Intelligent Data Catalogs Market Outlook, 2019-2024 – Trends, Forecasts, Competitive Analysis, SPARK Matrix – Quadrant Knowledge Solutions

Quadrant Knowledge Solutions announces the addition of the “Market Outlook: Intelligent Data Catalogs, 2019-2024, Worldwide” report to their strategic market outlook offerings.

Intelligent Data Catalogs Market Outlook research provides strategic information to the market participants and users who are responsible for strategic planning, marketing, sales, and purchasing data catalogs and solutions. Intelligent Data Catalogs market outlook research includes a detailed analysis of the global market regarding short-term and long-term growth opportunities, emerging technology trends, market trends, and future market outlook. The study provides competition analysis and ranking of the leading Intelligent Data Catalogs vendors in the form of SPARK Matrix.

Driven by the exponential growth of structured, semi-structured, and unstructured data, enterprise organizations continue to face significant challenges in terms of data management, governance, and analysis to get valuable insights. Traditional data catalogs, data lakes, and metadata management solutions often lack necessary discipline and intelligence to handle the ever-expanding volume, variety, speed, data sources, and data stores.

Intelligent data catalog provides a centralized platform to integrate data across internal and external sources, improve data quality, and provides a unified contextual view of metadata, their relationship, and usage. Intelligent data catalogs can extract data across sources including on-premise to cloud, data warehouse and data lakes, within or outside of the enterprise, online resources, and such others. Leveraging machine learning, artificial intelligence, and automation, intelligent data catalogs enable business, and IT users to identify complex relationship across data structures, improves data quality, uncover duplicate data sets, draw semantic inferences, recommends alternate data sets based on data quality and usage, and understand data lineage. It helps organizations in search, discovery, curation, governance, collaboration, management, and analysis of enterprise data assets to support digital business initiatives.