What is a Data Catalog? How to build it, Best practices & Tools
Turning big data into actionable insights is a popular business goal. Data catalogs can help organizations achieve this goal. The purpose of a data catalog is to support a business to find, understand and maintain its existing data assets. The process of creating a data catalog can lead businesses to identify data assets that they were previously unaware of.
What is a data catalog?
A data catalog is a record of an organization’s existing data. It is a library where an organizations’ data is indexed, organized and stored. Most data catalogs contain data sources, data usage information, and data lineage that describes the origin of the data and how it changed to its final form. With a data catalog, organizations can centralize information so that they can identify what data they have, distinguish data based on its quality and source.
The data catalog is a part of the data governance discipline. It automates metadata management and makes it collaborative. Having a data catalog helps businesses discover and manage their data at scale. It enables companies to track their data assets with a business mindset while supporting advanced search and visualization.
Why is it important now?
Companies are acknowledging the significance of data more, but data can only be an asset if organizations can find a way to convert it into meaningful insights for better outcomes. Below are the results of the Forrester Analytics survey. 39% of executives are highlighting the challenges they face in sourcing, gathering, managing and governing data which are all activities that can be supported by a data catalog.
How to build your company’s data catalog?
The data catalog building process can be separated into three parts:
- Indexing: The data catalog indexes the metadata of organizations’ data tables, files, and databases.
- Organizing: Adding descriptions of tables and files to make your data more understandable for data consumers.
- Tracking: Data catalogs can be used to track your organization’s data assets. Methods include graph analytics algorithms, analyzing the origins of data and its destination (data lineage), and informative summaries including different statistics.
What are its advantages?
Data catalogs can help organizations improve their efficiency, effectiveness and data security.
- Data catalogs help employees discover data faster so they have more time to analyze it to gain insights
- Since enterprises are connecting different data sources, data redundancies may occur. A good data catalog helps companies identify the data redundancies and eliminate them. Therefore, the storage cost of data and data management/quality costs can be reduced.
- A successful data catalog creates a single source of truth at an enterprise level. Therefore, it provides transparency and prevents ambiguities.
- Having a single source of truth in terms of data assets enables organizations to set up data governance and management processes, assigning data stewards and ensuring the quality of their data.
Improved compliance/data security/audibility
- As a business grows, it becomes important to know who accesses data since company data includes private information. Data catalogs can provide access control so that organizations protect their data.
- There are different data protection laws. 107 countries have put in place legislation to secure the protection of data and privacy. A good data catalog simplifies data security and compliance (GDPR, CCPA, etc.).
What are the leading tools for creating and maintaining a data catalog?
- Alation Data Catalog
- Alex Solutions Data Catalog
- Cloudera Navigator
- Collibra Data Catalog
- Google Cloud Data Catalog
- IBM Watson Knowledge Catalog
- Informatica Data Catalog
- Ovaledge Data Catalog
- Talend Data Catalog
- Waterline Data Catalog
Informatica offers a flexible approach focused on AI-powered data discovery and analytics capabilities. It has ~$1 billion in revenues.
What are the best practices for maintaining a data catalog?
- The purpose of a data catalog is to understand your data and discover what you don’t know before. That’s why make sure you don’t exclude any type of data in the catalog.
- Data cataloging service is also a part of your Big Data efforts. Don’t make it a separate activity. Align the catalog with your data strategy.
- For preventing unauthorized data access, set accessibility rules.
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List of best practices for maintaining a data catalog: Deloitte
Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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