Multi-Domain MDM Challenges
The maturity of Enterprise Multidomain Master Data Management (MDM) programmes has broadened its scope and applicabil...
Our approach to data migration has evolved to maximise the
efficiencies brought by both delivery methodologies
and technical advances.
There are many key components that provide an environment for successful
data migrations:
- 01. Approach - a tried and tested methodology that provides a framework that includes a tool-box of processes, templates and technical frameworks, including Mainframe, SAP and Oracle ERP solutions.
- 02. Data Quality - the heart of every migration, data profiling and cleansing are an integral to success
- 03. Accurate Estimating - DDC has invested in a global data migration estimation tool that is continuously refined.
- 04. Integrated Teams - specifically constructed to maximise effectiveness within a large program ensuring detailed data requirements are captured from both relevant legacy data experts (as-is) as well as the functional consultants (to-be).
- 05. Automated, Repeatable Process - migrations have many moving parts, it is imperative that each part executed correctly, Extract Transform Load (ETL) tools are used to achieve this mechanised, tested process. DDC has expertise in (and partners with) all major ETL vendors.
Data Migration Approach
The purpose of this section is to describe the approach that we recommend
migrating data from the legacy applications into strategic applications.
- 01. Methodology - the artefacts and process around getting the detail of the migration agreed by the business and application SME’s.
- 02. Technology - the tooling and the design and build of the migration processes using an ETL approach that can be re-used across subsequent data migrations.
Using a series of workshops DDC will deliver the following:
- 01. Data Migration Plan - with the key milestones identified.
- 02. Data Migration Strategy - covering the scope of the data to be migrated, extract rules, solution architecture, business acceptance and cutover.
- 03. Data Mapping Reports - detailing the source to target mapping rules, underpinned by a data analysis exercise on the source system.
Each of these deliverables will need to be reviewed and signed-off by the customer.
These activities should be led and managed
by the data migration stream with key inputs
coming from Business SME’s, Source and
Target System SME’s.
The Data Migration approach is used to its best when considering
a typical Data Project on the below aspects:
DDC’s approach to migration is a blend of the methodologies, processes, and dedicated resources supported by a suite of integration tools.
A core concept of our data migration approach are iterations to accommodate the inevitable changes that are driven from both the evolving solution and the complexities of the source systems.
The method supports both a manual and automated approach towards data migration, data quality improvement and verification tasks.
All Data Quality Improvement tasks must be completed before performing the data migration. As a result, (technical) phase planning will vary across streams. The main advantage of this guiding principle is found in the flexibility that it brings to the engagement and migration manager. By carefully planning each individual stream, an optimum result can be found between timely delivery whilst making use of scarce resources in quiet periods.
The method contains verification tasks to demonstrate the completeness and correctness of the data migration. Data migration can support the acceptance of the target information system. Customer confidence in the data migration process is therefore a key for successful implementation.
The Data Migration Method comprises validation and verification tasks that are aimed at quantifying progress and quality of the data conversion. By repeating these measurements and comparing the results to earlier measurements a complete audit trail is built up, satisfying the need for stakeholders
Extract, transform and load (ETL) refers to three separate functions combined into a single programming tool. First, the extract function reads data from a specified source database and extracts a desired subset of data. Next, the transform function works with the acquired data - using rules or lookup tables or creating combinations with other data - to convert it to the desired state. Finally, the load function is used to write the resulting data (either all the subset or just the changes) to a target database, which may or may not have previously existed. The ETL process will incorporate all the necessary transformations needed while migrating the data.
This approach provides a robust method and set of tools to successfully migrate data
from legacy systems to the target solution.
Typical Engagement
DDC helps a Data Migration Project by providing inputs into their overall Data Migration and assist their Data SME during the implementation with the help of a specialist Data Migration Consultant. The consultant will be engaged during starting from the project initiation stages to the golive and hypercare phase in a fixed capacity/time-boxed commitment.
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