The Client
The client is a national financial services company and part of a large Indian conglomerate. The group operates in consumer goods, appliances, agriculture, and real estate.
The financial services arm focuses on home loans. Its mission is to help citizens achieve home ownership and raise living standards across India.
The Need
The company needed accurate data to guide business decisions. Their legacy setup created problems.
- They used an OLTP system to capture and process transactions.
- PostgreSQL handled analytics workloads, but data was spread across multiple tables.
- Reports required heavy manual effort.
- No data warehouse existed, making analysis slow and complex.
Without a unified platform, the company could not get timely insights. They needed:
- A single data source
- Automated reporting
- Better data engineering
- Easier extraction of business insights
The Solution
Teleglobal designed a data analytics platform using AWS services and Snowflake. The architecture streamlined extraction, storage, and reporting.
Step 1: Data Extraction
Business data was captured in real time by the OLTP system. Teleglobal used AWS DMS and AWS Glue to extract and clean the data.
Step 2: Storage in AWS S3
The raw and cleansed data was stored in Amazon S3. This setup created a secure, scalable storage layer. Future machine learning use cases could also pull from this layer.
Step 3: Snowflake Integration
Cleaned data was moved into Snowflake’s published layer. Snowflake enabled advanced data modelling, faster queries, and integration with reporting tools.
Step 4: Data Modelling and Reporting
- Tables were created in Snowflake for analytics.
- ETL pipelines automated data transformation and loading.
- Reporting tools such as Tableau connected to Snowflake for visualization.
- Automated business reports included:
- Financial KPIs: delinquency rate, profit before tax, insurance penetration
- Loan and Collections: total loans, ROI, EMIs, outstanding amounts
- Sales reporting
Benefits
The new solution provided clear business advantages:
- Single source of truth: combined structured, semi-structured, and unstructured data.
- Improved accuracy: higher confidence in reports and insights.
- Secure platform: access controlled with AWS IAM, Secrets Manager, and authentication policies.
- Faster reporting: automated ETL reduced manual effort.
- Custom pipelines: flexible setup to handle new data sources.
- Gap analysis: easier to track performance against goals.
- Personalized offerings: better 360° view of customers.
Outcomes
- >70% accuracy in business insights
- ~60% reduction in operating costs
- 360° customer view, enabling targeted services
- Faster reporting cycles with reduced manual effort
Tech Stack
- Storage & Data: AWS S3, Snowflake, AWS RDS
- Data Processing: AWS Glue, AWS DMS
- Security: AWS IAM, AWS Secrets Manager, AWS KMS
- Monitoring: AWS CloudWatch
- Communication: AWS SES
- Analytics & Reporting: Tableau
Business Impact
The financial services company transformed its analytics with Teleglobal’s solution. Reports that once took hours were now automated. Customer insights became faster and more reliable.
Operating costs fell sharply while data accuracy improved. Decision-makers could now act with confidence, backed by real-time insights.
Conclusion
Teleglobal delivered a stable, scalable data analytics platform with AWS and Snowflake. The solution streamlined data extraction, improved reporting, and cut costs.
With this setup, the client now makes faster, more accurate decisions and offers better services to customers across India.