Ditch fragile scripts and slow queries — establish a governed, optimized data foundation that runs on Azure.
Data silos block business views — Finance, CRM, and logistics data sit in disconnected databases — preventing unified analytics.
Inconsistent definitions — Different departments calculate core numbers (like revenue or margins) differently — causing alignment issues.
Slow operational reporting — ETL pipelines take hours to refresh, causing dashboards to stall and fail during critical business hours.
Duplicate & messy customer files — No single source of truth; duplicate records across CRM and billing prevent clean database operations.
Manual file handling routines — Staff spend hours manually exporting CSV files, cleaning records, and emailing them to stakeholders.
Fragile data integration scripts — Custom upload scripts fail silently when source schemas change, causing downstream report outages.
Poor SQL warehouse performance — Analytical queries freeze or take minutes to return values due to poor table indexing.
Loose data security policies — Lack of column-level encryption or row-level security exposes sensitive billing data.
Spiralling cloud database costs — Unoptimized SQL databases or compute clusters remain active constantly, inflating monthly cloud bills.
No database schema versioning — Deploying pipeline updates breaks production reports because database schemas are not tracked.
Tell us a little about your situation — we'll suggest the right Microsoft solution for you.
Scalable data lakes and automated integration pipelines deployed on Microsoft Azure.
Urban mobility is at the core of smart city planning. For companies, the need to understand trip behavior, station utilization, and rider demographics is crucial. However, the absence of an automated, scalable analytics solution hindered their ability to make timely, data-driven decisions. INKEY IT Solutions delivered a full-stack data engineering solution on Microsoft Fabric, transforming unstructured bike-sharing data into rich, actionable insights via a layered Medallion Architecture and Power BI dashboards. The implementation simplifies planning, optimizes operations, and empowers stakeholders across operations, planning, and marketing.
Migrate data from a CRM (Sandbox) to another CRM environment (Production) while preserving data integrity, entity relationships, and system metadata using SQL Server Integration Services (SSIS) and KingswaySoft SSIS Integration Toolkit for Microsoft Dynamics 365.
Organizations face challenges in managing vast amounts of data daily, requiring efficient handling to ensure accuracy and consistency. Manual processes are error-prone, highlighting the need for automated systems to analyze, detect duplicates, maintain consistency, and validate data. Before distribution to managers, data must be validated to ensure accuracy. Implementing such a system can save time and resources by streamlining processes and providing reliable reports to managers.
We build production-grade, optimized data engines that ensure clean datasets are delivered on time.
Our Data Engineering practice designs and deploys data platforms. We specialize in Azure Data Factory, Azure Synapse, Azure Databricks, and SQL DB optimization — building scalable systems that power Power BI and custom applications.
From designing raw file ingestion pipelines to configuring partitioned databases, we scale data infrastructure.
We cover the entire lifecycle, from architecture design and pipeline development to performance tuning.
Building scheduled pipelines to extract, load, and transform data from diverse databases and APIs.
Designing storage tiers (bronze, silver, gold) in OneLake or Azure ADLS Gen2 using Delta Lake.
Building enterprise data warehouses with optimized distribution keys and partitioned schemas.
Analyzing slow database execution queries, redesigning indexes, and optimizing transaction tables.
Designing matching rules and merge routines to clean customer and product records.
Lifting legacy on-prem databases onto modern Azure SQL Managed Instances or serverless options.