Best Practices For Large Data Volumes

Your Org has tens of thousands of users, tens of millions of records, or hundreds of gigabytes of total record storage, have to follow best practices. Few Considerations:

Skinny Tables
Recommended to make your query fast. Important for batches taking long time to execute.Indexes
Use index fields in where clause of Query. Multiple indexed field in query make it more faster. Even use Two-Column Custom Indexes. Two-column index is more efficient than single indexes on same fields.Divisions
Partitioning the data of large deployments to reduce the number of records returned by queries and reports. For example, a deployment with many customer records might create divisions called US, EMEA, and APAC to separate the customers into smaller groups that are likely to have few interrelationships.

Mashups
One approach to reducing the amount of data in Salesforce is to maintain large data sets in a different application, and then make that application available to Salesforce as needed.

Deleting Data
Delete unused or unnecessary data. Use Bulk API’s hard delete option, which allows records to bypass the Recycle Bin and become immediately available for deletion.

Search
When large volumes of data are added or changed, the search system must index that information before it becomes available for search by all users, and this process might take a long time.

Indexing with Nulls
Idea to reduce Null values, replace with NA or blank. Either use formula field to set value and index formula field.

API Performance
Add addition filter in rest API’s query, so they dont scan all salesforce data. 

Sort Optimization on a Query
Add a limit or sort order in query to make it fast and scan a limit of data only.

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