Data catalogs serve as essential tools for organizations, providing a comprehensive inventory of data assets.See How Atlan Simplifies Data Cataloging – Start Product Tour
They enable users to locate, understand, and utilize data effectively. By addressing common data challenges, data catalogs enhance operational efficiency and support data-driven decision-making.
What is a data catalog used for? A data catalog is a collaborative workspace that provides context, control, and connection across your entire data estate. With a data catalog powered by active metadata, any data user in any business domain can locate, understand, and use the power of your company’s data.
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Read on to learn more about the problems a data catalog can solve and use cases when a data catalog can help.
What problems does a data catalog solve?
Permalink to “What problems does a data catalog solve?”Without a data catalog, your company may struggle to manage and utilize its data. You may be experiencing problems like:
- your data analysts spend too much time resolving tickets to fix broken dashboards.
- your information security team is unable to secure personally identifiable information (PII) to remain compliant with regulations like GDPR.
- your storage costs soar as you maintain duplicative datasets.
- your data stewards frequently have to provide context for data assets.
- different departments and teams have different definitions for the same term or metric.
- you feel unprepared for major data projects like migrations.
Data catalogs can resolve these issues and more. With a data catalog, you can
- reduce the amount of time spent troubleshooting data issues.
- enable self-service for data consumers.
- secure your data and help your company become compliant.
- save money by decreasing data storage and computational costs.
- avoid data problems before they arise.
With such a wide range of applications, data catalogs are vital for any data-driven company to manage and maximize its data. And it’s not just the company that benefits. Anyone who works with data––from data engineers to customer success representatives––can use a data catalog to work more efficiently.
Data catalog use cases and examples
Permalink to “Data catalog use cases and examples”Data catalogs have a variety of use cases across multiple business domains. Information security, data engineering, operations, and analytic functions all are more effective with a data catalog.
These eleven examples are some of the top data catalog use cases.
- Root cause analysis
- Impact analysis
- Proactive data issue alerting
- Data compliance management
- Cost optimization
- Data migration
- Data lifecycle management
- Business glossary
- Metrics catalog
- Data discovery
- Data exploration
Root cause analysis
Permalink to “Root cause analysis”Locating the source of a data issue can be time-consuming. A data analyst working to fix a broken dashboard may spend hours investigating its data lineage to track down the responsible column. A data catalog can speed up this analysis by streamlining the identification of upstream data assets.
Impact analysis
Permalink to “Impact analysis”Any modification to a data asset, like a schema change, can feel risky because it might unintentionally affect downstream datasets and workflows. A data catalog can visualize how modifying or taking data offline could break workspaces or dashboards so that you can foresee and address any potential problems.
Proactive data issue alerting
Permalink to “Proactive data issue alerting”When using a BI tool, data consumers want to feel confident that the data they’re viewing is accurate. A powerful data catalog can trace a report’s data lineage to its sources. If there is an issue anywhere in the data pipeline, the catalog can alert the consumer. This proactive alerting creates trust with data consumers.
Data compliance management
Permalink to “Data compliance management”With a data catalog, you can protect sensitive data by automatically flagging columns with PII and controlling access to those assets. With shared knowledge of where all sensitive data is created, stored, and used, it’s easier to comply with regulations like GDPR.
Cost optimization
Permalink to “Cost optimization”Resource-intensive queries and redundant data assets can add up to major expenses. A data catalog can help you find unused tables or pipelines, saving storage. Additionally, data catalogs can pinpoint infrequently used queries or calculations so that you can divert computational resources to where they’re needed most.
Data migration
Permalink to “Data migration”Migrations are expensive and risky endeavors. Costs can quickly spiral out of control when migrations result in data outages and loss. A data catalog can assist in mapping data across systems to achieve a clear view of potential impacts across your data stack. Data catalogs enable this crucial prep work, ensuring a successful migration while mitigating risk.
Data lifecycle management
Permalink to “Data lifecycle management”Properly managing data throughout its lifecycle has many benefits. You can prepare for potential data breaches or system failures, and you will know how to recover your data in case of a catastrophic event.
Business glossary
Permalink to “Business glossary”Your company may have a business glossary with common definitions for key terms. But many glossaries are siloed, so data consumers can’t use them to understand the data they’re using. A data catalog can act as a single source of truth for all your terms and data definitions. Additionally, a data catalog simplifies documenting and sharing these definitions.
