Why is Data Quality Important?
Over the past 10 years, the Internet of Things (IoT), artificial intelligence (AI), edge computing, and hybrid clouds all have contributed to exponential growth of big data. Due to which, the maintenance of master data (MDM) has become a more typical task which requires involvement of more data stewards and more controls to ensure data quality.
To support data analytics projects, including business intelligence dashboards, businesses depend on data quality management. Without it, depending on the business (e.g. healthcare), there may be disastrous repercussions, even moral ones.
- Now, organizations that possess high-quality data are able to create key performance indicators (KPIs) that assess the effectiveness of different projects, enabling teams to expand or enhance them more efficiently. Businesses that put a high priority on data quality will surely have an advantage over rivals.
- Teams who have access to high-quality data are better able to pinpoint the locations of operational workflow failures.
What is Data Quality and Why is it Important?
The significance of data quality in today’s data-driven environment is quite impossible to emphasize. The quality of data becomes more crucial when organizations, businesses and individuals depend more and more on it for their work.
This article gives detailed idea of what is data quality? its importance, and the essential procedures for making sure the data we use is correct, reliable, and appropriate for the reason for which data was collected.
Table of Content
- What is Data Quality?
- Data Quality vs Data Integrity
- Data Quality Dimensions
- Why is Data Quality Important?
- What is Good Data Quality?
- How to Improve Data Quality?
- Challenges in Data Quality
- Benefits of Data Quality