Unleash the power of analytics through
modern data engineering
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
We study the different data sources – right from files and data bases to logs and images. At this stage, the objective is to ensure we don’t lose out on any critical information. We collect, aggregate and move all types of data to one central location.
Data transformation & processing
We need to ensure that integrity of the data is maintained while achieving consistency. Data from different sources is transformed and aggregated in a way that it maintains a central data architecture.
Data storage
All the data is now moved into data lakes and data warehouses using on premise or cloud or hybrid architecture.
Data Governance
Effective Standards and Policies to monitor and control usage of data.
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
Data ingestion
storage
processing
ETL
Insights
Shaping an Effective Data Strategy: BI Tools Comparative Insights – Whitepaper
By John David
/ November 14, 2025
Shaping an Effective Data Strategy: BI Tools Comparative Insights Download our exclusive report comparing Power BI, Tableau, Qlik, IBM Cognos,...
Read More
Legacy System Modernization: Best Practices and Use Cases
By John David
/ November 11, 2025
Organizations across the world are being recognized for their speed and adaptability. Legacy systems that once worked fine are now...
Read More
How Copilot for Power BI Is Rewiring Enterprise Analytics
By John David
/ November 6, 2025
The success of an organization isn’t measured only by efficiency, minimal costs, and risk; it is also determined by its ability to unlock new...
Read More
Tableau to Power BI Migration – Your Comprehensive Guide in 2025
By John David
/ November 5, 2025
Introduction: The BI Crossroads Business Intelligence platforms have become the backbone of modern decision making across enterprises. Among the most...
Read More
Data Analytics in the Energy Sector: Unlock Real-Time Insights with Power BI
By John David
/ November 3, 2025
The traditional energy sector is undergoing a transformation led by data analytics, allowing energy companies to convert historical data into...
Read More
Database Tuning and Infrastructure Optimization for GenAI Workloads
By John David
/ October 31, 2025
Client Overview The client, an American manufacturer and leader in custom packaging, integrated GenAI into their existing infrastructure to enhance...
Read More
How Power BI Revolutionizes Manufacturing Operations
By John David
/ October 27, 2025
The manufacturing industry is large and produces a massive amount of data daily, from production lines and supply chains to...
Read More
Why Retail & CPG Companies Are Moving to Power BI for Smarter Forecasting
By John David
/ October 23, 2025
We are in an era where predicting demand is as tough as meeting it. One viral trend can flip sales...
Read More