Databricks: The Unified Data & AI Platform for Modern Enterprises

From data engineering to BI to AI, Databricks elevates your entire data strategy. 

Databricks brings together the flexibility of data lakes and the performance of data warehouses in a powerful Lakehouse Platform – driving faster innovation, smarter decisions, and measurable business value.

 

Logo Databricks Informatec

Developed by the creators of Apache Spark, Databricks is the leading platform for analytics, data engineering, and AI. Its Lakehouse architecture merges the scalability of data lakes with the governance and performance of data warehouses. This provides organizations with a unified environment to process large data volumes, build machine learning models, and create real-time dashboards. 

Whether building data products, running advanced analytics, or scaling AI, Databricks provides the solid technological foundation you need.

Databricks Vorteile Informatec

YOUR BENEFITS WITH DATABRICKS

  • Faster Insights

    Integrated workflows for analytics, ETL, and ML in a single platform.

     

  • Cost & Resource Efficiency

    Simplified data architecture and auto-scaling reduce infrastructure costs.

  • Open & Interoperable

    Seamless integration with Azure, AWS, Power BI, Tableau, dbt, and more.

  • Governance & Security

    Unified access controls and data lineage ensure compliance and control.

  • Cross-Team Collaboration

    Data scientists, analysts, and engineers work together in shared notebooks and workspaces.

  • Future-Proof AI Readiness

    Ideal foundation for operationalizing generative AI, LLMs, and beyond.

Who benefits from Databricks?

No matter the size of your business, the challenges are the same: How to harness data and AI more efficiently, accelerate innovation, and manage risks with confidence? The Databricks Lakehouse Platform empowers you to do all three – delivering tangible value across the organization, from IT leaders to business users.

  • For CIOs & CDOs – Reduce Cost & Complexity

    • Unified platform for all Data & AI use cases – up to 8x better price/performance.
    • Eliminate redundant tools, storage, and processes.
    • Centralized governance for stronger security, resilience, and customer trust.

  • For Data Scientists & Analysts – Accelerate Innovation

    • Real-time collaboration on a single platform without data silos.
    • Faster path from experimentation to production.
    • Democratized access to Data & AI – even for non-technical users via natural language.

  • For Compliance & Risk Managers – Mitigate Risks

    • Built-in security: access controls, encryption, monitoring, and auditing.
    • Meet regulatory requirements without slowing down innovation.
    • Responsible AI: trustworthy, transparent, and safe AI applications.

Getting Started with the Databricks Lakehouse Platform

DATABRICKS CORE CAPABILITIES

  • Lakehouse Architecture - One Platform for All Data

    Combines structured, semi-structured, and unstructured data in a single platform. By combining the best of data lakes and data warehouses, the Lakehouse makes it easier to run analytics, BI, and AI workloads without moving or duplicating data.

    Databricks Informatec Data Lakehouse Platform

  • Unity Catalog – Unified Data Governance

    It offers centralized governance through a single catalog for data discovery and management across all your data and AI assets. With flexible storage and open formats, it keeps your data portable and avoids vendor lock-in, letting you manage your data your way.

    Databricks Informatec Unity Catalog

  • Delta Lake – The Foundation of the Lakehouse

    Built on open-source technology, Delta Lake ensures data reliability and trust within the Lakehouse. It adds ACID transactions, time travel (data versioning), and schema enforcement to data lakes—so teams can confidently build analytics and AI on top of clean, consistent data.

    Databricks Informatec Delta Lake

  • Unified Data Engineering – Scalable ETL and ELT Workflows

    Powered by Apache Spark and enhanced by Databricks Lakeflow, Databricks simplifies building managing, and orchestrating data pipelines at scale. Engineers can transform and prepare data at scale using Python, SQL, R, Scala, or Java in a collaborative notebook environment, while analysts can query data directly with SQL for insights. Lakeflow ensures streamlined data management, governance, and lifecycle control while Spark provides the performance and scalability needed to handle complex, high-volume pipelines efficiently.

    Databricks Informatec Unified data Engineering

  • Databricks SQL- AI Powered Serverless Warehouse

    Databricks SQL is a serverless data warehouse built on lakehouse architecture that natively integrates AI. It enables you to access data-driven insights easily, whether through AI-powered natural language queries or traditional SQL written in the editor with AI-assisted code generation. With a lakehouse architecture powered by the Photon query engine, it delivers world-class price/performance, helping manage compute and storage costs.

    Databricks Informatec SQL

  • MLflow & AutoML – Streamlined ML Operations

    An open-source framework integrated into Databricks, MLflow lets teams track experiments, manage models, and streamline deployment. AutoML accelerates model development by automatically testing different algorithms and parameters, helping teams quickly identify high-performing models and focus on fine-tuning and innovation.

