As cloud data volumes grow, so do storage costs. Many organizations continue to store large datasets in expensive systems—such as Cosmos DB, Azure SQL, or managed NoSQL platforms—despite using that data primarily for analytics, not transactional workloads.

Enterprises running on traditional SQL platforms—such as SQL Server, Oracle, Teradata, or Netezza—often find themselves at a crossroads: increasing costs, limited scalability, and a lack of agility for modern analytics and AI. At the same time, moving critical data and logic to a platform like Databricks requires more than just “lift and shift”—it demands careful planning, tooling, and validation.

Power BI is a powerful tool for interactive dashboards and analytics—but as datasets grow and logic becomes complex, report performance and maintainability often suffer. Business logic written in DAX becomes harder to govern, and refreshes slow down under the weight of large semantic models or duplicated transformations.

Building and managing ETL pipelines has long been a complex, code-heavy task. From orchestration logic to data quality enforcement, engineers often reinvent the wheel for each new workflow. This results in brittle pipelines, delayed delivery, and rising operational costs.

Keystone Strategy developed a Data & Analytics maturity index to grade what companies can actually do with their data and their data platform. We took a modern take onto that matrix.

This white paper investigates the relationship between Data & Analytics technologies and business performance based on a large empirical study of major enterprises. To quantify the impact of data on business performance, Keystone Strategy developed a Data & Analytics maturity index to grade what companies can actually do with their data and their data platform.

The Lakehouse Deployment & DevOps Framework brings together best practices from Databricks Asset Bundles (DAB), GitOps, and environment isolation into a unified delivery model.

The GitOps & Dev Workflow Enablement Kit helps clients adopt proven software engineering practices within Databricks.

This accelerator equips clients with the tools and templates needed to adopt Asset Bundles effectively.

The Data Lineage & Cataloging Accelerator helps clients surface and manage metadata in a consistent, governed way.

The Cost Monitoring & Optimization Toolkit provides a structured, automated way to ingest Databricks usage logs, transform them into human-readable cost and usage metrics, and expose these through intuitive dashboards

The CDC Ingestion Toolkit offers a structured approach for ingesting incremental changes—updates, inserts, and deletes—from relational systems into the lakehouse using scalable, merge-ready logic.

The Data Quality Framework brings structure, automation, and accountability to this challenge. Built for Databricks, it integrates directly into ingestion and transformation pipelines, flagging issues early and ensuring only valid trusted data lands in your curated layers.

The Delta Live Tables (DLT) Streaming Framework provides a declarative, governed way to define ETL pipelines that run continuously or incrementally, with built-in monitoring, auto-scaling, and lineage.

The Databricks Auto Loader Ingestion Framework provides a prebuilt, production-grade pipeline that continuously ingests files from cloud storage into the lakehouse.

We are proud to collaborate with Databricks to empower data professionals with cutting-edge tools and training. Together, we drive innovation in data engineering, analytics, and AI.

We partnered with Databricks to host a hands-on Fundamentals Bootcamp, covering Apache Spark, Delta Lake, and Databricks SQL. Participants gained key data engineering and analytics skills to drive innovation.

A short story about Databricks

Startups and innovative enterprises are revolutionizing the way insurance policies are sold.

Startups and innovative enterprises are revolutionizing the way insurance policies are sold.

Startups and innovative enterprises are revolutionizing the way insurance policies are sold.

Startups and innovative enterprises are revolutionizing the way insurance policies are sold.

Startups and innovative enterprises are revolutionizing the way insurance policies are sold.