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
Data Poisoning in AI: The Hidden Threat Sabotaging Enterprise Models
By Taruni Sharma
/ June 5, 2026
Data poisoning has quickly become one of the most discussed risks in AI. As organizations increasingly rely on AI for critical...
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From Cloud Chaos to AI Readiness
By Sparity Inc
/ June 3, 2026
From Cloud Chaos to AI Readiness Download our practical guide for building a successful Azure modernization roadmap. Learn how to...
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Decoding the Unified Semantic Layer: The Missing Link in Your Modern Data Stack
By Harish Cholleti
/ May 19, 2026
A unified semantic layer is a centralized translation layer that sits between your raw data and every tool that consumes...
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Shadow AI: The Silent Threat Hiding Inside Your Organization
By Sumanth Itha
/ May 14, 2026
Your employees are already using AI tools you've never approved. Here's what that means and what to do about it. Shadow AI is the unauthorized...
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Alteryx to Microsoft Fabric: Why Enterprises Are Making the Switch in 2026
By Sunil Batchu
/ May 7, 2026
Alteryx to Microsoft Fabric: Alteryx is a capable data preparation tool, but in 2026 its per-user licensing costs, in-memory processing...
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The Real Cost of AI: Why Companies Are Overspending Without Seeing ROI (And How to Fix It)
By Srikanth Konda
/ April 27, 2026
The Hidden Problem: AI Subscription Sprawl AI ROI According to Gartner, spending on AI infrastructure will add $401 billion in spending in 2026 as...
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How a Leading Telecom Enterprise Automated 1,800 Alteryx Workflows to Microsoft Fabric
By John David
/ April 16, 2026
Alteryx Workflows to Microsoft Fabric: telecom enterprise had developed a large analytics environment over time, with nearly 1,800 Alteryx workflows used across...
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Power BI vs Tableau | Key features and Comparison 2026
By Sunil Batchu
/ April 6, 2026
Power BI vs Tableau: Selecting the best data visualization or business intelligence tool is a vital task, this blog offers...
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Fabric 2026 Highlights: Key Takeaways from Microsoft Fabric Conference
By Taruni Sharma
/ March 27, 2026
The Microsoft Fabric 2026 Community Conference 2026 conducted in Atlanta, Georgia, brought together data leaders, BI professionals, engineers, and AI practitioners. ...
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