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Databricks

Unifying data, analytics, and AI workloads through the power of Lakehouse

Founded by the original creators of highly successful open-source data and analytics projects such as Spark, Delta Lake, Delta-sharing, and MLFlow, Databricks Lakehouse provides a cloud-based, open, interoperable, and unified platform with out-of-the-box multi-cloud management support to meet today’s enterprise’s data and advanced analytics demands.

About our alliance

The Deloitte and Databricks alliance combines Deloitte’s industry experience and world-class experience in data modernization and advanced analytics with Databricks’ Lakehouse platform. Bring us your complex business and data requirements and we’ll help you to rapidly enable a target-state data and AI platform to not only meet your immediate needs but also create a foundation to serve your most strategic and long-term business needs. We are armed with a wealth of knowledge, including our Deloitte Databricks Migration Factory, that can provide you with structured approaches and methodologies on how to deliver successful on-time, on-budget implementations of Databricks. From the design phase through operate, automation is applied at every turn with tailored approaches for each of our major joint campaigns (e.g., Lakehouse enablement, multi-cloud management, AI/ML, MPP Migration, Hadoop Migration). In addition, our guidance keeps change management at the forefront, as we aim to simplify the end-to-end data modernization journey for all stakeholders and minimize as much disruption as possible.

 

Data and analytics should be simple, open, and collaborative – and Databricks is just that:

  • SIMPLE: There is one single source of truth for all data – whether structured, semi-structured, or unstructured/sparse, data in all forms are accepted and needs to exist only once to support all workloads.
  • OPEN: The open-source and open-standards of Lakehouse enable organizations to future-proof, supporting out-of-the-box integration with hyper-scaler data and platform services and multi-cloud management – making existing tools easy to work with and proprietary architecture avoidable.
  • COLLABORATIVE: Databricks serves as one integrated platform to support end-to-end data and AI use cases, including traditional BI and SQL workloads – but more importantly, real-time streaming analytics, AI/ML, and data sharing.

Download the PDF: Read more about leveraging the power of data and analytics platforms for improved decision-making.

Value Proposition and Benefits

Contact us

Kale Temple

Partner, Consulting Strategy AI and Transformation

Kale Temple is a Sydney-based partner in the Consulting Strategy AI and Transformation team. He is a data, analytics and machine learning specialist that works with enterprises to establish clear value from these technologies. In 2018 Kale co-founded Intellify, a data science and machine learning consultancy dedicated to helping clients build competitive advantage through industry-leading AI solutions. In the proceeding years, Intellify would grow to over 50 people and would be named a Partner of the Year for Amazon Web Services on three occasions and two with Databricks through high impact use cases delivered on their technology platforms. Today, as a consulting leader at Deloitte, he leverages his expertise in data, analytics and machine learning to orchestrate the delivery of sophisticated solutions that empower business performance and exponential growth.