What is Databricks?
Databricks is a cloud-based platform that helps organizations process and analyze massive amounts of data and build AI applications. Databricks invented the lakehouse paradigm and is a pioneer in generative AI.
Databricks' Data Intelligence Platform unifies data, AI and governance so companies can scale their data use across the entire organization and create new data products, including GenAI applications.
Over 10,000 global businesses are already solving their toughest data challenges with Databricks.
How can Recordly help you with Databricks?
We are your go-to experts for each aspect of Databricks
Recordly is a registered partner for Databricks in Finland. We offer certified Databricks experts with various specializations, such as infrastructure, data engineering, and machine learning, with the needed business experience to add value to Databricks' customers. Recordly has been a Databricks partner since 2022.
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Building and delivering value |
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Data and AI |
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Databricks Delta Live Tables |
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Why do businesses choose Databricks?
Databricks has become a leading choice for organizations seeking a unified platform for data engineering, analytics, and machine learning. Its popularity stems from the way it simplifies complex data workflows and accelerates time-to-insight, all while supporting scalability and collaboration across teams.
At its core, Databricks brings together the best of data lakes and data warehouses through its Lakehouse architecture. This hybrid model allows businesses to store large amounts of raw data efficiently while still enabling structured, high-performance querying, without the traditional cost or complexity of managing multiple systems.
Another major factor is collaboration. With native support for notebooks, version control, and role-based access - cross-functional teams, data engineers, scientists, and analysts - can work together in a single environment. This boosts agility and reduces the friction typically found in siloed toolchains.
Businesses also value Databricks’ strong integration with cloud ecosystems, including Azure, AWS, and Google Cloud, making it easy to embed into existing infrastructure. Combined with its support for open-source technologies like Apache Spark, Delta Lake, and MLflow, Databricks offers flexibility without vendor lock-in.
Finally, the platform’s emphasis on automation and governance. Via tools like Unity Catalog and built-in CI/CD capabilities, Databricks helps ensure that data pipelines are fast, secure, traceable, and compliant.
In summary, Databricks enables organizations to go from raw data to business-ready insights faster, more collaboratively, and at scale, making it a strategic investment for data-driven enterprises.
Proven capability to deliver Databricks platforms from scratch
We have hands-on experience in designing, building, and implementing Databricks platforms from scratch to meet a variety of business needs. Our end-to-end delivery includes:
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Databricks environment setup: Provisioning and configuring scalable Databricks workspaces tailored to the organization’s architecture and security requirements.
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CI/CD pipeline creation: Establishing robust continuous integration and deployment pipelines to ensure consistent, automated, and version-controlled development across multiple environments.
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Business solution delivery: Developing and deploying data pipelines, analytics workflows, and machine learning models directly within the Databricks ecosystem to support real business outcomes.
Our Databricks customers
We are continuously evolving our framework and reusable logic to create additional customer value with less work and faster development cycles. We've delivered large enterprise-level Databricks solutions in various industries such as retail, finance & insurance, manufacturing and energy.
Lumo Analytics
Lumo Analytics' previoys way of analyzing mineral samples for new and existing mines was cumbersome, expensive and slow. Lumo Analytics disrupts the field with a new data intensive solution aiming for fast analysis time to delivery and reduced costs. A large part of their value proposition is delivering the results from the device on the field in near-real-time around the globe.
Recordly helped build an IoT and data platform to gather and store sensor data from field and turn it into actionable insights. Our solution scales as data amounts and speed grows by using Databricks and Delta Lake. This is possible by utilizing Azure IoT technologies for connectivity and device management.
UPM Energy
Energy price volatility has increased significantly during the past few years. For industry clients, the electricity prices can be up to 30% of the cost base. UPME wanted to build a platform that optimizes energy consumption and cost at the same time with real-time data processing.
The platform built around Databricks is used to deliver Optimization-as-a-Service to various energy-intensive industries to both internal and external customers in Europe. Use cases involve varying deliveries of energy and resource consumption forecasts, and consumption optimizations.
The move to Databricks enables UPME to improve and enhance existing capabilities relating to platform and continuous optimization operations, and enable the development of entirely new ways of working with ML and MO (Mathematical Optimization). In addition, a well-managed Databricks environment provides a sandbox for analysts.
Databricks for data & AI
We have extensive experience in building Databrocks projects of all sizes.
We have tried and tested different approaches, and have extensive library of best practices, guidelines, scaffolding, and ways of working.
With Databricks, you can build better AI products with the help of a data-centric approach. With Databricks, lineage, quality, control and data privacy are maintained across your entire AI workflows, enabling you to deliver any AI use case.
Databricks from a Recordly standpoint
Blog
Databricks: All in one?
Custom binary format, ingestion, transforming thousands of column datasets, data quality testing, pipeline monitoring, data sharing... Is there anything you cannot do with Databricks?
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