We are Implementing Data Validation Process for our Organization for which we are thinking to implement following techniques:

  1. Apply validation rules for every object in order to maintain Data Quality, which would be approx 5-10 rules per object. There are more then 30 Objects in which we do bulk DataLoad of which some are dependent on each other.

Here I want to know how this will impact our salesforce performance towards End User or Developers.

  1. To use some AppExchange application to achieve Data Integrity & Validation eg. FormatMe, DupeCather.

I want some suggestions on this from everyone on how to Implement this? Which are the best practices involved in Data Validation?

Thanks! Chirag

  • As a comment, Validation rules are CPU intensive, you can do your own benchmarking if you like. If you have a lot of data quality stuff going on it might be better to create a validation framework in code in a before trigger. Additionally, anything you can do like make the field required or a UI to enforce data integrity over validation rules could be a good idea from a user experience (or a VF UI) so they do not get stopped after they enter all their data. Especially if a VR enforces a specific format of a field or something. Don't forget about the User Experience when doing all of this.
    – Eric
    Oct 10, 2016 at 11:10

2 Answers 2


How to boost data quality ---

To ensure consistently high data quality, you’ll need to train your users, create and implement a data-quality process, and use available technologies to automate the process whenever possible. Here’s a 6-step approach that’s working for many of our customers.

Profile your data Data profiling is all about understanding your data. You should know where your data comes from: spreadsheets, backend systems, or sticky notes all over reps’ desks. Take an inventory of your data that includes the following information: List your data sources and the names of the fields in which data is stored. Note any potential problems with your data. Do you have automated quality checks before a new record can be saved? Are all fields mapped correctly? For example, the information in the Company field in Microsoft applications usually belongs in the Account field in Salesforce CRM.

In Salesforce CRM, make sure there’s no duplicate information between objects (such as Accounts, Opportunities, and Contacts) and fields (such as State, City, and so on).

Control your data Data control is about achieving data accuracy and ensuring the right users have access to the right information, which also means blocking access, as needed. To control your data, you first need to “clean” it by removing duplicates and errors, and then set up processes and use technologies to keep it clean. Use automated routines or tools to clean your data. You’ll find several of these tools on the AppExchange. Prioritize your data cleanup effort.

First, fix data that’s highly visibly and frequently used, such as addresses and emails. Fix business-specific information next, such as Opportunity types and stages. Finally, remove any duplicate fields; for example, don’t repeat Account information in the Contact object. Get your users to fix their data. You can help by using Salesforce CRM’s validation rules to alert users when data records are incomplete or don’t conform to data-quality standards. Use exception reports and data-quality dashboards to remind users when their Accounts and Contacts are incorrect or incomplete. Scheduling a Dashboard Refresh and sending that information to managers is a great way to encourage compliance. Another data-control challenge is making sure that data ownership and sharing works for your organizational structure.

Review your profiles and role hierarchy and make sure the hierarchy, teams, and groups are kept up to date. Meet frequently with management to keep up with organizational changes. Define the Create, Read, Update, and Delete (CRUD) rights for each profile to ensure users can work with data, as needed.

Integrate your data Most organizations have data in more than one system. Whenever there’s duplicated data in several systems, it’s easy for information to get out of synch. One way to avoid this problem is to integrate your systems so that updates in one system automatically update the others, resulting in a single source of “truth” and making it easier for end users to access information.

Integration was once a huge headache. No more. Salesforce.com offers native connectors to Oracle and SAP systems for easy integration of customer-master records. And the Force.com API can be used for any integration scenario. There are also dozens of integration partners ready to help with any integration need. It's easy to learn about and access the Salesforce CRM data model with our Web Services API Developers Guide.

When designing your integration, evaluate your business applications to determine which one will serve as your system of record (or “master”) for the synchronization process. The system of record can be a different system for different business processes. Integrate your order entry and fulfillment applications with Salesforce CRM for a 360-degree view of your customers.

Augment your data

To make your CRM system even more valuable, augment your data with information that will give your salespeople and managers an edge. For example, a number of third-party organizations such as Dun & Bradstreet and Hoover’s provide valuable information your reps can use to prepare for sales calls. Also make the most of internal market intelligence, such as purchasing patterns or competitive analyses.

To understand what data is valuable, survey your sales and marketing users to see what they want the most.

Check the AppExchange to find partner solutions that can augment your data with external information. Get internal information about your customers’ behavior and buying patterns. Then evaluate whether this information would be helpful to your reps.

Monitor your data

Achieving high-quality data isn’t a one-shot effort, but requires ongoing vigilance. Establishing policies, processes, and tools for monitoring data is crucial to maintaining data quality. Define a centralized process for mass data loads and data-cleansing projects. Both the Force.com platform and the AppExchange have tools that can help with importing and cleansing data.

Use Workflow, Validation Rules, and Force.com code (Apex) to enforce critical business processes.

Create reports and dashboards to monitor data quality. Be sure to leverage free data-quality dashboards available on the AppExchange. By making data quality widely visible, you help make it everyone’s responsibility.

Assign ownership, train users & commit to a data-quality process Users need to know the importance of data integrity and how to do their part in any data-quality initiative. In training users, show them how data quality directly affects their work. It’s also a good idea to assign ultimate responsibility for each region’s data to a super user, geographic lead, or other business owner.

The Bottom Line Bad data is bad for business. Achieving and maintaining high-quality data requires vigilance, good processes, and a little help from technology—including the features in Salesforce CRM, tools from the Force.com platform, and solutions from our partners on the AppExchange.

Because it is integrate with salesforce, I would recommend Data.com which can also be used as a Master Data Management for your entire company for all applications.

  • That was like a lecture on architecting sfdc app with huge data volumes ..wow Mar 27, 2014 at 4:29

The answer to this depends on various factors

1)How complex these validation rules ? 2)Can these rules be handled through some tool before data is imported into the SFDC tables ? 3)What are data volumes you are talking about ?

If data is in huge volumes then its better to cleanse the data outside the SFDC platform and then start loading these data into SFDC.

Although these validation rules needs to be written for the data that will be created through SFDC interface .But if volumes are too much (above 100K) then would recommend switch off the validation and triggers at time of data load ,provided neat and clean data is loaded into SFDC .

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