Blackstraw’s Databricks COE

At Blackstraw, we provide a complete range of data, analytics and AI services designed to fuel innovation and foster growth. With a team of over 300 skilled data scientists and data engineers, alongside 100+ successful implementations, we bring you the best of data warehousing and data lakes, creating unified AI and Data solutions.
Partnering with Databricks, our mission is to break down data silos and inject data-driven insights into your business processes. We offer open, straightforward, and multi-cloud solutions that pave the way for a more data-savy future. As a trusted Databricks partner, Blackstraw specializes in AI/ML solutions, Databricks Platform Implementation, Data Optimization, and Data Migration.


Databricks Implementations


Databricks Certifications 


Solutions Built on Databricks



What we offer


Data Lakehouse Consulting Services

In an era where data fuels business growth, effective data management is not just a necessity; it’s a strategic imperative. Blackstraw’s Data Lakehouse Consulting Services stands as your trusted partner in navigating the complexities of modern data landscapes, ensuring that your data becomes a valuable asset rather than an overwhelming challenge.

Our Data Lakehouse Consulting Services are designed to empower your organization at every step of the data journey:

  • Assessment: We meticulously evaluate your data landscape, identifying specific needs and challenges.
  • Design: Our experts craft a tailored Data Lakehouse Architecture, ensuring precise alignment with your requirements.
  • Implementation & Migration: We seamlessly transition your data to the new platform, maximizing efficiency.
  • Tool Optimization: Leveraging top-notch tech, we fine-tune your ecosystem for streamlined data management and enhanced analytics.
  • Support: Beyond implementation, we offer continuous support, ensuring your Data Lakehouse evolves with your organization.

Data Lakehouse Implementation Services

Data lakehouses stand at the forefront of data management, seamlessly amalgamating the strengths of data lakes and warehouses. They serve as the quintessential hub for storing and analyzing diverse data types, irrespective of their structure. 

Our Data Lakehouse Implementation Services pave the way for unlocking the full potential of this innovative platform, tailored to your unique needs: 

  • Architecture: Our team meticulously crafts a bespoke data lakehouse architecture, precisely catering to your distinctive needs and objectives. 
  • Implementation: We take charge of implementing your tailored architecture and orchestrating the smooth transition of your data to the new platform. 
  • Tool & Tech Configuration: Leveraging cutting-edge tools, we configure your ecosystem for optimized data management and robust analytics.
  • Support: We provide continuous support, ensuring your data lakehouse evolves in sync with your organizational demands.
Data Governance with Unity Catalog

Data Governance with Unity Catalog

In the Databricks Lakehouse ecosystem, Unity Catalog emerges as a comprehensive governance platform explicitly designed for data and AI. It serves as the centralized hub for managing your invaluable data assets, encompassing tables, views, schemas, and databases. 

Blackstraw facilitates organizations in migrating to Unity Catalog-backed Databricks Workspace from standard workspace. It streamlines data governance and security management using ANSI SQL and enables users to:

  • Regulate data access across various data assets, including tables, files, etc.
  • Create a comprehensive data catalog encompassing all data assets within the Lakehouse.
  • Provide a lineage view illustrating the origin and usage of data across jobs and notebooks running in Databricks.
  • Enable secure and governed data sharing through a controlled and managed approach.

Data Engineering Services

Databricks, a unified data analytics platform, offers a versatile environment catering to data engineering, science, and machine learning. Our Data Engineering Services within Databricks are tailored to empower you in designing, implementing, and managing data pipelines and processing jobs within the Databricks Lakehouse ecosystem. 

Get the most of your data with Blackstraw’s Data Engineering Services: 

  • Expertise: Our skilled data engineers have the expertise and experience in crafting and managing intricate data pipelines, ensuring seamless operations. 
  • Efficiency: By leveraging our Data engineering services, you can sidestep costly errors and delays, ensuring efficient pipeline construction and management. 
  • Scalability: Our services aid in architecting scalable pipelines, and adapting to your evolving business needs seamlessly.
  • Security: Our services assist in implementing robust security protocols, ensuring data integrity and confidentiality.

Data Migration Services

Data Migration is a critical step for businesses striving to modernize their data infrastructure. Blackstraw’s Databricks Data Migration Services streamline the migration of your data to the innovative Databricks Lakehouse. 

Our Databricks Data Migration Services will streamline and secure your data migration process. We provide: 

  • Expert Guidance: Our Databricks data migration experts bring forth unparalleled experience and expertise, ensuring a swift and secure transition to the Databricks Lakehouse. 
  • Scale without Limits: Our services are tailored to accommodate the migration of extensive data volumes to the Databricks Lakehouse seamlessly.
  • Security: Our Data Migration services prioritize industry-standard security protocols, safeguarding your data throughout the migration process.

MLOps on Databricks

MLOps stands as a strategic amalgamation of practices aimed at automating and streamlining the entire lifecycle of machine learning. Combining the principles of DevOps, DataOps, and Machine Learning Engineering, MLOps empowers teams to proficiently build, deploy, and manage machine learning models in production environments. 

Databricks serve as the ultimate hub for storing, preparing, constructing, and deploying machine learning models. Our MLOps services within Databricks enable you to: 

  • Automate End-to-End Processes: Effortlessly automate the machine learning pipeline – from data preparation to model deployment  – with precision and ease. 
  • Effective Model Management: Seamlessly manage and track your machine learning models, ensuring efficiency throughout their lifecycle. 
  • Swift & Secure Deployments: Expedite machine learning model deployments to production environments swiftly and securely.
  • Continuous Performance Monitoring: Monitor and enhance the performance of deployed models in real-time, ensuring sustained efficiency.
Case Study

Building an MLOps platform on Microsoft Azure and Databricks for a large US-based Utility company

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Empowering businesses through AI solutions

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Why Databricks?

Data and AI Company

With origins in academia and the open source community, Databricks was founded in 2013 by the original creators of Apache Spark™, Delta Lake and MLflow. As the world’s first and only lakehouse platform in the cloud, Databricks combines the best of data warehouses and data lakes to offer an open and unified platform for data and AI


One platform for integration, storage, processing, governance, sharing, analytics and AI. One approach to how you work with structured and unstructured data. One end-to-end view of data lineage and provenance. One toolset for Python and SQL, notebooks and IDEs, batch and streaming, and all major cloud providers.


Automatic optimization for performance and storage ensures the lowest TCO of any data platform together with world-record-setting performance for both data warehousing and AI use cases — including generative techniques like large language models (LLMs).Whether you’re a startup or global enterprise, Databricks is built to meet the demands of your business at any scale.


Databricks platform ensures an end-to-end protection of your data. Founded on strong security practices, Databricks offers a unified architecture for seamless data integration, storage, processing, and governance. With transparent data governance, it provides a clear view of data lineage and provenance, enhancing accountability. 

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