Data Bricks Use Cases

Internet of Things (IoT)

The proliferation of embedded and networked sensors are bringing unprecedented visibility into previously opaque systems and processes with the data generated. A wealth of innovations could be made if you are ready to take on the challenge to turn the torrent of data into actionable insights.

With Databricks you can:
•Effortlessly ingest and process streaming data from a vast network of sensors in real-time.
•Iterate rapidly to develop new products based on information hidden in the sensor data.
•Seamlessly deploy sophisticated algorithms to production, achieving tangible improvements based on insights discovered.

Manufacturing and Industrial

The modern assembly line is made up of highly instrumented machines, with millions of sensors reporting billions of data points.

With Databricks you can:
•Improve quality control and increase yield by parsing sensor data in real-time.
•Increase machine uptime with preventative maintenance using advanced machine learning algorithms.

Media and Entertainment

To handle the vast number of data sources, broad user base, and billions of data points created by millions of interactions, you need a data platform that can cope with the growing scale and complexity of your data.

With Databricks you can:
•Gain a holistic view of your users by easily aggregating data from wearables, digital properties, or other relevant data sources.
•Develop data-driven recommendations using advanced machine learning algorithms to increase customer engagement.
•Provide a tailored and personalized view of pertinent data for each individual you serve.

Retail and Consumer Packaged Goods

Internet search, content browsing, and social media activities have the potential to reveal deeper customer insights than ever. Your success depends on being able to extract these insights for your customers.

With Databricks you can:
•Build a unified view of your customer behavior based on their online and offline behavior.
•Infer hidden propensities and recommend next product to buy using machine learning algorithms.
•Build reports in real-time to provide actionable intelligence for your customers.

How Databricks makes big data simple.

Here are some examples of what Databricks can do.


Prepare Data
•Import data using APIs or connectors
•Clean malformed data
•Aggregate data to create a data warehouse

Databricks is powered by Spark, giving it the ability to ingest data from a diverse set of sources and perform simple yet scalable transformations of data. The real-time interactive querying environment and data visualization capability of Databricks makes this typically slow process much faster.


Perform Analytics
•Explore large data sets in real-time
•Find hidden patterns with advanced analytics algorithms
•Publish customized dashboards

With Databricks, developers and data scientists can work in SQL, Python, Scala, Java, and R – with a wide range of advanced analytics algorithms at their disposal. Teams can be instantly productive with real-time analysis of large-scale datasets on topics ranging from user behavior to customer funnel. Databricks can easily publish these results and complex visualizations as part of notebooks, integration with third party BI tools, or customized dashboards for consumption with a few clicks.


Build data products
•Rapid prototyping
•Implement advanced analytics algorithms
•Create and monitor robust production pipelines

Databricks allows teams of developers and data scientists to efficiently experiment with new product ideas through the interactive workspace. Advanced analytics libraries such as MLlib and GraphX also provide an easy way for teams to deploy sophisticated algorithms in Spark. Once a prototype has been built, one can seamlessly deploy it in production – at scale – using the Jobs feature.