Flex Your Data Management Skills as a Salesforce Admin

If you’ve tuned into any podcast or blog post on data recently, chances are you’ve heard data referred to in lofty terms. “The oil of the 21st century” and “the lifeblood of any business” are some that come to mind for me. What is definitely true, in the context of your Salesforce environment, is that accurate data is the key to usability of your application. If users aren’t able to work with data that precisely reflects the business process they’re working through, then they’re far less likely to continue to use the application.

Of course, data management doesn’t just apply to the data that your users enter in themselves. Any new implementation features data migration as a key part of the process and is a great chance to ensure accuracy of the data in the org. Also, integration of data from other third-party applications and systems needs to be carefully designed to ensure the right information goes in the right place.

As a Salesforce Admin, you play a key role in ensuring all of these data entry and exit points are designed correctly, and that appropriate controls are in place to validate the data as it comes in to the org. Of course, that data won’t always be 100% correct! So proactive and preventative maintenance of those data controls, as well as the data itself, is another ongoing task in the lengthy set of admin duties.

I’ve been involved in many implementations, integration design meetings, and migration exercises where data accuracy is thrown right to the forefront. Let me take you through my thoughts on what can help a good Salesforce Admin excel in the area of data management.

What is data management?

Alongside making configuration changes and managing access to an org via user management and security management, managing data is a significant responsibility for admins. Data management doesn’t just refer to getting data into the org—it’s also the whole lifecycle of how data is created, updated, and eventually archived or removed.

At a practical level, let’s divide data management into four areas of focus:

1. Data lifecycle

If you’re part of a larger organization, this important part of determining how data is handled in the system is often led by the data or solution architecture teams. However, all admins (especially solo admins) should definitely have an understanding of what data lifecycle means, since it’ll likely be up to you to manage some of the controls and processes that implement specific data lifecycles. At a basic level, there are two things that are a good start to discussions around the lifecycle of data in an org:

• Having an understanding of the longevity and validity of different datasets in your org
• Knowing which datasets could be archived or removed and after what sort of timeframe—since data storage is expensive!

2. Data quality through controls

This is where you can really flex your admin muscles! Once you know how data needs to be handled, you can think about the different controls to put in place to support this:

• At a field level using required fields
• With some business logic using validation and duplicate management rules
• For more advanced data capture scenarios, you could even consider using screen flows to guide a user through entry of a more complex record or records of data. For example, from a usability perspective, it might be a better idea to have a custom Lightning page that allows entry of multiple records on the one page rather than having to click through Save and New endlessly.

3. Data monitoring

No set of data quality controls will be perfect, so you also need to work out what sort of exceptions and data issues are likely to crop up. You can do this by setting up data quality reports to periodically highlight where there could be records of data that require further investigation. Here are three tips to help you do this successfully:

• Schedule the reports to be sent to you on a weekly basis. That way, you’ll have a level of automation behind your data quality reports.
• If there are specific data owners who need to take an active part in the management or correction of those exceptions, you might even schedule specific data quality reports to be sent directly to those people.
• For a level of tracking on who needs to do what, you could even use some automated flows to find the exception records and autogenerate a task for the relevant owner!

4. Data analysis

Over time, you’ll build up a significant set of data in your org, which can be used to show some extremely useful trends as to how data is being compiled and used over time. This is really where data analysis comes into play, by providing valuable insights into the data and metadata your org is generating.

• The topic of data analysis really demands a whole discussion in itself! Check out the companion blog post in this series to get more information on this part of the data management process.

Why is data management important for Salesforce Admins?

Having a well-rounded view of the above will ensure that, as an admin, you get a seat at the table when discussions around data design, input, and output occur. You don’t have to be an expert in all of these areas, but being able to listen for key discussions around data, and knowing how to respond, will ensure your value to your wider team is recognized.

At a minimum, you should know the different types of admin controls that are possible in your Salesforce org, and some of the advantages and disadvantages of each. That way, you can provide valuable advice when you’re looking to configure data controls.

Don’t forget that data can also come from third-pary sources and other applications, so having some familiarity with external tools used to integrate data into Salesforce can also be beneficial. These are often referred to as ETL tools, which stands for extract, transform, and load. Having great data management expertise will also help you confidently contribute to discussions around how data is integrated from these applications and tools, opening up a path into the world of integration architecture.

Further still, a large part of enterprise architecture discussions center around not just how different applications talk to each other and what business processes can be managed across those applications, but also what types of data are exchanged and where some of those key datasets are mastered. Having a great foundation in data management can easily set you up for further career growth into those areas of architecture.

How can I learn and develop my data management skills?

Like any skill, learning about data management is an ongoing and iterative process. If you haven’t had any exposure to the world of data before, then I’d suggest some background reading on data lifecycles and brushing up on your Salesforce Admin skills, specifically on how required fields and validation & duplicate rules work.

• The Salesforce Data Management Best Practice Guide is a great place to get an overview of the different areas that data management encompasses.
• You can also start with this great trailmix from Priyanka Mukherjee which covers import and export of data, and duplicate management.
• Get a great overview of fields and validation rules in the data modeling and validation modules, both part of the Platform App Builder credential.
• Finally, check out the Duplicate Management module for more information on duplicate and matching rules.

Getting a bit more advanced, the parts I mentioned about flows are worth diving into deeper:

• The Flow Builder module covers both screen and automated flows.
• That module is part of the Build Flows with Flow Builder trail which is well worth a closer look.

Finally, the Reports & Dashboards Specialist superbadge is a great way to get the expertise you need for data quality reporting to help you manage your data on an ongoing basis.

I hope you can now get the sense that understanding the lifecycle of data, and knowing how to proactively manage that data, is critical to your success when overseeing any Salesforce org. As an admin, you can set yourself apart from other potential candidates by sharing real-world experience of how you took responsibility for data management.

At a practical level, make sure you’re up to speed on how to use different types of rules, data exception reporting, and flows for managing data in your org. And #AwesomeAdmins should continue to have a vested interest in ensuring the data in their orgs is up to date, accurate, and usable for the wider community of users.

Take these three steps to build your success:

1. Explore the new Salesforce Admin Skills Kit to learn how to represent your skills when applying for admin jobs or preparing for performance reviews.
2. Share these skills on social media using #AwesomeAdmin, and tell other admins three skills you’re going to commit to developing this year.
3. Revisit admin.salesforce.com next Tuesday for the next blog post in this series!

Resources

• Salesforce Help: Data Management Best Practice Guide
• Trailhead Trailmix: Data Management
• Trailhead Module: Data Modeling