Data Governance category
August 30, 2023

7 Data Testing Methods, Why You Need Them & When to Use Them

5 min read - What is data testing? Data testing involves the verification and validation of datasets to confirm they adhere to specific requirements. The objective is to avoid any negative consequences on business operations or decisions arising from errors, inconsistencies, or inaccuracies. In a world where organizations rely heavily on data observability for informed decision-making, effective data testing methods are crucial to ensure high-quality standards across all stages of the data lifecycle—from data collection and storage to processing and analysis.This is part of…

August 30, 2023

8 Data Quality Monitoring Techniques & Metrics to Watch

6 min read - What is data quality monitoring? Data quality monitoring refers to the assessment, measurement and management of an organization’s data in terms of accuracy, consistency and reliability. It utilizes various techniques to identify and resolve data quality issues, ensuring that high-quality data is used for business processes and decision-making.  The importance of data quality cannot be overstated, as poor-quality data can result in incorrect conclusions, inefficient operations and a lack of trust in the information provided by a company’s systems. Monitoring…

August 30, 2023

Building a Winning Data Quality Strategy: Step by Step

5 min read - What Is a Data quality strategy? A data quality strategy details the processes, tools, and techniques employed to ensure your company’s data is accurate, consistent, complete, and up-to-date. A well-defined data quality strategy enables better decision-making based on reliable information and reduces risks associated with poor-quality data. In order to develop a successful data quality strategy, you will need to understand how high-quality information supports decision-making processes and drives growth across your organization, and what factors can impact or reduce…

August 30, 2023

DataOps Framework: 4 Key Components and How to Implement Them

6 min read - What is a DataOps framework? The DataOps framework is a set of practices, processes and technologies that enables organizations to improve the speed, accuracy and reliability of their data management and analytics operations. DataOps is often compared to DevOps and agile methodologies used in software development, as it aims to break down silos, encourage collaboration, and streamline workflows for data teams. The core philosophy of DataOps is to treat data as a valuable asset that must be managed and processed…

Failed to load data
Featured by topic

IBM Newsletters

 Get our newsletters and topic updates that deliver the latest thought leadership and insights on emerging trends.
Subscribe now More newsletters