Managing Data in Salesforce: Key Terms and Processes

Andrew Rieser
By Andrew Rieser | President and Co-Founder, Mountain Point
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As a system of engagement, Salesforce has long been best in class. Manufacturers across the globe use Salesforce to manage relationships with prospects, customers, vendors, influencers, and channel partners.

Increasingly, it's also becoming their system of record with apps like Rootstock Cloud ERP allowing manufacturing companies to house their transactional data on the Salesforce platform as well. Having MRP, production, inventory, logistics, and finance data lined up alongside customer, sales, and service information can give companies a seamless view of their business. 

But, more data is worthless without a comprehensive analytics strategy and a sound data management plan. Ready to dig in? Here are some key terms and processes to help you get started managing data on the Salesforce platform. 

Managing manufacturing data with Salesforce: Key terms and processes

Dashboards: Data visualizations used to communicate information effectively and efficiently. Dashboards can be customized to monitor KPIs, track trends, and communicate calls to action for your company. In addition to reviewing dashboards manually, you can embed dashboards within user homepages, on records, or within lightning app pages to put your most important data front and center. 

Data Export Wizard:A built-in Salesforce tool for exporting data from your system. Using the data export wizard, you can manually export your data once every 7 days (for weekly export) or 29 days (for monthly export). You can also schedule automatic exports on a weekly or monthly basis. 

Data Hygiene: The process of maintaining data quality or "cleanliness." Data hygiene includes policies, procedures, and tools used to ensure data is accurate, up-to-date, and complete. 

Data Import Wizard: A built-in Salesforce tool for uploading data into your system. The Data Import Wizard allows you to upload up to 50,000 records at a time. One key feature of the Data Import Wizard is its ability to identify and ignore duplicate records. However, it does not support importing into all objects with opportunities being the most notable exclusion. 

Data Loader: Data Loader is a Salesforce tool that requires installation. Data Loader allows you to import up to 5 million records at a time and supports all standard and custom objects. You can also schedule automatic uploads such as nightly imports.  

Data Recovery: By default, deleted records in Salesforce are stored in your recycle bin for 15 days.

Descriptive Analytics: Descriptive analytics answer the question “What has happened so far?” These queries expose past trends and analyze historical data to help you better understand your business. Descriptive analytics can help you understand your operations and set baselines for improvement.

Dirty Data: Inaccurate, incomplete, or erroneous data.

Einstein: Einstein is Salesforce's smart assistant driving insight and intelligence across the Salesforce platform. Einstein AI embeds voice input and output, natural language processing, and contextual recommendations within Sales Cloud and other Salesforce tools.   

Einstein Analytics: Einstein Analytics is an advanced analytics platform available as an add-on to your Salesforce system. Sales Cloud, Marketing Cloud, and Service Cloud all offer Analytics add-ons. Salesforce's AI assistant, Einstein, is at the heart of Einstein Analytics providing predictive and automated intelligence. 

ETL (Extract, Transform, Load): ETL encompasses three steps — Extract, Transform, and Load — that allow data from various sources to be merged into a single platform. The term is often used in conversations surrounding data integration, in which a company or organization is working to automate the extraction of data from a system, standardize and map it for the system they want to integrate it with (the system of record), and then load the data into the system of record. Mulesoft, Jitterbit, Boomi, and TIBCO Scribe are common ETL solutions for Salesforce. 

Formula Fields: Formula fields perform calculations or populate data between fields. Use formula fields to prevent user error or redundant data entry by automatically making calculations from other fields. Because the calculated value is not stored, but rather calculated each time data is read, formula fields also help you keep information up-to-date as records change. 

Lookup Filters: Lookup filters restrict user input by verifying it against data from other records. For example, you might use a lookup filter to ensure that users can only select contacts related to the account for which a case has been created. Lookup filters help you maintain consistency and avoid duplicate entry.  

Metadata: Data about other data. Common examples of metadata are creation date, last modified date, tags and categories, author or creator, file type, and geolocation tagging.

O data: Short for "operational data."

Object databases: Salesforce is an object database, meaning that information is organized into relational objects. Standard objects include leads, accounts, contacts, and opportunities. You can think of each object as a separate tab on a spreadsheet. Each record is like an individual row. And each field is like a different column.  

Predictive Analytics: Predictive analytics answer the question “What could happen?” These lines of inquiry can help you anticipate likely events, mitigate potential risk, and assess future opportunities. Predictive analytics can also be applied to your service offering to provide greater value to your customers. 

Prescriptive Analytics: Prescriptive analytics answer the question “What should happen?” The purpose of prescriptive analytics is to determine the best course of action for your business based on insight from predictive models. Prescriptive analytics models can help you prioritize your investments of time, money, and energy.

Process Builder: The process builder allows you to create automatic processes in your system including updating records based on triggers you've identified. For example, you might automatically advance an opportunity to the qualified stage if a meeting with a related contact is scheduled. 

Record IDs: Each record in Salesforce has a unique ID that is often referenced when managing data.

Report Subscription: Salesforce offers the ability to subscribe to reports so that you can receive up-to-date information in your email inbox. 

System of Record: The authoritative data source or "system of truth."  

Upsert: The upsert operation allows you to insert or update an existing record using a record's ID as the key. 

Validation Rules: Validation rules allow you to set criteria to ensure users enter the right type of data in a particular field. Validation rules are useful for preventing incorrect formatting, ensuring consistency, and enforcing policies and procedures. 

X data: Short for "experience data." 

Topics: Analytics, Big Data, Salesforce, Industry 4.0, Data Integrations, Dashboards, Business Intelligence, Shopfloor 360, Supply Chain 360, Customer 360, Einstein Analytics, Einstein

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