Databricks For Data Science Community

Learn how Databricks products break silos for the data science community and boost productivity by providing technologies like Delta Lake, MLflow, and Serverless Compute. This E-Guide includes coding screenshots of the said platforms to assist the readers with understanding them in a better way. Whether it is about building incremental pipelines or developing Machine Learning models, practitioners can now introduce automation in their workflows and accelerate project completion in a hassle-free manner. With the help of low-cost and flexible Databricks technology, organizations can integrate all their data and AI in a unified system to stimulate business growth through strong teamwork.

To unlock the true value of data, companies need to be able to utilize it intelligently while making sure that data is coming from reliable sources. Besides establishing reliability, close collaboration between different teams belonging to data engineering, science, and analytics departments, and decision-makers is also necessary to leverage the data for carrying out strategic planning for the business.

This E-Guide will help you learn:

  • The what and why of Delta Lake
  • How to build incremental pipelines
  • How to achieve instant computing and lower TCO with Serverless Databricks
  • Ways in which MLflow is aiding the ML model development process and how you can use it
  • How Royal Cyber resolved the challenges of its customers with Databricks

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