Data Catalog vs. Data Dictionary: Understand the Differences and Benefits with Example

July 4th, 2022

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The difference:

A data dictionary holds the metadata for your database. In simple terms, a data dictionary is documentation for your database. It helps engineers and analysts get the context behind tables, columns, and data fields. Without data dictionaries, one has to rely on people or read through codebases and SQL queries.

A data catalog is a tool that helps index, inventory, and classify data assets across multiple data sources in your enterprise. A data catalog adds a context layer with a focus on discovery, search, metadata management, lineage, collaboration, and governance.

Let’s explore in detail the differences between a data dictionary and a data catalog and how both of them plays a role in adding context to data.

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What is a data dictionary?

A data dictionary provides information and insights about your database. Consider a data dictionary to be a documentation for databases.

A data dictionary provides insights on

  1. Data source(data warehouse, data lakes, databases, applications)
  2. Tables names and descriptions
  3. Table relationships
  4. Column name and descriptions
  5. Permissible values for a field
  6. Data types
  7. Column nullability
  8. Referential constraints — foreign keys and primary keys
  9. Column statistics — missing values, min-max values, and histogram distribution.
  10. Data and time when the property was created or changed
  11. Data owner
  12. Data freshness
  13. Classifications(PII, GDPR, HIPAA)

Example of how a data dictionary looks like

A data dictionary provides information about the database’s structure, data elements, constraints and relationships. Image by Atlan

What are the benefits of a data dictionary?

  1. A data dictionary links physical data assets to business terms/concepts/metrics. This helps data users to understand and trust data better. (improves data validity and credibility)
  2. Enables quick detection of anomalies and errors and hence helps keep a check on data quality.
  3. Check how and where a field is referenced across the entire database.
  4. Provides a framework for programming and database standards to maintain data integrity.
  5. Helps evaluate data consistency during security and compliance audits.
  6. A data dictionary acts as self-serve documentation for new engineers/analysts. This greatly reduces onboarding time.
  7. Data dictionaries can be accessed externally through APIs for reporting and cataloging purposes.

[Download ebook] → The Ultimate Guide to Evaluating a Data Catalog

What is a data catalog?

A data catalog is an inventory of data assets across all your data sources in your enterprise. It helps organizations discover, understand, and consume data better — all in one place.

A data catalog helps finding answers to:
  • What data do we have?
  • Where does it come from?
  • Who is the owner?
  • How clean is the data are there any gaps?
  • How it is classified?
  • Is the data good enough for running analysis?

Features of a data catalog

Fundamentally, what does a data catalog do? A data catalog reduces the time to insight for data users. It ensures:

  • Data is made readily accessible
  • Context is provided
  • Data lifecycle is visible
  • Access permissions are defined

Watch a demo of Atlan data catalog

Data catalogs make data accessible

A data catalog automatically crawls, identifies, inventories, and classifies data assets from multiple sources. Data catalog tools allow you to run a search across data lakes, data warehouses, databases, tables, columns, SQL queries, and business glossaries.

Example of how a data catalog looks like

Modern data catalogs have google-like search interfaces that respond to text based search for data assets. Image by Atlan

Data catalogs provide context

People with no context of the data can learn more about it to decide if they have the right data.

Business glossary provides context to business terms and metrics

Modern data catalogs come with in-built business glossaries to ensure common understanding of data asset and its usage across the organization. Image by Atlan

Data catalogs helps visualize data lifecycle

Data catalogs enable you to visualize the complete lifecycle of a data asset, its transformation, and dependency both upstream and downstream.

Data lineage helps visualize the data flow from source to dashboards

The best of modern data catalogs auto-construct visual lineage of data to give an understanding of how data has evolved through its lifecycle and how changing the data will impact downstream. Image by Atlan

A Guide to Building a Business Case for a Data Catalog

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Data catalogs enable data governance

A data catalog helps enforce robust access control policies as guard rails to help you protect the confidentiality and comply with various data protection regulations.

screenshot of Atlan data governance features

Modern data catalogs help deploy best-in-class data access governance without compromising on data democratization. Image by Atlan

When does an organization need a data catalog?

It's safe to say, deploying a data catalog is a right of passage for an organization to be truly data-driven. As a business, you can collect all the data that you want, set up best-in-class infrastructure to store that data, but data in itself is nothing. Just numbers.

You need the right data to reach the right person at the right time - for it to really move the needle on your business. Modern Data Catalogs are being designed to ensure that the complexities and scale of data do not deter "non-data" folks from using data in their day-to-day work.

Read in-depth about data catalogs.

Data catalogs vs. data dictionaries in the real world

As more and more data teams are feeling the need and adopting data catalogs, the difference between a catalog and a dictionary is fast vanishing — and becoming more complementary — because catalog tools now crawl and inventory data dictionaries for metadata. Data dictionaries are now an integral part of a data catalog.

Just in case if you are evaluating a data catalog, data dictionary, and metadata management for your team do take Atlan for a spin.

Atlan is a modern data catalog built on the premise of embedded collaboration that is key in today’s modern workplace, borrowing principles from GitHub, Figma, Slack, Notion, Superhuman, and other modern tools that are commonplace today.

Ebook cover - metadata catalog primer

Everything you need to know about modern data catalogs

Adopting a modern data catalog is the first step towards data discovery. In this guide, we explore the evolution of the data management ecosystem, the challenges created by traditional data catalog solutions, and what an ideal, modern-day data catalog should look like. Download now!