CAMPBELL, Calif., February 6, 2024 — accelerator datathe market leader in enterprise data observability, today announced industry-first AI technology that enables DataOps teams to deliver advanced AI-assisted data observability that adapts to their unique business context.
While traditional approaches to AI for data observability have been black boxes, Acceldata’s technology gives enterprises the ability to tailor AI for data observability to their unique technical environments and business scenarios. We provide. This includes providing the desired guardrails to ensure business context, regulatory requirements, and the right balance between human oversight and AI autonomy are taken into account.
“Artificial intelligence has the potential to fundamentally change the way enterprise data is managed,” said Rohit Chaudhary, co-founder and CEO of AccelData. “Our innovative approach allows companies to tailor AI-assisted data observability to adapt and fit their specific operational and business needs, setting us apart in the industry. Built on this AI technology, AI Copilot eliminates the hassle of manual configuration, reduces setup time, enables automatic monitoring of data anomalies, and encourages collaboration and contribution from non-technical users. Masu.”
Amid the explosive adoption of AI, modern enterprises are seeking greater control over their AI models to avoid undesirable effects such as poor model performance and reduced reliability. Following the acquisition of Bewgle, a leading artificial intelligence platform, Acceldata is addressing the needs of enterprises by introducing the new AI CoPilot in its all-in-one enterprise data observability platform.
Key benefits of Acceldata’s AI CoPilot are:
- Anomaly detection – Improve data reliability and ensure data reliability by investigating and alerting on anomalies in data freshness, data profiling, and data quality changes.
- Cost management and forecasting – Automatically learns cost consumption patterns, including seasonality, and alerts users to prevent out-of-control consumption. Predict consumption based on learned behavior.
- Automate the enforcement of rules and policies – Streamline bulk policy creation by leveraging generative AI and large-scale language models (LLM) to reduce effort and prevent errors and omissions caused by human oversight.
- Generating data asset descriptions – Automatically generate human-readable descriptions of data assets, policies, and rules, facilitating seamless communication between technical and business owners of data assets.
According to Gartner, “Data observability, driven by active metadata and AI/ML, improves the trust in data and data ecosystems by increasing the ability to observe change and discover the unknown. Data and analytics leaders must understand and leverage its capabilities and benefits to ensure data reliability and reliability.” by Gartner Analysts Melody Chien and Ankush Jain. 2023 Data and Analytics Essentials: Data Observability Report.
As businesses across industries continue to experience a rapid influx of data, Acceldata has proven to be a key solution for driving success with the most complete all-in-one enterprise data observability solution. With the introduction of his industry-first AI capabilities, the company solidified its position as a leader in data management by providing teams with the most innovative technology to build and operate best-in-class data products.
If you would like to learn more, please visit here https://www.acceldata.io/ai.
About accelerator data
Founded in 2018 and based in Campbell, California accelerator data has developed the world’s first enterprise data observability platform that enables companies to build and operate superior data products. Acceldata’s solutions are used by customers around the world including Dun & Bradstreet, Nestle, PubMatic, PhonePe (Walmart), and HCSC. Acceldata’s investors include Insight Partners, March Capital, Industry Ventures, Lightspeed, Sorenson Ventures, Sanabil, and Emergent Ventures. Contact us to learn more about the benefits of data observability.
Source: Accel Data
