We enable modern data engineering through integration of various data sources, creation of hybrid data lakes and warehouses and fully operationalized data pipelines to support data driven innovations.

At Sparity, we believe that data engineering is the enabler for data science. Data science consists of AL & ML models and experimentations. They can be developed only when we have a solid data infrastructure, which is possible through data engineering processes like collection, storage and transformation.
We can help you build this framework and use the power of data to reduce operational costs, discover new revenue sources and create new products. Our proven processes ensure all data, internal or external move from identification to storage without losing granularity and value.
Our approach
Data ingestion
Data transformation & processing
Data storage
Data Governance
Our Offerings

Consulting
- Data Maturity Assessment
- Data Consolidation Strategy
- EDW Roadmap
- Cloud Adoptions Strategy

Design
- Data Warehouse Architecture
- Data Pipelines (SQL & No-SQL)
- Data Lakes and Analytical Sand Boxes
- Cloud Architecture(AWS, Azure,GCP..)

Implementation
- EDW Implementation and Maintenance
- Cloud Migration
- Maintain Data Pipelines for ML
- Data Model Support/Update
Data Engineering Technologies we work with
cloud

storage

processing

etl

CASE STUDY
Client wants to puts businesses in control by providing them with a Smart Mobile App Builder, enabling them to create their own custom app centralized around their business.
Client is into performance tracking solution and as offerings like group training, personal training for fitness clubs, boutiques and franchisee tailored to their brand and class style features such as data management, member retention, result tracking, booking and communication.