Get Clean and Stay Clean Solution for Complex Salesforce Application Delivered in 40 days

Client Overview

Non-Profit Catholic Relief organization whose operations mainly involve human capital development for needy communities that have been affected by war, famine and natural disasters.

Project Scope

Extraction of master data records of Institutions, Institution address, Individual & Individual address (Approx. 400K) from Source instance for data cleansing.
Master Data deduplication
Institution related transactional record update for 23 objects.
Individual related transactional record update for 18 objects.

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Business Situation

The Client’s master data quality in salesforce is in bad shape with major problems like duplicates and non-standardized data for its major operational objects. For Example, consider in the name of Catholic Church (institution), there might be 5 records which should be a single record and those 5 records has n number of institution address which needs to group to single institution. Due to it the accurate data is not present in system.

Technical Solution

Transformation logic for Data cleansing and data standardization
Duplicate check
Reparenting transactional objects (Institution has 23 transactional objects and individual has 18 transactional objects)
Reparenting code needs to be done in Salesforce without affecting the existing functionalities.
Migration of huge volume of data
Need to extract huge number of records
To extract the records, filter condition is provided, By using that filter condition we need to extract the From and To relationship of the child object which is a challenging one.

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Solutions

The Institution and the institution address will be combined and maintained in another object in dataZen.
The Individual and the individual address will be combined and maintained in another object in dataZen.
Implement 60+ Transformation logics for Data cleansing
Google API and USPS
Match and Merge rule to deduplicate data
After completion of the match process the data will be submitted to the business users to confirm on the merge process for final review & actions.
After final confirmation from the business users the data will be moved to dataZen golden hub.
After the golden hub is confirmed the data would need to be moved to Salesforce (CRSfullsandbox & Production instance).
Code development in Salesforce for reparenting transactional objects

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Illustrations

No items found.

Benefits

Data Standardization
Approx 15K records has been cleaned from the master objects.
Increased data accuracy
Eliminate poor quality data
A Single source of truth
Clean master data lead to operation excellence
Reduction in cost and effort for business users in the new rollouts

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Products & Services Used

dataZap - Pre-Configured Templates & Migration Engine to Extract, Transform, Pre-Validate, Load, Reconcile & Report.

dataZen - To 'Get Clean' and 'Stay Clean', and Introduce Master Data Governance.

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Industry:

Get Clean and Stay Clean Solution for Complex Salesforce Application Delivered in 40 days