Grid Dynamics Introduces AI-Powered Data Observability Starter Kit, Extending Its Analytics Platform Offering

In This Article:

Key Takeaways:

  • The AI-powered Data Observability Starter Kit from Grid Dynamics helps clients ensure data quality, enabling them to develop AI solutions more rapidly and maintain operational integrity.

  • The capabilities of this new starter kit are vital in today’s data driven world, delivering comprehensive data quality checks across diverse data sources, including anomaly detection and statistical distribution checks, for both structured and unstructured data.

  • To accelerate time-to-market, the Data Observability Starter Kit offers clients a range of pre-built integrations with major data platforms and data warehouses.

  • The new starter kit extends the capabilities of Grid Dynamics’ Analytics Platform to provide clients with a comprehensive set of pre-packaged enterprise data services.

SAN RAMON, Calif., July 25, 2024--(BUSINESS WIRE)--Grid Dynamics Holdings, Inc. (NASDAQ: GDYN) (Grid Dynamics), a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services, today announces its Data Observability Starter Kit—an AI-powered solution designed to help businesses ensure data quality across their data transformation processes and data platforms. This is a vital capability in today’s data-driven world because businesses operate with high-volumes of diverse data from multiple sources. The ability to identify issues with data and stop the propagation of broken data to downstream applications, or to prevent data issues from corrupting sales reports and dashboards, is invaluable for businesses to make informed decisions and maintain operational integrity. Data quality also has a significant impact on the ability to develop and productize AI solutions.

The AI-powered Data Observability Starter Kit from Grid Dynamics simplifies data quality onboarding and provides a range of comprehensive checks, ensuring that clients can effectively monitor data quality across all of their data types. It provides checks for tubular data, structured and unstructured data, including additional built-in quality checks for null, missing, or empty values, statistical distribution checks, data freshness, data volume checks, and unsupervised learning models for anomaly detection.

"Data observability is one of the top concerns for our clients," said Ilya Katsov, Vice President of Technology at Grid Dynamics. "The Data Observability Starter Kit provides them with a flexible framework that can flag anomalies such as unusually high/low numerical values in individual data elements, misformatted values, records lost due to data replication errors, and others. The kit uses AI models to simplify the configuration and maintenance of the data quality checks making the solution much more usable and efficient than rule-based systems."