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Databricks partner
Databricks consulting by BCMtec: we bring your data and AI into production
As a Databricks partner, we support mid-sized and large companies across all industries with architecture, migration, governance and AI applications on the Databricks Data Intelligence Platform. Consulting and implementation from a single source, from the initial analysis to stable operation.
Your entry point
Where do you stand?
Starting point
Lots of data. Little impact.
In many companies, data sits in separate systems. Analyses, reports and AI are created in different places. This costs time and slows down decisions.
Data silos
ERP, Produktion, Vertrieb und Service speichern ihre Daten getrennt. Eine gemeinsame Sicht auf das Unternehmen fehlt.
AI projects don't get beyond the pilot stage
Models work in testing, but production lacks stable data pipelines and clear processes.
Governance and costs
Access rights, data quality and cloud costs are hard to control when every department uses its own tools.
Databricks is in place, but the value isn't there yet
The platform is running, but costs are rising, business units barely use it and use cases stay stuck in notebooks.
Starting point
Why Databricks
and when to use.
The Databricks Data Intelligence Platform unifies data engineering, analytics and machine learning on a shared foundation. The lakehouse architecture combines the flexibility of a data lake with the performance and governance of a data warehouse.
Databricks runs on AWS, Azure and Google Cloud. Open data formats and a free choice of cloud reduce dependency on a single vendor, keeping your platform future-proof and extensible.
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Open data foundation with Delta Lake
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Unified governance with Unity Catalog
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Data pipelines with Lakeflow
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Analytics with Databricks SQL and AI/BI
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AI and machine learning with Mosaic AI and MLflow
Services
Our Databricks services: from architecture to operations.
Whether it's a new implementation or an existing environment, our in-house Databricks experts support your project from strategy to operations. You book exactly the services you need.
Strategy and architecture
We analyse your data landscape and, building on this, design a lakehouse architecture that matches your goals.
Migration to Databricks
We migrate data warehouses, data lakes and ETL pipelines to Databricks, step by step and without disrupting day-to-day business.
Data engineering
With Lakeflow, we build stable data pipelines for batch and streaming data, so your data is reliably available.
Governance with Unity Catalog
We introduce Unity Catalog or migrate existing workspaces from the Hive Metastore. This lets you manage access rights, data lineage and quality centrally for data and AI models.
Bringing AI into production
We develop ML models and bring them into production with MLflow and Mosaic AI, including monitoring, versioning and retraining (MLOps).
Analytics and BI
With Databricks SQL and AI/BI, we create dashboards and reports that your business units can use themselves.
Databricks costs under control (FinOps)
We configure scaling, policies and budgets to suit your needs, make costs visible per team and use case, and continuously optimise workloads.
Training
We train your teams to work with Databricks, so they can use the platform confidently and independently in their daily work.
Databricks health check: where does your environment stand?
You already use Databricks, but costs, usage or results don't meet your expectations? We analyse your existing implementation and show specifically what can be improved. You receive a prioritised list of measures and implement them yourself or with us.
What we look at
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Architecture and data model
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Costs and utilisation of compute resources
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Governance, access rights and Unity Catalog
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Stability and maintainability of data pipelines
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The path of AI models into production
Approach
From needs assessment to a running platform.
Every project starts with a needs assessment. Then you decide how far we support you. Each step can also be booked individually.
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Needs assessment
We get to know your data landscape and your goals and identify the use cases with the greatest value.
02
Assessment
We evaluate systems, data quality and requirements. The result is a target architecture with a clear roadmap.
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Proof of concept
We implement a selected use case on Databricks, so you can see early on what the platform can do for you.
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Implementation
We build your complete Databricks platform and connect your systems. We then hand over to your team or continue to manage operations.
Why BCMtec
Databricks expertise combined with AI experience
We come from AI, not from reporting
As a spin-off of the University of Augsburg, we bring more than 13 years of experience in AI and machine learning. This expertise flows into every data project.
More than ERP and CRM data
Wir verarbeiten auch Maschinen-, Sensor- und Prozessdaten. Das zahlt sich überall dort aus, wo Daten nicht nur aus Standardsystemen kommen.
Consulting and implementation from a single source
Dedicated contacts support your project from analysis to operations, instead of changing consulting teams. We don't just advise, we also implement.
Databricks partner
BCMtec is a partner in the Databricks Brickbuilder Partner Network. Industry-independent and technology-agnostic: we recommend Databricks where it is the right fit for you.
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Get more out of your data
Your platform is the foundation. We make it usable.
Alongside Databricks consulting, we develop our own AI solutions. On request, we connect them to your platform so your data delivers tangible impact in everyday work.
Alongside Databricks consulting, we develop our own AI solutions. On request, we connect them to your platform so your data delivers tangible impact in everyday work.
FAQ
Frequently asked questions
For mid-sized and large companies that want to bring together data from multiple sources and use it for analytics or AI. We work across all industries.
With the Databricks health check, we analyse your existing environment, including architecture, costs, governance and data pipelines. You receive prioritised measures and implement them yourself or with us.
That depends on your goals, your existing IT and your use cases. Our advice is technology-agnostic, and we only recommend Databricks where it is the right fit for you.
We clarify this in the needs assessment and the assessment phase. We evaluate your existing environment and show whether a migration, an extension or a step-by-step transition makes sense.
Databricks runs on AWS, Azure and Google Cloud. We set up the platform in the cloud of your choice.
You choose the cloud region of your Databricks workspace, for example in Europe. According to Databricks, customer data is generally processed in the same geographic region as your workspace, with documented exceptions for individual services. We set up the environment to meet your data protection requirements.
Databricks charges on a usage basis in Databricks Units (DBUs). Depending on the deployment model, your cloud provider's compute and storage costs are added. Your actual costs depend on your workloads.
For compute capacity to follow actual demand and for costs to remain attributable, compute resources, scaling, policies and budgets must be configured correctly. That is exactly what we take care of. On request, we then monitor and optimise costs on an ongoing basis.
Databricks recommends migrating tables from the legacy Hive Metastore to Unity Catalog. Unity Catalog manages access rights, data lineage and governance centrally. Together, we assess whether and how the migration makes sense for you.
That depends on the complexity, the number of connected systems and your objectives. You will receive a realistic estimate after the needs assessment.
No. Each step can be booked individually. The usual starting point is a needs assessment, or the health check for existing environments.
Yes. We train your employees to work with Databricks, so you can continue developing the platform independently later on.
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