Grid Dynamics Holdings, Inc., a leading provider of technology consulting, platform and product engineering, AI and advanced analytics services, announced its Data Observability Starter Kit, an AI-powered solution designed to help companies ensure data quality across their data transformation processes and data platforms. This is a vital capability in today’s data-driven world, as companies operate with large volumes of diverse data from multiple sources. The ability to identify data issues and stop the propagation of bad data to downstream applications, or prevent data issues from corrupting sales reports and dashboards, is invaluable for companies to make informed decisions and maintain operational integrity. Data quality also has a significant impact on the ability to develop and produce AI solutions.
Grid Dynamics’ AI-powered Data Observability Starter Kit simplifies data quality integration and provides a comprehensive suite of controls, ensuring customers can effectively control data quality for all their data types. It provides controls for tubular, structured, and unstructured data, including additional built-in quality checks for null, missing, or empty values, statistical distribution checks, data refresh, data volume checks, and unsupervised machine learning models for anomaly detection.
“ Data observability is a top concern for our customers,” said Ilya Katsov, VP of Technology at Grid Dynamics. “ The Data Observability Starter Kit provides them with a flexible framework that can flag anomalies such as unusually high or low numeric values in individual data elements, poorly formatted values, records lost due to data replication errors, and more. The kit uses AI models to simplify the setup and maintenance of data quality checks, making the solution much more usable and effective than rules-based systems.”
Another benefit of the Grid Dynamics Data Observability Starter Kit is its ability to accelerate time to market for enterprise-scale customers. The starter kit seamlessly integrates with leading platforms and data warehouses, allowing customers to scale their data quality controls without disruption.
SOURCE: BusinessWire