Client Case Study · Data Engineering
From legacy data chaos to daily insight.
Kalpita Technologies migrated business-critical data to a secure cloud environment and built an Enterprise Data Warehouse with automated ETL and interactive Power BI, Tableau, and Looker dashboards.
Daily
dashboards, not eventually
1
cloud data warehouse
3
BI tools — Power BI, Tableau, Looker
ETL
automated pipelines
Overview
Five things that changed for the business
The data moved to the cloud.
Business-critical data migrated to a secure, scalable cloud environment.
One warehouse, every source.
Enterprise Data Warehouse (EDW) built to unify multiple data sources.
Dashboards refresh daily.
Daily reporting and interactive dashboards via Power BI, Tableau, and Looker.
Cleaner data going in.
Data quality rose through cleansing, injection, and transformation pipelines.
Built for what comes next.
Future-proof decision-making enabled with predictive analytics and trend evaluation.
Summary
The reports were always late. Now they arrive every morning.
The client’s legacy analytical system was losing the race against its own data: growing volumes, slow processing, and reports that nobody fully trusted. Kalpita modernized the entire ecosystem — cloud migration, a centralized EDW, automated ETL pipelines, and business-ready dashboards — so stakeholders now work from accurate, daily, interactive insight.
Client profile
At a glance
A leading enterprise seeking to modernize its data management and analytics ecosystem for faster reporting, predictive insight, and informed decisions.
- Industry
- Finance
- Challenge focus
- Legacy analytics, cloud migration and daily reporting
- Engagement
- Cloud migration plus enterprise data warehouse build
Tools & technologies
The stack behind the warehouse
- SSIS
- SSAS
- Power BI
- Tableau
- Looker
- cloud data platform (with Salesforce, Oracle, and SQL source integrations)
The challenge
The problem we solved
A complex legacy system buckled under growing data volumes — delaying reports and leaving business users without the interactive dashboards they needed to decide.
Strained
existing system was complex, inefficient, and strained by growing data volumes.
Delayed
delays in processing big data and producing accurate reports.
No scale
legacy analytics lacked scalability and cloud compatibility.
No self-serve
business users needed interactive dashboards for faster decisions.
The result was a business making decisions on numbers that were already out of date by the time anyone saw them.
The solution
A cloud warehouse feeding dashboards that refresh every day.
A cloud warehouse feeding dashboards that refresh every day.
Centralized EDW for analytics
Centralized EDW for analytics.
Automated ETL pipelines using SQL Server Integration Service
Automated ETL pipelines using SQL Server Integration Services (SSIS).
Advanced data models with SQL Server Analysis Services (SSAS
Advanced data models with SQL Server Analysis Services (SSAS).
Real-time access to secure, structured, enriched data
Real-time access to secure, structured, enriched data.
Visual, easy-to-use reports for faster insight
Visual, easy-to-use reports for faster insight.
Results
What changed, measured
The warehouse changed the tempo of the business: reporting moved from a monthly scramble to a daily habit.
Reporting
Daily
faster reporting through automated daily dashboards
Accuracy
Improved
improved accuracy in data insight and trend evaluation
Architecture
Future-ready
future-ready architecture that absorbs growing data volumes
Decisions
Data-led
better decisions powered by daily, interactive reporting
Access
Centralized & secure
operational efficiency from centralized, secure data access
Conclusion
Your reports should be daily, not eventually.
The client’s data ecosystem became an asset instead of an obstacle: scalable, secure, and insight-driven. Next on the roadmap: AI-driven predictive analytics, self-service BI for non-technical users, and cloud data lakes for unstructured data.
FAQ
Frequently asked questions
Let’s talk
Your reports should be daily, not eventually.
Bring us the report everyone waits on. We will show you the pipeline that makes it arrive by itself.