Blog > Data Quality > 4 Steps Toward Better Data Management

4 Steps Toward Better Data Management

Authors Photo Precisely Editor | July 20, 2020

In April 2019, digital magazine Raconteur predicted that by 2020, the digital universe would be 44 zettabytes. That means that there are 40 times more bytes than there are stars in the observable cosmos. That’s why putting a data management plan in place is so important. 

For the enterprise, this statistic represents an opportunity as well as a risk; when information is managed properly, it’s valuable and helps you make better decisions. When information isn’t managed properly, it becomes more of a liability.

The four steps toward better data management

Step 1: Carry out a data audit

The first step to creating a data management plan is to carry out a full data audit. While the idea sounds daunting, it’s crucial. We now live in the age of stringent data regulations, and not knowing what kind of information you possess could lead to hefty fines in the event of a breach. 

Make the data audit easier by breaking your information down by type (emails, financial details, statistics, images, etc.) as well as by source (internet server, private data center, customer credit cards, third-party applications, private networks, etc.).

Step 2: Assess your data quality 

Now that you understand what information you have and where it is, the next step in your data management plan is assessing your data quality. “Data quality” refers to the completeness, consistency, uniqueness, validity, timeliness, and accuracy of your information. 

Assessing data quality through manual methods eats up time and valuable resources. Consider using a data quality solution. 

Read our eBook

Fueling Enterprise Data Governance with Data Quality

We’re operating in a world where our expectations about what data can do is growing while at the same time trust and confidence in data is declining. In this eBook, we’ll discuss how to strengthen your data governance framework with improved data quality.

Data management isn’t a one-and-done process. It’s ongoing, so you should put data governance best practices into place. What are data governance best practices? 

“Data governance” refers to the rules and policies related to data ownership, data processes, and data technologies. When you have data governance practices in place, you’re putting a framework in place that bolsters data quality. Information that meets data quality standards is trustworthy, meaning that you can make better decisions with it. 

Step 4: Create a strategy combining people, processes & tools

A data management plan is only as strong as the people, processes, and tools that power it. Those are the components that support a data management plan. 

Think about the people who will manage the tools and carry out the processes in your plan. What are their roles, and what qualifications do they possess? Additionally, what are these processes? Do they sustain data quality as well as security? 

“A data management plan is only as strong as the people, processes, and tools behind it.”

 The right tools do a few things: 

  • Automate processes
  • Scale to handle extremely large data volumes
  • Ensure security 
  • Guarantee data quality 
  • Save time, money, and other resources because they’re easy to use 
  • Enable better decision-making, because you have access to quality data

A data management plan sets the stage for higher-quality data within your organization, which ultimately leads to better business outcomes. To learn more about data quality and data governance, download our eBook: Fueling Enterprise Data Governance with Data Quality