Who Uses a Data Catalog & How to Drive Positive Outcomes?

Updated May 25th, 2023
header image

Share this article

A data catalog is the backbone of modern data management, enabling organizations to find, understand, trust, and use their data effectively. It acts like a central repository for data, providing context and accessibility.

But who uses a data catalog? In this blog, we will understand the roles and user personas who can use a data catalog along with examples and uses cases.

Let’s dive in!

Table of contents #

  1. How a data catalog benefits everybody in an organization?
  2. Exploring the benefits of a data catalog tool across various organizational roles: examples and use cases
  3. Enabling user-centric data management: Must-have capabilities in a data catalog tool
  4. Summary
  5. Who uses a data catalog? Related reads

How a data catalog benefits everybody in an organization? #

Data catalogs are beneficial for several roles in an organization:

  1. Data analysts and data scientists
  2. Data stewards and data managers
  3. Business users
  4. IT professionals
  5. Compliance officers

Let’s dive into these roles in detail:

1. Data analysts and data scientists #

Data analysts and data scientists can use the data catalog to find the data they need for their analyses and predictive models. They can understand the meaning of the data, its source, and its transformation history. It makes their data preparation process quicker and more effective.

2. Data stewards and data managers #

Data stewards and data managers are responsible for ensuring data quality and governance. They use the data catalog to define and enforce data standards and rules, manage metadata, and maintain data lineage.

3. Business users #

Business users, like salespeople, marketing managers, and operations managers, often need data for decision-making but don’t have the technical skills to query databases directly. A data catalog tool provides them with a user-friendly interface to find, understand, and use data without needing to write SQL queries or understand database schemas.

They can see what data is available, what it means, and even see insights directly if the data catalog tool supports that.

4. IT professionals #

They use data catalogs to understand the data landscape, manage access rights, and ensure that data is stored securely and efficiently.

5. Compliance officers #

Data catalogs also help with regulatory compliance. They can provide information about data lineage, data handling, and data usage, which can be vital for demonstrating compliance with regulations like GDPR or HIPAA.

By using a data catalog, each of these roles can better understand what data exists, where it comes from, how it’s used, and whether it can be trusted. This leads to better decision-making, better data governance, and a more data-driven culture.

It can be particularly useful when you’re migrating to a new platform like Snowflake and need to help a range of users adapt to the new system.

Exploring the benefits of a data catalog across various organizational roles: Examples and use cases #

In this section of the blog, we will examine how each role might use a data catalog along with a few examples.

1. Data analysts and data scientists #

Suppose a data scientist is building a predictive model for product failure rates. They would use the data catalog to find relevant data sets, for instance, manufacturing data, historical product failure reports, and maintenance records.

The data catalog would help them understand if the data is fit for purpose by providing details about data quality, when it was last updated, and how it was collected and transformed.

2. Data stewards and data managers #

Consider a data manager tasked with ensuring data quality. They would use the data catalog to set data quality rules and standards. For instance, they could specify that all customer addresses must be in a standard format.

They could also use the catalog to trace back errors or inconsistencies to their source, by following the data lineage information in the catalog.

3. Business users #

Let’s imagine a marketing manager planning a new campaign who wants to target it toward the most profitable customer segment. They could use the data catalog to find data about past purchase history, customer demographics, and past campaign responses.

The data catalog would help them understand what each data set means and how it can be used. They could do it without knowing technical details like database schemas or SQL.

4. IT professionals #

Suppose an IT manager needs to plan data storage for the next fiscal year. They would use the data catalog to understand what data is stored where, how fast data volumes are growing, and what the usage patterns are.

They could also use the catalog to manage access rights, ensuring that each user or team only has access to the data they need, which helps with both efficiency and security.

5. Compliance officers #

Consider a compliance officer preparing for a GDPR audit. They would use the data catalog to demonstrate that the organization knows where all its personal data is stored, who has access to it, and how it’s being used.

The catalog could provide data lineage information to show how data is collected, transformed, and stored, which could be crucial for demonstrating compliance.

In all these examples, the common theme is that the data catalog helps users find, understand, and use data effectively. It helps users trust the data, because they know where it comes from and how it’s managed. It also helps users work more efficiently because they spend less time looking for data and more time using it.

Enabling user-centric data management: Must-have capabilities in a data catalog #

When choosing a data catalog, there are several capabilities that you need to consider to address the needs of all your users. Here are some key features to look out for:

  1. Support for multiple data assets
  2. End-to-end data visibility
  3. Big data capabilities for metadata
  4. Embedded collaboration
  5. Flexible and scalable
  6. User-centric design
  7. Security and governance
  8. Cloud-based and agile

Let’s dive into each of these features in detail:

1. Support for multiple data assets #

The tool should be able to handle a diverse array of data assets, not just tables. This includes BI dashboards, code snippets, SQL queries, models, features, and Jupyter notebooks.

2. End-to-end data visibility #

The tool should not just improve data discovery, but also provide a “single source of truth” for your data. This means the tool needs to integrate data lineage, data quality, data prep, and other information about data assets into a unified view.

3. Big data capabilities for metadata #

Given the volume and variety of metadata, data catalogs should be able to handle metadata as a form of big data. This includes being able to search, analyze, and maintain metadata effectively.

Data catalogs should leverage the elasticity of the cloud to process large amounts of metadata, such as parsing through SQL code from query logs in Snowflake. They should be able to automatically create a column-level lineage, assign popularity scores to data assets, and deduce potential owners and experts for each asset.

4. Embedded collaboration #

The tool should integrate seamlessly with teams’ daily workflows and promote frictionless collaboration. It should provide features like request access, issue reporting, and support requests that are integrated with other tools you use (like Slack or JIRA).

5. Flexible and scalable #

Just as your data infrastructure has to be able to handle rapid changes in data volumes and requirements, your data catalog should also be flexible and scalable. It should be able to handle growth in both the amount of data and the number of users.

6. User-centric design #

The interface and user experience of the data catalog tool should be designed keeping the diversity of data teams in mind. It should be easy to use for different roles within your organization, from data engineers to business analysts.

7. Security and governance #

The tool should provide robust security and governance features to ensure that your data is protected and compliant with relevant regulations. This includes features like access control, audit trails, data masking, and consent management.

8. Cloud-based and agile #

The tool should be built on a cloud-based architecture and deployable quickly, just like other components of your modern data stack. It should not require extensive setup time or engineering resources, and it should be possible to update the tool easily.

Remember that while these are key characteristics, your specific needs might require additional features or focus areas.

Summary #

Data catalog tools aren’t just for data engineers or IT professionals. They cater to a wide range of roles including data stewards, data scientists, data analysts, business analysts, IT and compliance officers, as well as everyday business users.

Each of these roles can benefit from a data catalog tool in different ways, such as finding data sources, understanding data lineage, ensuring data quality and compliance, and enhancing collaboration among teams.

Share this article

[Website env: production]