Royal Cyber + Databricks

Accelerate your Data Analytics and AI Initiatives
by Partnering with Royal Cyber and Databricks

Introducing Databricks Strategic Consulting Partner Royal Cyber

Royal Cyber is an experienced Databricks consulting services partner with a team of experts dedicated to implementing a data strategy that optimizes existing data pipelines for speed, scalability, and accuracy while maintaining cost-effectiveness. Royal Cyber’s expertise goes beyond just Databricks by bridging the gap between a company’s existing data infrastructure and Databricks, ensuring a smooth integration. Our services encompass everything- from initial consultation to implementation and ongoing support, thus helping companies unlock the full potential of Databricks for data engineering, analytics, and AI.

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Databricks Services We Offer

Databricks Jumpstart

Databricks Migration

Data Lakehouse

GenAI Applications

Business Intelligence

Data Governance

Mosaic AI

Data Warehousing

What Makes Royal Cyber the
Right Databricks Consulting Services Partner?

Faster Performance & Insights
Lower Costs
Certified Databricks Consultants
0 x
Accelerated Implementation

Our Databricks Consulting Services Custom Packages

Choose the package that best fits your needs. Our Databricks packages are designed to cater to a variety of requirements.
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What Exactly Does Databricks Do?

Databricks is a serverless, cloud agnostic Data Intelligence Platform that simplifies data architecture by breaking down silos between analytics, data science, and ML. The platform empowers users to create data-centric language models for direct insights. It ensures comprehensive connectivity and interoperability by offering seamless integration with Azure Lakes, PowerBI, and Kafka. In essence, Databricks aims to democratize data, automate tasks, and facilitate the development of custom AI applications.

Databricks For Data Science Community

Why Companies Need Databricks

Benefits of Databricks Data Intelligence Platform

Streamlined AI Model Deployment

Databricks offers a comprehensive suite of tools to manage your data throughout the AI workflow, ensuring its lineage, quality, control, and privacy. This empowers you to tackle any AI challenge with features like creating and deploying custom generative models, automated experiment tracking, and scalable model deployment and monitoring.

Simplified Data Governance

Streamline control over your data, analytics, and AI with a unified data governance approach. This single model simplifies compliance and provides a holistic view of all your data, structured or unstructured. Gain deeper business insights through features like context-aware search, AI-powered monitoring, and unified data and AI permissions.

Cost Effective Data Scalability

Databricks Lakehouse delivers 12x better price-to-performance for your SQL and BI needs. It offers simplified management with serverless architecture, AI-powered query execution for faster results, and open formats and APIs to avoid vendor lock-in.

Real-time Data Insights

Databricks handles batch and real-time processing, automatically adapting to maintain data quality. Build workflows quickly for any data type, and enjoy end-to-end monitoring with hands-off reliability and optimization, even at a massive scale.

Secure & Simplified Data Exchange

Databricks revolutionizes data sharing. Collaborate openly and securely with anyone on any platform. Share live data, models, and notebooks without proprietary formats, expensive replication, or complex ETL (extract, transform, load) processes. Even monetize your data through the Databricks Marketplace.

Optimized Data Asset Management

Databricks intelligently tailors computing resources and autoscales workloads to meet deadlines and budget constraints. Automatic error correction ensures smooth operation, allowing you to focus on insights, not infrastructure.

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How we can transform your business with Databricks Platform

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Databricks FAQs

No, Databricks is not owned by Microsoft. However, they have a close partnership that goes beyond just investment. They’ve collaborated on projects like Azure Databricks and the Open and Governed Data Lakehouse Foundation, showcasing their commitment to advancing data analytics.
Databricks does provide ETL capabilities. However, it is not restricted to being an ETL tool; it is better described as a data intelligence platform—in short, a platform that aims to manage all data operations.

Databricks and Snowflake are both powerhouses with different strengths

  • Architecture: Databricks separates data storage and processing, while Snowflake takes a more unified data warehouse approach.
  • Billing: Databricks offers a subscription or open-source model, while Snowflake uses a pay-per-use system.
  • Use Cases: Databricks shines in machine learning and streaming, while Snowflake excels in analytics and reporting.
  • Indexing & Ingestion: Databricks offers advanced indexing and both batch/continuous ingestion. Snowflake focuses on batch processing with less emphasis on indexing.