{"id":11926,"date":"2023-01-18T07:00:00","date_gmt":"2023-01-18T15:00:00","guid":{"rendered":"https:\/\/formtek.com\/blog\/?p=11926"},"modified":"2022-06-19T15:47:43","modified_gmt":"2022-06-19T23:47:43","slug":"data-quality-the-critical-factor-for-analytics-success","status":"publish","type":"post","link":"https:\/\/formtek.com\/blog\/data-quality-the-critical-factor-for-analytics-success\/","title":{"rendered":"Data Quality: The Critical Factor for Analytics Success"},"content":{"rendered":"\n

Do you trust your data? It’s increasingly easy to tap data into data analytics, machine learning, and other AI tools, but if the data itself is flawed, out of date, or incomplete, the exercise can turn into a classic case of garbage in\/garbage out.<\/p>\n\n\n\n

A survey by Corinuim Intelligence<\/a> in June 2021 found that 80 percent of senior executives had concerns about the quality of the data used in their projects and found that it was difficult to frequently update and clean data to maintain accuracy, consistency, and context.<\/p>\n\n\n\n

Melody Chien<\/a>, Senior Director Analyst at Gartner, said that<\/a> “data quality is directly linked to the quality of decision making. Good quality data provides better leads, a better understanding of customers, and better customer relationships. Data quality is a competitive advantage that D&A leaders need to improve upon continuously.”<\/p>\n\n\n\n

Abe Gong<\/a>, CEO of Superconductive, said that<\/a> “poor data quality and pipeline debt create organizational friction between stakeholders, with consequences like degraded confidence. Data quality is critical to facilitate the making of decisions with confidence across the organization, enabling a singular understanding of what that data means and what it\u2019s being used for.”<\/p>\n\n\n\n

What kinds of data quality problems are common?<\/a><\/p>\n\n\n\n