covering a vast array of topics from data management, quality, business focused metrics, searching data, decision intelligence and how to allocate financial resources effectively. The mountain of data is truly a never ending journey. I recommend anyone who is a data profoessional, both leader and contributor or just a fan of data should attend. We are calling it analytical heft because without data capabilities, business are lacking the weight to be able to deliver the value they require to be the best in their respective industries. Ian Phoenix Zak Watson Fern Watson Manoj Chalamcherla #gartnerdatasummit

DataWalk, the industry leader in graph analytics software, has been referenced in four different 2023 Gartner® Hype Cycle™ reports. Gartner generates Hype Cycles to assess the maturity and potential of emerging technologies across various market sectors. These provide a framework for understanding the various stages in technology adoption, and can provide insights into where investments should be made or avoided. DataWalk is referenced as a vendor in the following Gartner Hype Cycles:  Hype Cycle for Analytics and Business Intelligence, 2023 (Graph Analytics)   Hype Cycle for Data and Analytics Programs and Practices, 2023 (Graph Analytics)   Hype Cycle for Public Safety and Law Enforcement, 2023 (Public Safety Predictive Analytics)   Hype Cycle for Digital Government Services, 2023 (Predictive Analytics in Government) Gartner recognized DataWalk as technology at the “early mainstream” maturity stage in all categories

At Gartner, we've just published our "Voice of the Customer for Analytics and Business Intelligence Platforms". The “Voice of the Customer” is a document that synthesizes Gartner Peer Insights’ reviews into insights for IT decision makers. In the analytics and business intelligence platforms market, Gartner Peer Insights has published 4,124 reviews and ratings in the 18-month period ending 31 July 2023. This aggregated peer perspective, along with the individual detailed reviews, is complementary to Gartner expert research and can play a key role in your buying process, as it focuses on direct peer experiences of implementing and operating a solution. What Are Analytics and Business Intelligence Platforms? Analytics and business intelligence (ABI) platforms enable less technical users, including business people, to model, analyze, explore, share and manage data, and collaborate and share findings, enabled by IT and augmented by artificial intelligence (AI). Many platforms are adding capabilities for users to easily compose low-code or no-code automation workflows and applications. This blend of capabilities is helping to expand the vision for analytics beyond simply delivering datasets and presenting dashboards. Today’s ABI platforms can deliver enriched contextualized insights, refocus attention on decision-making processes and ultimately take actions that will deliver business value. Gartner clients can read this brand new research here: https://lnkd.in/dqxEpXXr #Analytics #BusinessIntelligence #Gartner #ABI #Data #DataAnalytics #GartnerSym #GartnerSymposium

Worth the Hype? Real-time #DataAndAnalytics demand is a priority, especially in uncertain times. The new report “Hype Cycle™ for Data and Analytics Programs and Practice, 2023” from Gartner® intends to help you explore strategies to meet this demand effectively.   Get complimentary access ➡️ https://lnkd.in/eEnWizcR ❗️ Access only available for a short time ⏳ #HypeCycle #Gartner #dataleadership