How Data Cataloging Improves Data Adoption for Decision-Making?

Jun 01, 2023
Digital Transformation | 5 min READ
Organizations in today's fast-paced digital era strive to be data-driven, generating unprecedented data daily. The abundance of data provides ample opportunities to make informed decisions - but only if the data is trustworthy, relevant, and easily accessible. 
Deepak Gupta
Deepak Gupta

Former AVP, Practice Head

Data & Analytics, Data Science & AI


Unfortunately, many organizations fail to take a modern approach to data governance, leading to a lack of data adoption for decision-making. Gartner's forecast predicts that by 2025, 80% of organizations aiming to expand their digital business operations will face failure. The primary cause of this setback is their failure to adopt a contemporary approach to data and analytics governance.
In this article, we delve into how data cataloging improves data adoption for decision-making, empowering organizations to unleash the complete potential of their data and drive strategic success.
The Role of Data Cataloging in Data Governance
Data's sheer volume and complexity can often hinder effective decision-making - and this is where data cataloging comes into play - acting as a catalyst for effective data governance and adoption.
Data cataloging is essential to data governance because it provides visibility of data assets across the organization. In addition, by defining a common language and understanding data assets, data cataloging offers a foundation for effective data governance.
Organizations that embrace data cataloging as part of their data governance strategy gain a competitive edge in today's data-driven landscape.
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Benefits of Data Cataloging
The key benefits data cataloging provides that can improve data adoption for decision-making are:
  • Enhance Data Visibility & Access
    The most significant challenge for organizations is knowing what data they are collecting & where it resides. Data cataloging enables organizations to understand their data, its location, and how to access it by providing an inventory of data assets. The enhanced data visibility ensures that decision-makers know the data they have at their disposal, fostering data-driven decision-making.
  • Data Compliance & Safety
    Data compliance & safety are essential aspects of data governance. Data cataloging helps organizations comply with regulations and protect sensitive data by providing visibility into data assets. Data cataloging also ensures that data is classified, tagged, and tracked to meet regulatory and compliance requirements.
  • Data Trustworthiness for Decision-making
    Data trustworthiness is about data assets' reliability, accuracy, and completeness. Data cataloging provides information about the quality of data assets, making it easier for organizations to evaluate data trustworthiness and determine whether it is suitable for decision-making.
  • Leveraging Data for Monetization
    Various ways can monetize data, making it a priceless asset. Data cataloging helps organizations identify and understand their data assets' value, making leveraging data for monetization opportunities easier.
  • Fast and Seamless UX
    A data catalog facilitates a new era of seamless user experience, providing swift and convenient management and access to valuable data products.
Tools for Data Cataloging
Multiple tools are available in the market to help organizations implement data cataloging. Here are the three most popular data cataloging tools:
  • Alation: Alation is a data cataloging tool that provides a collaborative and social approach to data governance. It includes features such as data lineage, quality, and cataloging, which help users understand and trust data assets.
  • Collibra: Collibra is a data intelligence platform that provides a single, centralized ground for data governance, including data cataloging. It provides an intuitive interface allowing users to search, discover, and understand data assets across the organization.
  • Purview: Purview is a data cataloging tool from Microsoft that allows organizations to create a holistic, up-to-date, and easily searchable inventory of data assets. It uses AI (Artificial Intelligence) and ML (Machine Learning) to automatically classify and organize data assets, enabling users to find necessary data effortlessly.
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Implementation of Data Cataloging
Embarking on the path of data cataloging implementation requires careful planning, meticulous organization, and a strategic approach to unlock its full potential.
  • Step-1: Start with a data inventory
    Before implementing data cataloging, it's essential to understand the organization's data assets. Building a data catalog involves conducting an inventory to gain insights into data assets and their location.
  • Step-2: Define a metadata model
    Organizations must define a metadata model to ensure consistent classification and effective searchability of data assets. In addition, the organization should align the metadata model with its data governance framework and ensure it is flexible enough to accommodate future changes.
  • Step-3: Select a data cataloging tool
    Selecting a data cataloging tool that aligns with the organization's data governance framework and meets its requirements is essential. In addition, the tool should be user-friendly, scalable, and provide relevant metadata to support decision-making
  • Step-4: Establish a governance framework
    Data cataloging is critical to data governance, but more is needed. Establishing a governance framework that includes policies, processes, and controls is essential to ensure the data catalog's accuracy, consistency, and completeness.
Key Takeaways
  • Data cataloging is a crucial component of modern data governance and is essential for organizations seeking to scale business digitally. The findings of a report by Forrester revealed that organizations leveraging data to extract valuable insights for decision-making purposes are nearly three times as likely to attain double-digit growth.
  • Data cataloging provides visibility of data assets, ensures data compliance and safety, establishes data trustworthiness for decision-making, and allows organizations to leverage data for monetization.
  • By following the practical tips for implementing data cataloging, organizations can create a searchable and centralized inventory of data assets that support informed decision-making.
  • As organizations continue to scale their business, implementing modern data governance practices like data cataloging will be essential to stay competitive and thrive in the digital age.
What’s next?
Gone are the days of laborious data requests and wrangling processes. Instead, keep valuable data from being untapped.
Take the next step towards improving data adoption for decision-making by partnering with BirlaSoft. Our experienced team can lead you through the implementation of data cataloging and provide tailored solutions to meet your organization's specific needs.
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