Understanding data is crucial for any organization's success, making clear data quality standards is vital for any information system. This “data integrity” maintains and assures the accuracy of data through a project’s entire lifecycle. Furthermore, data integrity ensures that data is both accurate and reliable.
Sources of Data Inconsistencies
In large organizations, it is common for multiple users to have inconsistent data inputs. Often, users prefer different data management systems, leading to a trail of misaligned data across the organization. For instance, one team might use Excel, while another uses Smartsheet. This situation can be frustrating; however, it also presents an opportunity to understand why users prefer certain systems over others. This insight can deliver value in selecting the best data management system for your teams.
Tip 1: Data Dictionary
If data terminology seems confusing across your organization, it is best practice to start with a data dictionary. A data dictionary explains vocabulary and acronyms commonly used within your organization. Having a data dictionary can help your team communicate more effectively, allowing you to achieve better results (Data Dictionaries: A Comprehensive Guide | Splunk).
This data dictionary is best when supported by a team that is committed to ensuring data is accurate and the correct stakeholders are involved. Data governance policies can be an impactful way to ensure accountability within an organization. Furthermore, it is important to have a group of data stewards. Data stewards are individuals within your organization who are committed to ensuring data accuracy and engaging key stakeholders in a positive way that impacts your data.
Tip 2: Data Process Maps
Even with the best data dictionary, understanding an organization's data processes are critical. Process mapping tools like Visio and Lucid Chart are excellent tools to ensure that an organization understands how data flows from beginning to end. Data owners should first conduct user interviews to understand how different systems and processes are used. As you create a visual representation of data flow and processes, it may reveal unidentified process gaps and uncover ways to educate users.
Tip 3: Ask the Right Questions before Selecting a System
Overall, it is critical to ask the right questions so that you have a thorough understanding of everyone's workflow.
Questions for example may include:
- Can you describe a typical day using Smartsheet/Excel?
- How much of your time is typically spent dealing with (issue/task)?
- What are some of your main pain points when dealing with this part of the (issue/task)?
- Does there need to be an alert system in place for a particular piece of information?
- Is there a process that needs to be further automated?
The goal of asking questions like the ones above is to ensure the right decisions, while using the right information system.
Once you have completed a process map utilizing tools like Visio and Lucid Chart, it can be empowering for your team to understand the full workflow from beginning to end. Data integrity may seem like a daunting concept but creating a strong foundation will reduce bottlenecks and create a more sustainable database in the future.
