New Practices in Data Cataloging
Webinar Speaker: Philip Russom, Senior Research Director for Data Management
Date: Tuesday, September 25, 2018
Time: 9:00 a.m. PT, 12:00 p.m. ET
Find relevant data quickly and accurately to accelerate and enhance your productivity with analytics and other data-driven business practices.
Are you tired of starting with a blank slate every time you begin a new analytics assignment? That’s what happens when you spend your precious time researching the same data sources as last time and assembling yet another aggregated data set prior to doing what you really need to do. Creating a new analysis can have a positive business impact on your enterprise.
To address this problem and related ones, savvy users are now turning to innovative vendor tools for data cataloging. When a good cataloging tool is used well, the result is a wealth of information about data. The information in that catalog in turn enables a data analyst, data scientist, or other user to focus their exploration of data on the most relevant, trusted, and quality data available.
A mature catalog will have extensive information categorization, so that analysts and similar users can also focus their work by data domain (e.g., only look at customer data), compliance risk (e.g., to avoid data about EU residents), and trustworthiness or usefulness (as rated by other users).
This webinar will drill into the new functionality that is available through data cataloging, plus the beneficial use cases for both business and technical programs.
- Overview of modern data cataloging emphasizing centralization and semantic standards
- How cataloging relates to metadata management, but is so much more
- How the cataloging process can be accelerated and automated by tribal crowdsourcing and machine learning
- Real-world use cases for new practices in data cataloging, such as analytics, reporting, data management, compliance and governance, curation and stewardship, business glossaries, digital marketing, self-service data prep, auditing data usage, and collaboration via data
Philip Russom, Ph.D.