AI para hacer Catálogos de Datos. Por TDWI. - Seguridad Mania.com - España y América Latina

Data catalogs are increasingly critical as more users engage in self-service analytics and business intelligence and seek access to a wider variety of data types and sources. Many organizations fear that allowing users more self-service access and analysis will result in data chaos, especially if those sources exist outside IT-managed platforms such as an enterprise data warehouse. Data catalogs help organizations combat data chaos by enabling them to manage and govern distributed data assets more effectively. With an effective data catalog, organizations curate data so that users can trust sources and gain insights faster.

 

The problem with data catalogs (as well as metadata repositories and business glossaries) is that traditionally, building and managing them is slow, tedious, and usually involves heavily manual work by IT administrators, not users. Enterprise metadata and master data management might be effective for some corporate data sources, but generally do not cover all the sources that users want to access today, such as Hadoop data lakes.

 

Fortunately, newer solutions are making it easier and faster to build and manage data catalogs. These solutions apply the power of artificial intelligence (AI), including machine learning and natural language processing (NLP) to improve data usability and trust so that users can analyze data and share knowledge with greater confidence.

 

Join this TDWI Webinar to learn how AI-powered data catalogs can enable your organization to stem the tide of data chaos and better manage and govern self-service analytics, BI, and data preparation. Smarter, more visual data catalogs can increase users’ speed to insight and confidence in their ability to share knowledge and collaborate on data and analytics.

 

 

- Why a data catalog is critical to self-service analytics, BI, and data preparation

- The emerging role of AI, machine learning, NLP, and relationship visualization for improving the usability and value of the data catalog

- The key role of AI-powered data catalogs for effective information governance