Metadata catalogs enable organizations to find the data they need to perform analysis, data science, and governance programs to provide insight to know how data is being used. A traditional metadata catalog enables collaboration that builds data culture, but often requires manual data stewardship to populate the catalog and keep it current (and accurate). BigID’s automation and machine learning enriches traditional data catalogs, extending value with scalable classification, automating context-rich insight across and within the catalog itself, and enabling a single view across silos for a holistic approach to data management.
These are 4 key critical capabilities that a modern data catalog needs to address the challenges of today’s enterprise environment.
Step 1: Discover Your Data
Most metadata catalogs are limited by data sources or types. Get visibility, context, and data intelligence by extending your enterprise data catalog to cover all data sources and types for a comprehensive view of your data environment. BigID scans all data, structured and unstructured, from all data sources, and applies ML for cataloging, classification, correlation, and cluster analysis for unique insight.
- Catalog: Capture and manage technical, business and security metadata across the complete data ecosystem all in one view. Preview sensitive data, see what data is overexposed and over privileged, identify duplicates and originals, and filter by type – all in one data catalog.
- Classification: Automatically identify, classify, and categorize data, metadata, and docs across any data source or data pipeline – based on type, sensitivity, regulation, and more.
- Correlation: Find all data related to a person or entity, discover dark data, and identify related data.
- Cluster Analysis: Find duplicate and similar data for easy labelling, governance & data consolidation across your data landscape – from structured to unstructured data, and everywhere in between.
Step 2: Enrich and Tag for Context
Most tagging in data catalogs requires manual work by data stewards or is crowdsourced by data users. BigID’s metadata exchange adds scalability, speed, and accuracy using ML to define data. By adding data context to know what the data is, BigID enables automated data set labeling to eliminate manual data set tagging once required by data stewards.
Step 3: Establish Data Privacy and Business Policies
Regulatory policies are evolving, rules are changing, and companies maintain additional corporate data policies. BigID’s policy manager allows administrators to easily add, update, or change policy rules using out of the box policy templates or creating specialized rules.
Step 4: Scale Tagging and Policy Notifications for Action
Tag relevant data sets with policies for insight, enforcement, and action. Align the right data with the right policy – by regulation, business rules, or sensitivity – and take action with apps: from data remediation to retention.
These 4 critical capabilities provide benefits to stakeholders across the organization – including Chief Data Officers (CDOs), Data Analysts, Data Scientists ,and Data Stewards.
- Chief Data Officers – Gain a complete view of all data in the environment with classification for context: know what the data is and how data is being used.
- Data Analysts & Data Scientists – Choose better data for analytics and modeling with additional insight and context, including visibility of relevant business policies and privacy regulations to know if the data has any restrictions.
- Data Stewards – Boost productivity by populating the data catalog with insight and classification to identify and tag data, allowing data stewards to focus on higher level stewardship responsibilities.
BigID analyzes all sources and types of physical data for insight to know what and where the data is, find sensitive data to protect, and identify redundant, outdated and trivial (ROT) data to remediate. BigID’s metadata exchange enhances metadata catalogs, adding unique insight from classification, correlation and cluster analysis.
Schedule a demo to see how BigID enhances traditional metadata catalogs applying advanced machine learning to enrich any data catalog with deeper insight.
Author
