Modern Data Quality refers to the process of ensuring that data is accurate, reliable, consistent, and up-to-date in today’s data-driven environment. It involves implementing advanced… Read More »Modern data quality management
Modern data quality practices make use of new technology, automation, and machine learning to handle a variety of data sources, ensure real-time processing, and stimulate… Read More »Difference Between Modern and Traditional Data Quality – DQLabs
Data Engineers: We look into Data Engineering, which combines three core practices around Data Management, Software Engineering, and I&O. This focuses primarily on reconstituting data… Read More »How do different personas in an organization see data quality?
As companies gather seemingly endless data streams from an increasing number of sources, they start to amass an ecosystem of data storage, would-be end-users, and… Read More »Data observability vs data quality
An organization with 1000 employees, in 2022, has an average of 177 SaaS applications. Most of these applications store data relevant to their needs, However,… Read More »Modern data quality approach
The goal of a data quality program is to build trust in data. However, trust is an expansive, and often ill-defined term that can include… Read More »Top 4 Benefits of Modern Data Quality
The need for high-quality, trustworthy data in our world will never go away. Treating data quality as a technical problem and not a business problem… Read More »4 pillars of modern data quality
With the growth in data and the adoption of cloud architecture or hybrid with data spread across cloud and on-premise, both producers and consumers of… Read More »What is Modern Data Quality?
Trustable data can be defined as data that comes from specific and trusted sources and is used according to its intended use. It is delivered in the appropriate format and time frames for specific users.
With the world’s data multiplying in leaps and bounds, every organization is trying to make better business decisions in marketing, product development, and finance using insights from the data they hold. The value of businesses today can be measured by the quality of the data they hold.
