FinTech Data Analytics: Architecture, Metrics and Governed Reporting
The metrics FinTechs should track, an analytics architecture with CDC, lakehouse and semantic model, ledger reconciliation, governance and security, and a roadmap.
Hetal KENGINEERING BLOG
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34 articles in Data Engineering & Fabric
Hetal K
Big Data in Logistics: Shipment Visibility, Forecasting and Data Architecture
How logistics companies use big data for shipment visibility, ETA prediction and forecasting, the data sources involved, a streaming and lakehouse architecture and…
Harshil Shah
Data Warehouse vs Data Lake vs Lakehouse: Cost and Decision Guide
How data warehouses, data lakes and lakehouses differ, what really drives their cost, a decision matrix by workload, and a typical lakehouse architecture.
Jainam Shah
Data Governance Automation: Stewardship Workflows, Policy Enforcement and Exceptions
What data governance tasks can be automated, a reference architecture, stewardship workflows for access, quality and sensitive data, handling exceptions and a roadmap.
Manisha Sheladiya
Data Warehouse to Data Lake Migration: A Step-by-Step Plan
A step-by-step plan for data warehouse to data lake migration: why move, a governed lakehouse target, seven migration steps, testing and reconciliation, and…
Hetal K
Snowflake to Databricks Migration: Architecture, Cost and Cutover Plan
How to migrate from Snowflake to Databricks: concept mapping, six migration steps, cost considerations, risks and a reconciled, wave-based cutover.
Vedant Virani
Healthcare Data Governance: Privacy, Lineage and Quality Controls for Clinical Data
A practical healthcare data governance framework: why health data is different, framework components, roles, clinical data quality, secondary use for research and AI,…
Harshil Shah
Data Strategy Consulting: What a Modern Data Strategy Engagement Delivers
What data strategy consulting includes: signs you need it, the five phases of an engagement, deliverables, maturity assessment, AI readiness and how to…
Manisha Sheladiya
AI-Ready Data: A Practical Playbook for Preparing Enterprise Data for AI
What makes data AI-ready, a six-step playbook to prepare it, a layered reference architecture and a checklist to test your own data before…
Jainam Shah
Data Pipeline Observability: Freshness, Volume, Schema Drift and Lineage
Monitor usable data rather than task status alone. Covers freshness, volume, schema drift and lineage with an SLO template, dashboard specification and incident…
Harshil Shah
SQL Server to Azure SQL Migration: Compatibility, Downtime and Cost Checklist
Plan SQL Server migration to Azure SQL with a target decision, compatibility inventory, cutover gates, validation checks and cost worksheet. Covers jobs, SSIS…
Jainam Shah
Streaming ETL vs Batch ETL: Architecture, Latency and Cost Trade-Offs
Compare streaming, micro-batch and batch ETL with freshness budgets, delivery semantics, failure tests and a decision flow. Includes a workload matrix and practical…
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