Data Migration
When it comes to data migrations, failing to prepare is preparing to fail.
When it comes to data migrations, failing to prepare is preparing to fail.
Many organisations undergoing a data migration encounter unforeseen challenges that increase budgets and throw off timelines.
With the help of our data quality management platform, you gain visibility into your data and achieve greater control over the migration process. De-risk and streamline your migration project to ensure you successfully move your data to the new environment on time and on budget.
In many cases, the complexity and magnitude of data migration is underestimated. At Experian, we partner with our clients and specialist providers to develop the migration scenario most suitable for your needs and requirements.
Landscape Analysis
Identify critical data elements and segregate data into categories. Assess data age and determine data linkages.
Solution Design
Identify source/target mappings. Identify data transformations and run detailed data quality and profiling checks. Identify trends, outliers and anomalies.
Build & Test
Test all data transformations identified in the solution design review data flows to improve consistency, accuracy, validity, completeness, timelines & fitness for use of data.
Project Initiation
Determine the scope and stakeholders involved, begin to define upstream and downstream impacts of the data migration.
Decommission & Monitor
Decommission source systems and run in oarallel for specified time. Archive and purge data where required. Ensure an ongoing process to measure and correct Data Quality issues is proven.
Execute & Validate
Execute build and test plans; run detailed data profiling and quality checks on target systems, identify orphan records and handover for UAT.
Format, clean and standardise your data as it flows in from different sources with Experian Data Quality. Aperture Data Studio, a powerful and easy to use data management suite can then help you to merge those data sets in your own environment.
Clean data in your CRM is vital. Experian can help with batch cleanses of your existing data across Address, Email and Phone. Once imported into your new CRM Experian can then bring advanced data quality solutions seamlessly into your CRM system so you can create and maintain an accurate view of your customers in real time.
Before migrating, all records should go through some Data Quality control measures. Profile your data, analyse existing records looking for anomalies and inconsistencies. Cleanse your data, standardise your data and remove duplicates. Finally, Enrich relevant records and implement business rules to ensure your data remains clean and UpToDate.
SCV in a Data Quality context refers to a Single Customer View, similar terms are Golden Record, and Unified Customer View. Experian's Single Customer View solutions incorporate best in class data preparation, data matching, golden record creation, monitoring and consultancy capabilities.
Our approach to creating a single customer view (SCV) focuses on a methodology that will consolidate, clean, fix, link, harmonise and enrich your data. The 4 stages we focus on are; Investigate, Assess, Improve and Control.
AI can rapidly identify data quality errors. In some cases it can then be used to standardise and repair certain data fields. (For example highlighting missing or incomplete data).
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