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The Five Keys to Transforming Data Architectures for the Automotive Market
Data is exploding at the edge and in the core. Companies are realizing that they can make better decisions by utilizing larger data pools. Autonomous vehicles, smart cities and urban transportation are all adding to data growth and the need for a scalable, real-time data architecture from the core to the edge.

This webinar will discuss how transforming the IT architecture makes it possible to leverage both data at the edge and the core system resulting in real-time decisioning at petabyte scale that can determine risk levels and react in micro milliseconds, making things like fully autonomous vehicles possible.

These new architectures have huge implications for business leaders and data architects focusing on mobility platforms.

Please join this webinar to learn more about:

- The need for new platforms to run next generation applications
- Designing data architectures that include real time processing closer to where the decisions are being made. This includes a combination of real-time data at the edge and historical data at the core.
- The role of AI and ML analysis to speed and optimize IoT data
- The need for comprehensive edge-to-core IoT blueprints
- Why Apache Spark is ideal for fusing data and creating layers that enable us to create new rules and machine learning models. Priceless insights flow from these models.
- How to reduce server footprint by up to 80% in order to scale effectively in the face of IoT

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