Metrics catalog
Permalink to “Metrics catalog”In a metrics-driven environment, calculations like DAU/MAU/WAU, ARR, and churn rate are important considerations in any business decision. However, without a data catalog, stakeholders may be using different calculations and data sources for the same metric. A data catalog can define these metrics so that all decision-makers are working from a single source of truth.
Data discovery
Permalink to “Data discovery”Data consumers can spend a lot of time locating the data they need. They also have to find subject matter experts and uncover an asset’s context. As a result, data teams often spend too much time answering questions and fulfilling requests. These same requests can appear repeatedly.
A data catalog can provide context and metadata so that data consumers can use data on their own. Any time a question receives an answer, it can be added to the data catalog to prevent repeat asks.
Data exploration
Permalink to “Data exploration”Finding and understanding the data you need are the first steps. To use the data, you’ll need to explore it through sampling or simple queries. A powerful data catalog helps data consumers with basic analysis. With a data catalog, data consumers can access and even query data on their own, saving data engineers and analysts time.
How organizations making the most out of their data using Atlan
Permalink to “How organizations making the most out of their data using Atlan”The recently published Forrester Wave report compared all the major enterprise data catalogs and positioned Atlan as the market leader ahead of all others. The comparison was based on 24 different aspects of cataloging, broadly across the following three criteria:
- Automatic cataloging of the entire technology, data, and AI ecosystem
- Enabling the data ecosystem AI and automation first
- Prioritizing data democratization and self-service
These criteria made Atlan the ideal choice for a major audio content platform, where the data ecosystem was centered around Snowflake. The platform sought a “one-stop shop for governance and discovery,” and Atlan played a crucial role in ensuring their data was “understandable, reliable, high-quality, and discoverable.”
For another organization, Aliaxis, which also uses Snowflake as their core data platform, Atlan served as “a bridge” between various tools and technologies across the data ecosystem. With its organization-wide business glossary, Atlan became the go-to platform for finding, accessing, and using data. It also significantly reduced the time spent by data engineers and analysts on pipeline debugging and troubleshooting.
A key goal of Atlan is to help organizations maximize the use of their data for AI use cases. As generative AI capabilities have advanced in recent years, organizations can now do more with both structured and unstructured data—provided it is discoverable and trustworthy, or in other words, AI-ready.
Tide’s Story of GDPR Compliance: Embedding Privacy into Automated Processes
Permalink to “Tide’s Story of GDPR Compliance: Embedding Privacy into Automated Processes”- Tide, a UK-based digital bank with nearly 500,000 small business customers, sought to improve their compliance with GDPR’s Right to Erasure, commonly known as the “Right to be forgotten”.
- After adopting Atlan as their metadata platform, Tide’s data and legal teams collaborated to define personally identifiable information in order to propagate those definitions and tags across their data estate.
- Tide used Atlan Playbooks (rule-based bulk automations) to automatically identify, tag, and secure personal data, turning a 50-day manual process into mere hours of work.
Book your personalized demo today to find out how Atlan can help your organization in establishing and scaling data governance programs.
Putting it all together
Permalink to “Putting it all together”A robust data catalog can save you time, reduce your costs, and secure your company’s data. See how Atlan customers have been using our third-generation data catalog to bring their data to life.
FAQs about Data Catalog Use Cases
Permalink to “FAQs about Data Catalog Use Cases”1. What are the use cases for a data catalog?
Permalink to “1. What are the use cases for a data catalog?”Data catalogs have various use cases, including root cause analysis, data compliance management, and proactive data issue alerting. They help organizations manage data effectively and improve decision-making.
2. What is a data catalog with an example?
Permalink to “2. What is a data catalog with an example?”A data catalog is a centralized repository that organizes and manages data assets. For example, it can help a data analyst quickly locate the source of a data issue, streamlining the troubleshooting process.
3. What is the use of a catalog in a database?
Permalink to “3. What is the use of a catalog in a database?”In a database, a catalog serves as a metadata repository that provides information about data assets. It helps users understand data lineage, definitions, and relationships, enhancing data governance and usability.
4. Why do we need a data catalog?
Permalink to “4. Why do we need a data catalog?”A data catalog is essential for improving data accessibility, ensuring compliance, and enabling self-service analytics. It helps organizations maximize the value of their data assets and supports data-driven decision-making.
5. What role does a data catalog play in content organization and management?
Permalink to “5. What role does a data catalog play in content organization and management?”A data catalog organizes and manages content by providing a structured framework for data assets. It enhances collaboration among teams, ensuring everyone has access to accurate and relevant information.
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