Dataqrypt

Dataqrypt × Databricks

Practical Execution. Trusted Data.
AI That Actually Works.

Dataqrypt is a Databricks partner focused on hands-on execution and real adoption of the Databricks Lakehouse. We help organizations move beyond platform setup and into reliable, business-ready usage of Databricks where pipelines are stable, data is trusted, and analytics and AI are actually used.

Our approach is shaped by observing how leading Databricks partners operate and by intentionally focusing on the areas where customers continue to struggle even after Databricks is live.

Why Dataqrypt

Through our research and market observation, one theme is consistent:
Databricks implementations rarely fail at the platform level, they fail at execution and adoption.

What we commonly see in customer environments:

  • Databricks is implemented, but pipelines are fragile
  • Data exists, but business teams don’t trust the numbers
  • Analytics work for one team but not others
  • ML and GenAI initiatives stall at POC’s (proof of concepts)
  • Internal teams struggle to own and extend what was built

Dataqrypt was built to address this exact gap.

We focus on making Databricks work reliably in day-to-day business scenarios.

Our Databricks Focus

Databricks Platform Stabilization & optimization

Many Databricks environments technically function but are difficult to scale or trust. We help bring structure and stability to existing implementations.
Our work typically includes:
  • Reviewing and improving ingestion and transformation pipelines
  • Standardizing bronze, silver, and gold data layers
  • Improving performance and cost efficiency
  • Implementing Unity Catalog in a practical, usable way
  • Cleaning up schemas, naming conventions, and data contracts

Outcome:

A Databricks environment teams can rely on without constant firefighting.

Analytics Engineering on the Lakehouse

Databricks delivers value only when analytics align with how the business actually operates. We focus on designing analytics that are usable, consistent, and trusted.
We help with:
  • Analytics ready data modeling
  • Defining consistent metrics and business definitions
  • Reducing dependency on ad-hoc SQL and extracts
  • Enabling BI tools (including Power BI) to consume Databricks data cleanly

Outcome:

Business teams gain self-service access to trusted insights without increasing technical debt.

AI, ML, and GenAI > From Experimentation to Production

Many organizations experiment with AI on Databricks but struggle to operationalize it. We focus on production-ready AI, not demos.
We help with:
  • Reusable feature engineering pipelines
  • Model deployment and retraining workflows
  • RAG based GenAI solutions using governed enterprise data
  • Guardrails around access control, data quality, and hallucination

Outcome:

AI and GenAI solutions that run reliably in production and support real business workflows.

Databricks + Cloud (Azure-First) Alignment

For organizations heavily invested in Microsoft Azure, we ensure Databricks integrates cleanly into the broader cloud ecosystem.
This includes:
  • Integration with Azure Data Lake
  • Secure identity and access patterns using Azure AD
  • Power BI consumption from curated Databricks tables
  • Cost and performance optimization

Outcome:

Databricks becomes a natural extension of the existing cloud architecture, not an isolated platform.

Where Dataqrypt Fits Best

Dataqrypt is a strong fit when:
  • Databricks is already implemented, but adoption is uneven
  • Pipelines exist, but reliability or performance is a concern
  • Data models make sense to engineers, not business users
  • BI teams rely heavily on manual workarounds
  • ML or GenAI initiatives are stuck at POC stage
  • Teams need hands-on support close to the data

In many cases, we work alongside larger partners, focusing on execution quality and adoption after the platform is live.

How We Engage

We keep our engagement model intentionally flexible:
  • Short discovery and assessment phases
  • Targeted execution sprints
  • Ongoing optimization and support

We adapt to where you are, rather than forcing a fixed methodology.

Dataqrypt’s Perspective as a Databricks Partner

Dataqrypt positions itself as a Databricks partner focused on the hardest part of Databricks adoption, execution, trust, and daily usability.

Our approach is informed by studying how leading Databricks partners operate and by intentionally choosing to work in the space where customers continue to face challenges after the platform is live.

Already on Databricks?
Let’s Make It Work Better.

Whether you need stabilization, better analytics adoption, or production ready AI, Dataqrypt can help you move forward with confidence.

Get Quote

Real Adoption Patterns

Retail & CPG:

Demand forecasting and inventory optimization

Promotion and pricing analytics

Customer segmentation built on Databricks

Healthcare:

Centralized analytics across clinical and operational data

Governance-driven reporting

Predictive insights using trusted data models

Enterprise Analytics:

Consolidating fragmented analytics into a unified Lakehouse

Improving performance while reducing cost

Enabling self-service BI on Databricks