Data Mapping Best Practices
Data mapping refers to the process of matching fields from one database to another. This is the first step to facilitating data migration, integrations, and other forms of data management. Data mapping helps organize, distill, analyze and understand large amounts of data that lives in multiple locations. Before an enterprise can analyze their data for business initiatives, the data must be homogenized in an accessible way for decision-makers.
The benefits of data mapping include integrating, transforming, and migrating data while also creating data warehouses quickly. Data mapping ensures that the data collected is not only quality data but accurate data. Organizations can identify real-time trends and share data points with members of their teams. The benefits go on and on, but the only way to reap the rewards is to execute properly. So here are a few best practice tips.
The Right Approach
First and foremost, you must have the right resources to map your data flow. Identifying the right plan or tools for data mapping will depend on the type and volume of data collected by an organization. There are plenty of free data mapping templates to help conduct the process. Additionally, there are many tools and software available if you’d prefer an automated process.
It’s all about selecting the right approach for your organization.
Mapping can be implemented across an organization or one unit at a time. Because data mapping can involve people across different teams within an organization, the approach will largely depend on the budget and resources available for the project. Regardless, companies should include all necessary groups to conduct a high-level overview of the activities and build out a comprehensive plan.
Select the Right Solution/Tools
Data mapping, or any data-related process, is a complex one. The tool(s) used for data mapping will have a significant implication on the outcome. Your organization’s specific complexities should be taken into consideration when picking the right tool for the job.
A few factors to consider when picking the right mapping tool:
A diverse set of source systems
Automation and scheduling
Track changes
Delta changes
Personal data identification
User interface
Identify and Involve Data Owners
When mapping, there can be varying degrees of risk. One way to reduce complexity is to identify the data owner. It’s critical to identify data owners and stewards responsible for representing different parts of your organization. The identified stakeholders will be responsible for the data within your organization. They will know the ins and outs better than anyone else. They’ll be an essential point of contact because they bring history and context to the data.
Ensure Data Security
Customer data is essential. That’s why data security is crucial when carrying out the data mapping process. Enterprises must protect data against any unauthorized access, theft, loss, damage, and unlawful disclosure. If using any automated tools for data mapping, be sure the tools offer security features that will protect your data. Discuss best practices your organization’s implemented for the safe dispersal of customer data.
Maintenance
Creating an effortless system is the goal. The best way to ensure the system continues to run smoothly and effectively is to frame and execute routine maintenance. For example, updating or modifying a flow might be necessary if you need to address the challenges of a use case. Alterations can cause disruption; therefore, it’s best to ensure the accuracy of your mappings before executing the process.
Document the Process
Data comes and goes. Some data will be removed if it’s been used for a long time and no longer serves a purpose. Newer data needs to be collected to reflect real-time changes and trends for an organization. It should go without saying, keeping a record of all data mapping processes will help avoid any discrepancies. Documenting also helps set standards and regulations for data mapping changes and upgrades that need to be made in the future.
Planning and preparing will go a long when it comes to data mapping for your organization. Ultimately, it’s all about using quality data tools that help simplify and optimize the process in an efficient manner. These are just a few of the practices that can promote optimal results.
Maybe you aren’t sure where to begin. Perhaps you don’t know how to implement these practices in an already established process. Let’s talk about creating the best data mapping process for your organization’s needs and goals!
