Secure Data Migration Journey For A Leading Construction Company
- Technology: Microsoft SQL Server, Azure Data Factory
- Industry: Construction and Development
About Client
Business Objectives
Solution
The migration process began with the extraction of data from the source on-premises ERP database using Azure Data Factory (ADF). Configuration tables in the target environment specified the extraction parameters and rules, ensuring precise and tailored data extraction. The extracted data was temporarily stored in the StageDB schema within the target cloud environment.
Once the data was staged in the StageDB schema, we applied mappings using predefined mapping tables in the target system. These tables translated source data values to their corresponding target values, ensuring consistent and accurate data representation. After mapping, the data underwent transformation processes and was then loaded into the actual target tables of the cloud-based ERP.
For specific data sets, we utilized templates within the ERP system. Mapped data was converted into CSV files, which were then uploaded into the ERP system. These templates facilitated the automated population of the relevant tables, streamlining the migration process.
We employed configuration tables to guide the data extraction and migration process, as well as dashboard configurations in the target environment. Mapping tables were used to store and manage the relationships between source and target data values, ensuring accurate translation during migration.
- Data Migration Workflow
1.Extract Data: Data was extracted from the source ERP database into the StageDB schema in the target environment, following configurations in the configuration tables.
2.Stage Data: The StageDB schema served as an intermediary, holding the data before mappings were applied.
3.Apply Mappings: Source values were translated into target values using the mapping tables in the target system.
4.Populate Target Tables: The mapped and transformed data was loaded into the target tables, completing the migration process.
- Key Considerations
Robust error handling and logging mechanisms were implemented to ensure data integrity. These tools allowed for quick identification and resolution of issues, minimizing potential downtime.
The migration process was optimized through parallel processing in ADF, enabling efficient handling of large data volumes. Indexing and partitioning strategies were also employed to enhance query performance in both the StageDB and target tables.
Data security was paramount throughout the migration. Data was encrypted both during transfer and at rest, adhering to industry standards and compliance requirements, including GDPR, to safeguard sensitive information.
A real-time monitoring system was established to track the progress of the migration. Alerts and notifications were configured to promptly inform the team of any issues to ensure timely interventions.
- Construction Data KPIs and Modules
- Managing vendor invoices and payments.
- Handling customer invoices and collections.
- Tracking equipment usage, maintenance, and costs.
- Monitoring project costs and budgets.
- Controlling and reporting on costs associated with construction projects.
- Maintaining the financial records of the organization.
- Validation and Auditing
- We developed dashboards to display both summary and detailed views of different modules. These dashboards provided real-time insights into the migration progress and data integrity.
- Audit stored procedures in the AuditDB schema ensured comprehensive auditing of the data migration process.
- Another validation method involved comparing reports from the source ERP system with those generated in the target ERP system. This ensured that the data migration was accurate and complete.
Architecture Diagram
Results
In Our Customers’ Words
Real pleasure consulting with Kenexai to set up our company’s entire data warehouse and dashboards on AWS. I will definitely be reaching out to them for future work to be done. Our project was effective and 100% achieved what I planned to do in the beginning, in a shorter time frame and with less effort than I expected.
Hans
United States
CCR Data perform complex data migrations, we needed and extra pair of hands to restore an Oracle database and transfer the data to a Microsoft SQL database ready for our migration analysts to do their stuff. We would not hesitate in recommending or using Kenexai again and would be happy to outsource bigger projects to them in the future.
Henry Sykes
Director - CCR Data
I have used RA on numerous occasions over the past 2 years, specifically with Nitesh Solanki for the delivery on PDI ETL jobs. I am very happy with him and the high level of quality work he has provided. He seems to be available all the time and works extremely hard to deliver high quality solutions.
Mark Scriven
Technical Director - Value Ad