How VRP unlocks Salesforce’s new data intelligence stack
Salesforce has revolutionized its data intelligence stack since it acquired Tableau. These latest enhancements are empowering customers to unlock value across sales and service.
Read moreLiam Thorpe was surprised when he was offered the COVID vaccine along with the at-risk group. As a man in his 30s with no underlying conditions, he suspected something must have been wrong and contacted his doctor. It turned out they had his height at 6.2 cm and not 6 feet 2 inches giving him a body mass index of 28,000! Although this was a humorous data error with no consequences, other data quality issues can be more serious.
The over 150,000 companies, across every industry, growing their business with Salesforce know the importance of data for delivering value to their customers. However, if that data is incorrect, your business doesn’t stand a chance of success. How many organizations are really concerned about data quality? What exactly is data quality and why is it so important?
An overview of data quality
Let’s start our journey about data quality with a quick overview.
Finding a precise definition of data quality is difficult due to the many contexts in which data is used, as well as the different perspectives such as end-users, database or business. In this article, we mainly discuss the database/business levels.
While data quality includes many aspects, in this article we specifically refer to:
| Age | When was the last time each record was updated? Customer data always changes |
| Completeness | Are all key business fields filled in? If you advertise via sms, have you collected mobile phone numbers for each contact? |
| Accuracy | Is your data as accurate as possible? Has it been checked to reveal typos? Has it been recently reviewed? For example, mobile phone numbers and email addresses can be validated, to avoid empty fields within records in their CRM |
| Consistency | Is the same formatting, spelling, and language used across records? Do you have drop-down lists to ensure consistency? |
| Duplication | Do you have duplicate records and data in your org? Have you considered merging records where a person is both a lead and a contact? |
| Excess data | Do you have any extra fields without values or fields which are not used anywhere else? Should these be researched and populated or removed? |
| Usage | Is your data being harnessed in reports, dashboards and apps? You should only store data you actually use |
Data quality is extensive and important. That’s why there is a lot of research on this topic.
The benefits of clean data
Having clean data ultimately increases overall productivity, informed decision-making and reduces the risk of errors. Other benefits include:
- Removal of duplication errors when multiple data sources are at play
- Fewer errors make for happier clients and less-frustrated employees
- The ability to map different functions fully utilizing your data
- Monitoring errors and better reporting to see where errors are coming from, making it easier to fix incorrect or corrupt data for future applications
- More efficient business practices
Understanding data quality and the tools you need to create, manage, and transform data is an important step toward making efficient and effective business decisions.
There are a lot of ways to investigate data, such as by manual spot checks on a random selection of records or by exporting data to an Excel spreadsheet and looking through each row. While these methods are still used by many companies to explore and fix data, they are not the most efficient way to fix the issues.
Find the best tool to achieve your goal
To support data sustainability in Salesforce, different rules, techniques and applications can be used. First of all, standard Salesforce functionality should be properly configured, for example:
- Duplicate and matching rules: These rules help you find extra records which should not have been created
- Reports and Dashboards in Salesforce can be very helpful to find obsolete data. Reports can be based on specific objects like Lead or Case and can be configured to show (for example) unused records in the past 3 years, (which will most likely not be used in the future). We recommend using the predefined dashboard set from Salesforce: Data Quality Analysis Dashboards App.
- Discover what fields you aren’t using by installing the Field Trip package from AppExchange
- Use standard automation such as Validation rules, Process Builders, Flows and others to fill certain fields. A good implementation can help your user to find the appropriate lead or contact faster or build a better report to show results
- Add External ID for data mastered in other applications to avoid duplication and maintain consistency between systems
- Think about your users, at the end, they are the one entering your data. Make sure that Page Layout are tailored to their needs. Make use of functionalities such as Dynamic Actions and Dynamics forms as well as Screen Flow to guide the data capture and provide context around it.
- To increase the performance in your organization, the Salesforce Platform offers the Big Object functionality. You can archive data from other objects or bring massive datasets from outside systems into a big object to get a full view of your customers. There is no need to store all Cases or Orders for the past ten years if you need them just once a year to build an annual report for your manager. Also, you should keep in mind storage limitations and costs. The big objects functionality is included with your license.
If you are unsure how to start cleaning your data, you can always ask professional consultants to help you. Based on our experience we can recommend the following options:
- A ready-to-go app on the AppExchange. It is a good option that doesn’t require a significant effort, however these applications are not designed specifically for your business and often configurable options are limited
- Sometimes you need to conduct a deep analysis using BI tools like Tableau and Einstein Analytics. These can help in simplifying raw data in an easily understandable format. These insights are clear making actions obvious and simple to implement
- Configure standard Flows and Validation rules; a proper configuration of such elements can help you avoid performance issues and make your solution scalable
- Sometimes the best option for your business is to customize functionality based on Apex logic and Lightning components. This is a more complicated way to create an app to analyze your business data, giving you (almost) limitless options
- Another mass data manipulation too available on the AppExchange is Record EditorX
Don’t neglect your data quality
Data quality and data analysis are significant at any point in a business’s lifecycle. No matter if you started your business a week ago or founded your company decades ago, our architects and developers here at VRP Consulting can help you adjust your processes to fulfill your business requirements. To date we have created and set up wide ranging applications and functionality based on customer requirements, from initial rapid implementations to more complex projects spanning years. Every implementation reaches a point where the data quality needs to be re-evaluated – even when following best practice implementations. Why? Because businesses evolve over time, meaning their data will need to do the same. Often this is overlooked. That’s why our clients call us, to help their data keep up with their business evolution.
Vincent Spehner
VRP Consulting
Certified Technical Architect
About the author
Vincent Spehner is a Certified Technical Architect based in Cambridge, UK with 9-years experience in Salesforce and Mulesoft. His experience of integrations highlighted the need for data quality.
