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Data catalogue definition

A data catalogue is an organised inventory of data assets that enables data consumers to locate, access and evaluate data in a centralised location for analytical and business uses. Data catalogues leverage metadata to allow data consumers to quickly search an organisation’s entire data landscape, understand the data available to them and operationalise that data for insight-driving analyses. 

Like a library catalogue which provides a central location for you to easily look up the description, location and availability of all books in a library, a data catalogue provides a comprehensive view of data across your organisation with a powerful search function that enables you to easily locate and access your data. In addition, similar to a book description in a library catalogue, a data catalogue provides business context around your data so you know what data is available across the organisation and can effectively use this data to make impactful business decisions. As a result, many organisations are placing data catalogues at the center of their data management strategies and using these data catalogues to drive innovation, growth, and insightful business decisions.

90% of respondents see data as a high priority in decision making, but 47% struggle with a lack of efficiency when using data and 42% deal with poor quality data.

Leveraging data to suit yor needs, BARC

These organisations may wonder why do I need a data catalogue? How would I use one? What are the business benefits? This blog helps answer these questions and illustrates the must-have capabilities of a data catalogue, so you can be sure you are getting the right one for your needs.

Why do I need a data catalogue?

To help you understand how companies can benefit from data catalogs, we put together this quick six-step checklist:

1. Do you spend way more time looking for the data you need than the time you spend using it?
2. Do you know less about the data than you think you should?
3. Do you know the source of your data?
4. Do you know the quality of the data?
5. Can you rate your data assets?
6. Can you get and give data access easily and securely?

Most organisations see data as crucial to their business strategy. According to a survey conducted by Forrester, 84% of respondents see data as central to generating accurate business decisions. But without a data catalogue many organisations struggle to be data driven because their data is siloed across the organisation. In fact, business analysts spend 76% of their time finding, understanding and accessing data, instead of using data to generate insights. This time wasted can slow down analyses and ultimately innovation. To solve this problem, organisations turn to a data catalogue to help them:

• Gain a unified view of all your data
• Eliminate the pain of searching through chaotic data swamps to find the right data 
• Improve trust and confidence in your data
• Increase productivity and operational efficiency
• Accelerate time to insight

Being able to trust data enables you to truly unlock the value of your data and generate meaningful and trusted business insights. Gaining a unified view of all your data across your enterprise allows you to easily find the right data for your needs and spend less time searching for data and more time creating analyses. This ultimately speeds up time to insight and allows your organisation to adapt to the trends of the market as they occur and spend more time innovating. 

Must-have capabilities of a data catalogue

Not all data catalogues are created equally, so it is important to know what capabilities to look for when selecting a one. To make it easy for you, here is a list of the seven must-have capabilities for a data catalogue:  

• Ability to deploy across an enterprise: strategically deployed catalogues provide more value than tactically deployed data catalogues because they can catalogues sources across the enterprise, thus eliminating the creation of metadata silos. 
• Broad metadata connectivity: with data spread throughout an organisation, data catalogues must be able to connect to and ingest metadata from databases, data lakes, data warehouses, enterprise applications, ETL tools, BI solutions and other data sources. 
• Machine learning-powered automation: an ML-powered data catalogues saves time and increases productivity by automating the manual tasks of sorting, classifying and organising data assets. It also enriches data in the catalogues by add business context at scale.   
• Native, automated data lineage: data lineage helps data users better understand and trust their data by adding additional context that shows where the data comes from, how the data transforms, and how it is used.
• Collaboration: collaboration capabilities break down organisational silos and enable the sharing of data, knowledge and insights across an organisation. 
• Embedded data governance and data privacy: ensure trust, compliance and confidence in your data by operationalising and enforcing policies that control user access so you know that only the right people are using your data.