SAP Data Archival and Reporting for a Prominent Construction Firm

Technology: SAP Hana, Microsoft SQL Server, Azure Data Factory, Power BI

Industry: Construction and Development

About Client

The client is a prominent Canadian construction company specializing in large-scale infrastructure and building projects. Committed to innovation and digital transformation, the organization leverages SAP HANA for transactional data management. Over time, rapid data growth has led to system performance challenges, rising storage costs, and compliance concerns. To address these, the client sought a scalable, cost-efficient SAP data archival and reporting solution that ensures optimized performance and seamless access to historical data for analytics.

Business Objectives

The primary objective was to enhance SAP HANA performance and streamline data management by archiving historical data while maintaining full accessibility for business reporting and analytics. As transactional data volumes expanded, system responsiveness declined, impacting operational efficiency. The solution aimed to offload infrequently accessed data into an external SQL Server environment, improving query performance and ensuring a seamless user experience across business functions.

Given SAP HANA’s in-memory architecture and associated infrastructure costs, the initiative sought a cost-effective archival approach by migrating older datasets to SQL Server. Leveraging Azure Data Factory (ADF) enabled automated, scheduled, and scalable data movement, eliminating manual processes prone to errors and reducing resource overheads.

The solution also prioritized data-driven decision-making by enabling advanced reporting and analytics. Using SQL Server Data Models and Microsoft Power BI, the organization could efficiently analyze archived data through interactive dashboards, trend visualizations, and KPI tracking.

Additionally, to ensure continuity and usability, existing SAP reports were functionally recreated within SQL Server, preserving familiar reporting structures while extending analytical capabilities within a more flexible, cost-efficient environment.

Solution

To address the challenges of performance degradation, rising storage costs, and limited reporting flexibility, a comprehensive SAP Data Archival and Reporting Solution was implemented using Azure Data Factory (ADF), SQL Server, and Microsoft Power BI. The architecture ensured seamless data movement, optimized storage, and intelligent analytics while maintaining governance and accessibility.

1. Data Extraction with Azure Data Factory (ADF)

Using the native SAP HANA connector in ADF, the required transactional and master data tables were extracted from SAP HANA and imported into a designated SQL Server environment. ADF pipelines enabled automated, scheduled, and incremental data transfers, ensuring data freshness and reliability. The process minimized manual effort while providing high-performance integration between SAP and Microsoft ecosystems.

2. Data Archival in SQL Server (ArchivedDB)

Historical SAP data was securely archived into a dedicated SQL Server database (ArchivedDB) for long-term retention and cost-efficient storage. Each SAP table was replicated and optimized for analytical workloads. SQL-based transformation scripts were implemented to design data models and relational structures, improving query efficiency and enabling faster data retrieval. This approach ensured data consistency, scalability, and auditability while reducing SAP HANA’s in-memory footprint.

3. Business Intelligence with Microsoft Power BI

To unlock actionable insights, Microsoft Power BI was integrated with the archived SQL data models. Business users gained access to interactive dashboards, real-time reporting, and trend analytics that supported data-driven decisions. Through role-based access control (RBAC), sensitive business data was securely shared with authorized users only, maintaining compliance and governance.

The combined use of ADF, SQL Server, and Power BI delivered a highly automated, scalable, and insight-driven architecture, ensuring performance optimization, cost reduction, and enhanced reporting capability across the organization.

Architecture Diagram

Results

The SAP Data Archival and Reporting Solution delivered tangible performance and efficiency gains. Offloading historical data from SAP HANA to SQL Server improved query response times and overall system performance, allowing SAP to focus on current operational workloads. Storage costs were significantly reduced by transitioning to a more scalable SQL Server environment, enabled by Azure Data Factory’s automated, cost-efficient data transfer.

The integration of SQL Server Data Models with Microsoft Power BI enabled rapid access to historical insights, interactive reporting, and faster decision-making across business teams. Automated archival workflows minimized manual effort, improved data integrity, and ensured consistent compliance with data governance policies. The unified architecture across SAP HANA, Azure, SQL Server, and Power BI established a high-performance, scalable foundation for ongoing analytics and reporting.

This project is part of a broader data migration and modernization initiative designed to ensure system integrity, reporting accuracy, and seamless ERP performance. Explore related case studies below.

In Our Customers’ Words

Excellent to work with in every way. Proactively identified solutions to the problem in the initial design and the recommended solutions. Work has top-notch. Results delivered on time. Communication was excellent.

David Mann

United States

They took us from square one, building a smart data strategy – everything from collecting data to dishing out real-time insights. With their help, we’ve seen some major improvements. We would give them a thumbs-up for anything data-related.

Eric A.

Real-estate Company

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

Working with Kenexai was a game-changer for us. Thanks to Nitesh from Kenexai, our data strategy is on point and giving our business a major boost!

Jason Wood

Auto Finance Company

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

They truly understand what they do. Their restaurant analytics provide real-time insights into our operations and customer behaviors, and it has made a significant difference in our business.

Patrick

Restaurant Business

Working with Kenexai has been fantastic! Thanks to their AI and ML-powered solution, we’ve made great progress. Their expertise helped us spot and prevent fraud in rentals and make us trustworthy.

Remi Martens

Hospitality business

Kenexai has made a real difference for our insurance firm. Their know-how in fraud detection is top-notch. Their data strategies have been a big help, and we are seeing great results. We are quite pleased with what they’ve done for us

Sharon White

Insurance Firm

Insights That Moves,
Impact that Matters.

Turning insights into meaningful impact with tailored solutions, every step of the way.

SAP Data Archival and Reporting for a Prominent Construction Firm

SAP Data Archival and Reporting for a Prominent Construction Firm

About Client

Business Objectives

Solution

1. Data Extraction with Azure Data Factory (ADF)

2. Data Archival in SQL Server (ArchivedDB)

3. Business Intelligence with Microsoft Power BI

Architecture Diagram

Results