Quality Data is all about valuable data that is readily available to businesses. That data helps evaluate your market position, understand your audience, identify risks and growth opportunities, understand trends and dynamics, build effective strategies, and eventually drive organization growth.
Bad data leads to wrong decisions, disgruntled customers, high costs, wrong targeting, etc. Even technologies such as artificial intelligence (AI) and machine-learning (ML) require accurate data to function properly.
Data-driven organizations need to trust their data, but the scenario looks grim: some 55% of business leaders don't trust their data assets.
Accurate: Data with no errors or outdated information, redundancies, or typos
Complete: Data with no missing fields, values, or incomplete information.
Relevant: Data that's helpful for your set goals
Valid: Data that's verified and validated and therefore trustworthy
Consistent: Data that remains consistent and aligns with your format
Real-time: Data that's updated consistently and regularly