    Databricks Informatec MLflow & AutoML

Databricks Whitepaper

Why Success with Data & AI Depends on Openness and Portability

For many organizations, existing Data & AI infrastructures are becoming roadblocks rather than enablers of innovation — especially when they lack the scalability and adaptability needed for the future.
The key lies in open and portable platforms: they unlock flexibility, reduce vendor lock-in, and pave the way for long-term success. In this whitepaper, you’ll discover:

  • The competitive advantages of openness and portability
  • The critical factors to consider when moving to a new platform
  • How to secure technological independence for your business
  • Proven strategies to minimize risks during migration
Informatec Whitepaper Databricks

Download Whitepaper (PDF)

Application scenarios for databricks

  • Real-Time Customer Insights

    Unify customer data from transactions, web, and IoT streams to create a 360° customer view. Enable hyper-personalized experiences, targeted marketing, and smarter recommendations.

  • Predictive Maintenance & IoT Analytics

    Ingest and process sensor data at scale to predict equipment failures before they happen. Reduce downtime, extend asset lifetime, and optimize operations in manufacturing, utilities, and logistics.

  • Fraud Detection & Risk Management

    Leverage machine learning on massive transaction datasets to detect anomalies in real time. Improve fraud prevention, credit scoring, and compliance monitoring with explainable AI models.

  • Demand Forecasting & Supply Chain Optimization

    Forecast demand at a granular level using historical, seasonal, and external signals. Optimize inventory, reduce stock-outs, and ensure more resilient supply chains.

  • Healthcare & Life Sciences Innovation

    Analyze clinical trial data, patient records, and genomic datasets in a secure, compliant environment. Accelerate drug discovery, improve patient outcomes, and support evidence-based healthcare decisions.

  • Generative AI & Knowledge Management

    Use enterprise data to power generative AI and LLM applications. Build AI assistants that deliver accurate, contextual answers by combining natural language with governed business data.

Databricks F.A.Q.

What types of data workloads can Databricks handle?

Databricks supports a wide range of workloads, including data engineering, batch and streaming analytics, business intelligence, and AI/ML applications. Its lakehouse architecture allows you to process both structured and unstructured data efficiently.

How does Databricks ensure data security and governance?

Databricks provides centralized governance with a single catalog for data discovery, access control, and auditing. It also integrates with enterprise security standards, ensuring your data is protected and compliant across all environments.

Can Databricks integrate with our existing BI and data tools?

Yes, Databricks works seamlessly with popular BI, ETL, and AI tools, allowing you to leverage your existing ecosystem. Its support for open formats and APIs ensures smooth integration without vendor lock-in.

What are the cost benefits of using Databricks compared to traditional data platforms?

Databricks reduces costs by combining storage and compute efficiently with its lakehouse architecture, eliminating the need for multiple copies of data. AI-driven optimizations and automated performance tuning lower operational overhead, while scalable resources let you pay only for what you use, helping maintain predictable and sustainable budget growth.

How does Databricks compare to Snowflake?

Databricks and Snowflake are both cloud data platforms but serve different needs. Databricks is ideal for unified analytics, AI, and machine learning on both structured and unstructured data through its lakehouse architecture. 

Snowflake, on the other hand, is a cloud-native data warehouse focused on high-performance SQL analytics for structured data, with automatic scaling and easy BI integration.

HOW INFORMATEC HELPS YOU SUCCEED WITH DATABRICKS

Official Databricks Partner

As experienced Data & AI experts, we guide you through every step of your Databricks journey – from planning the right architecture according to your needs and integrating your data, to delivering production-ready AI and analytics solutions. Whether a proof of concept or enterprise-scale deployment, we ensure you maximize your Databricks investment. Our approach helps you accelerate adoption, scale efficiently, and turn data into actionable insights that deliver measurable business results.

Informatec Databricks Partner

Certfied Databricks Data Engineer

Our consultants hold the Databricks Certified Data Engineer Professional Badge – a clear proof of their advanced expertise. This certification demonstrates the ability to design and implement complex data engineering solutions on Databricks: from building optimized and cleaned ETL pipelines, to modeling data within the Lakehouse, and ensuring security, reliability, monitoring, and testing before deployment. It also validates deep knowledge of the Databricks platform and its developer tools, including Apache Spark™, Delta Lake, MLflow, as well as the Databricks CLI and REST API. Organizations can trust our experts to deliver sophisticated, efficient, and future-ready data engineering solutions with Databricks.

Databricks Credentials

Databricks Data Engineer Professional

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