Unleash the Superpowers of Cloud Data Governance and Catalog

Learning Objectives

After completing this unit, you’ll be able to:

• Describe Cloud Data Governance and Catalog.
  
• Explain how Cloud Data Governance and Catalog helps govern data.
  
• List Cloud Data Governance and Catalog features.
  
• Define core Cloud Data Governance and Catalog terminology.
  

The Command Center for Your Data

Now that Maria and Alpine Group understand the value of organizing their data, they need the right tool to make it happen. Cloud Data Governance and Catalog (CDGC) is a single, unified solution that combines the power of a data catalog (finding data) and data governance (managing data) into one tool. Instead of having Maria use a map while Mateo, the data architect at Alpine Group (the IT admin), follows a rulebook, CDGC puts the map and the rules on the same screen. It’s designed to help everyone—from IT pros to business analysts—find, understand, and trust the data they use every day.

Bring Order to Data Chaos

Governing data manually is like trying to organize a stadium-sized junk drawer while thousands of people across the company are simultaneously adding new spreadsheets, moving folders, and renaming files. CDGC automates this with CLAIRE®, the AI engine that does the detective work for you.

CDGC helps you govern the data by:

• Automating discovery: It automatically finds sensitive data (like credit card numbers) in the system so you don’t have to search for it manually.
  
• Ensuring accountability: It clearly defines who the data steward is—the person responsible for maintaining and protecting that piece of information.
  
• Measuring quality: It finds, evaluates, and scores the data. If a dataset is full of errors, CDGC flags it so Maria doesn’t use bad info for a big report.
  

The Superpowers of CDGC

CDGC comes packed with tools that organize your data and turn it into a transparent, competitive advantage. Here is how the Alpine Group uses CDGC capabilities.

Data Cataloging

It acts as a comprehensive index that maps out every data asset across your company with a simple, search engine-style interface.

In action: Maria doesn’t know which physical server holds the latest customer transaction data. She just searches for a keyword, locates the asset instantly, and starts building her marketing campaign.

Data Lineage

This provides a visual map showing the complete lifecycle of your data, its origin, how it was transformed, and its final destination.

In action: If an end-of-year finance report displays unexpected numbers, Mateo, the data architect, can trace the backward step-by-step to locate the exact glitch where the numbers went wrong.

Data Quality Integration

This evaluates and scores data for accuracy, completeness, and consistency right inside the catalog.

In action: Alpine Group uses automated rules to flag missing email addresses or broken product codes before they ruin Maria’s massive email marketing launch.

Stakeholder Dashboards

These dashboards offer high-level, customized views of data health, quality metrics, and usage trends.

In action: Alpine Group’s chief data officer can review the health score of data across the entire company, instantly spotting weak points and allocating resources to fix them, in a single view.

Data Classifications

These are the labels or tags assigned to data elements to identify the type of information they contain.

In action: CDGC automatically assigns labels so Mateo doesn’t have to. For example, it scans a column of 10-digit numbers and tags it as “Phone Number” to automatically flag it as personally identifiable information (PII).

Data Profiling

Profiling assesses source metadata and analyzes column data statistics such as value distribution, patterns, and data types to determine the suitability of data for business use.

In action: It reveals hidden data patterns and anomalies in customer information that improve Maria’s decision-making accuracy.

Metadata Management

This automatically pulls in the tags about your data (creation dates, file types, classifications) without actually moving the large datasets.

In action: An Alpine Group compliance officer can instantly search for all datasets classified as PII to ensure they’re locked down, which keeps the company compliant and secure.

Business Glossary and Asset Relationships

This feature connects confusing technical data assets to simple, easy-to-understand business concepts and policies.

In action: It connects cryptic database table names such as CUST_TX_001 to clear business terms such as Customer Transactions. It bridges the gap between IT and nontechnical teams, which ensures that everyone in the company interprets the data exactly the same way.

Stakeholdership and Workflows

This assigns clear ownership for every asset and establishes automated approval processes for making changes.

In action: If someone wants to alter a data classification, an automated workflow routes it to the designated data steward for review. It acts as a digital permission slip to ensure accountability.

Search and Browsing Flexibility

This supports complex queries, adaptive search methods, and easy exporting to adapt to how different people work.

In action: A data scientist searching for a highly specific set of attributes can use advanced queries to find exactly what they need, export the results in a grid layout, and share it with their team in seconds.

Data Observability

Observability continuously monitors and detects anomalies in your data by analyzing profiling results to ensure data quality and reliability for business use.

In action: It acts as an early warning system that identifies unexpected spikes in transaction records that could indicate data ingestion issues. This allows Mateo to investigate before business users are affected.

Data Access Management

This creates and enforces rules to control who can view, use, or modify data, and ensures that sensitive information remains protected while allowing appropriate access.

In action: Mateo applies data filter policies to restrict access based on geographic location, ensuring European customer data is only accessible to team members within the EU to comply with GDPR regulations.

Core CDGC Terms

Get familiar with common CDGC terms.

You have now learned how CDGC can be used to catalog and govern data in an organization. But how are these data brought into the catalog? How does CDGC even know where the data is? You get the answers to these questions in the next unit.