Databricks

Databricks is the Data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics, and AI. Databricks is headquartered in San Francisco, with offices around the globe, and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake, and MLflow.

Our partnership

b.telligent is a long-standing Databricks partner and supports its clients, starting with design of a target architecture right up to its actual implementation. Our projects are as diverse as the possibilities of the platform itself – machine learning, stream processing, central lake, classic data warehouse, IoT etc. Here b.telligent also benefits from its partnerships with the three major cloud providers (AWS, Azure, GCP) and can cover the entire spectrum ranging from cloud setup to actual data processing.

Depending on our client's initial situation, we offer standard architectures and procedures, or develop an individual solution tailored to the respective requirements. Our standardized quick check is a good starting point for this, in order to register the initial situation and use it as a basis for presenting a target concept including architecture. Alternatively, we conduct architecture workshops on specific issues.

The partnership also encompasses training of further experts and professional exchanges between Databricks and b.telligent. In this way, we regularly obtain an overview of new functionalities and an insight into innovations planned for the future.

"Databricks inspires - with its vision of the lakehouse and also with new groundbreaking features and innovations. With Databricks, you have the right technology to build a lakehouse of the future, and we provide the experts to make this happen.“

Julia Ouyang, Senior Consultant Data Integration and Architecture

Products & services

Lakehouse & Delta Lake
Based on the open-delta format, the data warehouse can be set up in the cloud directly on the data lake. This eliminates data silos, inconsistencies between DWH and data lake, as well as exploding costs and extra effort to load data into closed systems. Data Lake + Data Warehouse = Lakehouse. With Spark as the underlying engine, open-source technology is used to enable high-performance and cost-effective data processing.

DWH & data engineering
In a cloud DWH, orchestration of jobs and loading processes plays a decisive role in addition to the actual databases. Databricks offers workflows enabling dynamic control of all processes within the platform. A delta live tables framework is available for simple declaration of data pipelines, while auto-scaling job clusters ensure that workloads can run cost-effectively.

Data governance
At least as important as data availability is the enterprise's organizational framework which regulates the handling of data – data governance. The platform's integrated tool, Unity Catalog, enables unified control of access by users throughout the lakehouse, providing data lineage for structured and unstructured data across all layers as well as BI and AI assets. This allows traceability which simplifies compliance with legal regulations and finding of data. In addition, Unity Catalog and systematic collection of metadata enable additional functionalities such as audit logging, delta sharing and monitoring of all resources in the lakehouse.

Data science & AI
Efficient use of artificial intelligence (AI) is increasingly playing a major role at enterprises across all sectors – with Databricks and Spark, data scientists can use the language of their choice (Python, R, Scala or SQL) within the platform. An additional range of features available to users with Managed Mlflow simplifies all development stages in the machine-learning lifecycle - including mapping of generative AI and LLM use cases.

Applications

Databricks is versatile. The platform's features and services allows complete solutions for data lakes, lakehouses, data warehousing and machine-learning to be implemented in the cloud. Databricks can also be employed in existent cloud platforms on a modular basis to enable special applications such as real-time processing of data streams. The solution's openness as well as a wide choice of compatible technologies from third-party partner companies ensures maximum flexibility to fulfil individual requirements and framework conditions.

Our Databricks champions

databricks can be combined with these solutions

The solution can be purchased with b.telligent.
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Case Studies

We will be happy to provide you with case studies upon request.

databricks interview about the joint partnership

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The benefits four your organization

We're technology-neutral vis a vis our direct partner network and the technology market as a whole; we're guided solely by what works best for you.

We know each partner in our extensive network individually and will select a solution that reflects your challenges, your infrastructure, and the legal situation in your country.

We offer end-to-end support – from selection, evaluation, purchasing and implementation, through to operational management.