Why Curated Data is Essential for Reliable Research and Analysis


Businesses and other organizations store vast data, and there is more data access today than ever. But the more the data, the harder it becomes to use it. To seek the highest level of knowledge from this data, you need to review and manage it carefully. Here, data curation comes into the picture.

What is Data Curation?

Data is a company’s most valuable asset, but it needs to be used to increase the data value. Companies have ample data, but you can only reap its benefits when analyzed and applied to drive business trajectories. As the need for analysis and reporting to make data-driven decisions are increasing, analysts and decision-makers need to understand what data to use to drive the business.

Data Curation Best Practices and Methods

Initially, data curation emerged from the management of scientific data. Scientists can harness the potential of published data and find additional interest in it in new research endeavors. To ensure scientists find what they want in the vast oceans of data, there’s a need for research data management procedures to organize and categorize information based on its features and relevance. This led to the evolution of diverse practices under “data curation.”

Gradually, the significance of curated data extended beyond research data management to various other fields. Data scientists, analysts, and users embraced and further refined these practices to suit their specific needs. While data curation activities may vary across different domains, they typically involve specific fundamental techniques, as mentioned below.

  • Preserving data commonly means gathering, storing, and managing data to ensure it’s not lost.
  • Data sharing, which makes data accessible for use by interested bodies.
  • Cleaning data to remove data inconsistencies and errors.
  • Data discovery allows data collection from different databases, categorizing, cataloging, and preparing for analysis and usage.
  • Data integration includes transformation and normalization to integrate data from varying formatted databases.
  • Metadata management which refers to creating and managing data about the curated data will make it easy for you to filter the data and find the relevant facts.

Moreover, data curation refers to the data presentation in a way that is helpful for the targeted audience. Hence, data curators employ charts, dashboards, and several other tools and techniques to show the potential implications of the curated data.

Who Owns Data Curation?

To begin with, data curation is not an IT task but rather a data governance initiative. In entrepreneurial companies, curation is often handled by a team of data curators or stewards. They not just help to determine and manage the IT systems storing the data but excels in the context, content, and ownership of the data. Data curation is linked with metadata management as the way that data is tagged, defined, and managed is through the metadata.

Benefits of Data Curation for Businesses

  1. Improved data quality: Data curation ensures data quality at all levels. Curated data is free of redundancies, cleaned, and organized, making it easy to spot and correct leftover errors. Moreover, the usability and quality of a company’s data are directly linked with how much of an asset it can become when achieving business objectives.
  2. Added value: Data curation contributes significant business value by effectively processing data assets, akin to repairing a dysfunctional or poorly functioning tool. While these assets may hold some value even before fixing, their true potential is realized after curation. Through repairing and integrating data, curation brings new value to old assets. Moreover, efficient metadata management and data presentation save time and effort and enable the redirection of resources to more beneficial purposes.
  3. Efficient usage of data assets: Data curation ensures that information assets are used efficiently. This means it eliminates the wastage of storage space since every piece of data can be revitalized through the curation process. The categorization and well-organized metadata resulting from curation enable efficient data utilization in terms of cost-effectiveness and speed.
  4. Enhanced machine learning practices: Machine learning is a vital process in business and finance today, and trained algorithms can immensely improve the results and efficiency of several practices. However, you need high-quality and well-prepared data to train algorithms. Data curation makes immense data stored by the company usable for the training of algorithms.
  5. Increased innovation: Data curation fosters innovation in data handling approaches by encouraging collaborative efforts and promoting the exchange of ideas regarding data and its management. Continuous monitoring of processes facilitates open discussions on issues, potential solutions, and suggestions for improvements. As a result, this collaborative environment leads to the development of innovative data-handling solutions, contributing to a more data-savvy business environment.
  6. More accessible knowledge: Data curation revolves around effectively presenting specific information to individuals with the necessary skills to derive practical value. By discovering and organizing data sets, data curators ensure that the knowledge within these sets becomes accessible to all other professionals within the organization. The strategic presentation of relevant expertise to the appropriate audience opens possibilities for advancing business objectives.


Data curation presents many business benefits indispensable in today’s data-driven world. Organizations can unlock their true potential by systematically organizing and categorizing data, making it more accessible and insightful for decision-makers and analysts. Data curation enhances data quality, ensuring accuracy and reliability in research and analysis, leading to better-informed and strategic business decisions.

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