Best of 2022: Top 5 Data Quality and Data Governance Blog Posts
The common goal of many data governance programs is to increase visibility around the quality of data for better business outcomes. As this year comes to a close, let’s count down the Top 5 Data Quality and Data Governance blog posts of 2022.
#5 Kickstart a Data Quality Strategy to Build Trust in Your Data
Data quality strategy plays a foundational role within the broader context of data integrity. From the executive suite to the front lines, the people who rely on analytics to help them make important decisions must know that they can trust the integrity of the underlying data. Establishing that trust typically begins with a good data quality strategy and data lineage tools that profile and catalog your enterprise data. This creates a strong foundation on which to build confidence in data-driven decisions. Read more >
#4 Four Reasons to Prioritize Data Quality
Few organizations have created dedicated data quality teams, according to a study from O’Reilly Radar. To make matters worse, only 20% of companies track and report data lineage. And while reliable analytical insights require high-integrity data, many organizations only prioritize data quality when revenue, brand reputation, or regulated data is on the line.
Companies can’t wait for a data quality emergency to provide evidence that poor integrity data harms an organization’s financials, reporting, customer experience, and more. Regardless of the company’s industry or size, data quality is critical to a data management strategy. Read more >
#3 Real-time Data Quality and Data Enrichment as-a-Service
Real-world applications of data and analytics are exploding, due to the power and affordability of advanced analytics and the explosion of information is available than ever before.
As the quest for powerful data insights captures the attention of business leaders across every industry, many are realizing the benefits of introducing curated third-party data into their analytics initiatives. These leaders they have developed a keen awareness that unless they proactively manage and control data quality, their data analytics will fall short of expectations, or worse yet, will deliver the wrong results altogether. Read more >
Read the analyst report
Data Professionals Speak: Trends In Data Governance and Data Quality
Learn what 800+ data & analytics leaders shared about the choices their organizations are making today, which appear most effective in charting a path to data governance maturity and ultimately, data integrity.
#2 Metadata Management vs. Master Data Management
Metadata management and master data management might sound like similar terms, but the difference is very important. Both are essential to virtually any enterprise. To understand why, you’ll need to understand a few things about both categories of data. Read more >
#1 Building a Business Case for Data Governance: Here’s how
There’s no denying data is a valuable organizational asset. It represents the key to business development and organizational success. If an organization isn’t analyzing data to enhance business processes, uncover customer insights and identify competitive opportunities, they have almost no chance to remain competitive. Building a data governance business case is the key. Read more >
Learn what 800+ data & analytics leaders shared about the choices their organizations are making today, which appear most effective in charting a path to data governance maturity and ultimately, data integrity. Read the report.