Data Migration

Data migration is a key element to consider when adopting any new system. It improves data efficiency and effectiveness and provides more timely, accurate data for effective decision making. Tenzing’s data migration solution assists clients in deploying new solutions as well as enhancing existing solutions.

Our migration strategy mitigates risk by:

  • Including key business / data SME’s 
  • Using a data conversion tool enabling rapid development of data transformation programmes
  • Creating a resilient migration framework
  • Executing mock go-lives against a stable target system.

We believe the key elements to successful data migration and cleansing include planning, focussing on areas of high complexity, and keeping the business engaged. As legacy data is loaded into the staging area and test scenarios executed, a number of changes will need to be made. To achieve this Tenzing adopt the following approach:

  • Migration strategy and planning
  • Conversion design, execution and testing
  • Risk mitigation

The approach leverages off other core capabilities within Tenzing’s information management services, including business performance management and business intelligence. It addresses the complex issues surrounding data quality in a structured and predicable manner and reduces the overall risk to implementations. 

Tenzing’s approach to data migration

  • Extract - Source system data should be extracted from each of the source systems on as regularly as possible. Preferably, this should be a nightly process as new data can be transformed and tested on a regular basis. Otherwise a monthly or bi-monthly refresh of source system data should be scheduled.
  • Stage - The source system extracts will be loaded into a common staging area. It is important to keep this process as simple as possible. Data in the staging area will be fully refreshed for  each of the source systems in scope. Where certain tables are too large to be fully refreshed, a delta process will be applied by selecting all records loaded since the previous load. Manual off-system files, databases as well as enrichments files will also be loaded into the staging area.
  • Transform - The data mappings defined by the business data analysis will be realised as data transformation programs. The transformation section of the migration process is where all the business rules will be coded. Staging data will be transformed using data mappings into an intermediate enriched format. Additional data fields will be available in this layer to support analysis of data transformation / data quality issues.
  • Validate - Data validation rules will also be built in this layer to test the data mappings and identify outliers.  Data which fails validation will be exported to a set of reject tables which will be reviewed by the business representatives on an ongoing basis. Obsolete data may be piped to a set of obsolete tables for the business to review if required.
  • Export - Before loading data into the staging schema, data will be loaded into a set of export tables from the transformation layer. This provides the migration team the ability to view/audit data in its final form before loading into the staging schema. It is also anticipated that staging may not allow some of the data to be loaded due to internal validation rules. This would significantly impact the transformation process if not separated into another layer. Adding this layer also gives us flexibility as we can test the load with a subset of data if required.

Data Migration for SAP

Tenzing's consultants have extensive experience implementing and migrating data into SAP. Implementing SAP is a challenge, both in terms of resources (people, money, time) and in business process. A proven methodology that provides a realistic planning, a solid supporting project structure, a way to manage the process and control tools to manage risk.

An important part of any SAP implementation is getting the data into the system. Previous implementations of SAP have shown that data migration can amount up to about 40% of the entire project. Poor data conversion can make your Go Live and ensuing post Go Live processes very difficult.

Data migration is not purely technical activities to assign to the programmers. Most, if not all, of the data quality issues encountered in the conversion process will be functional or business related. Getting the right data at the right place with the values required for the new SAP business processes is always a challenge.

SAP is a process-oriented system and master data is an integral part of this process. This means that everything is integrated together and tightly coupled to the system configuration. Master data is dependent on the configuration, the configuration is designed to support your processes, and master data is needed to run your process.

Our team know these challenges and have developed frameworks and techniques to manage and simplify the approach.