Data Cleansing

As a business grows and matures, the size, number, formats, and types of its data assets change along with it. At ZoftSolutions, our aim is to improve your data quality and utility by catching and correcting errors before it is transferred to a target database or data warehouse

Our Approch

Step 1

Identify the Data Source to be Cleansed

Step 2

Profile the Data Source to Assess Data Quality.

Step 3

Define Rules for Data Cleansing.

Step 4

Identifying libraries or Third-Party Sourcing for Larger Cleansing.

Step 5

Provide Cleansed Data for Business Use Along with Scorecard of Profiled data.

Package Deliverables

A scorecard of profiled data

Cleansed data set for Business use

Package Goal

Focus is on creating a single source of truth (SSOT) for the business with the help of a Proof of Concept (POC) of Low Complexity.

TimeLine

4 to 8 weeks