On Beer, Chips & Data: Why Your Big Data Project is Bound to Fail

Eldad Farkash, Co-Founder & CTO, Sisense

Mon. Apr. 13, 2015 6:30pm
New York City
Free shirts, beer, bottles of Sisense Secret Hot-Sauce, swag, drinks, candy & more!

Eldad Farkash

Co-Founder & CTO, Sisense

On Beer, Chips & Data: Why Your Big Data Project is Bound to Fail

Join the presentation to watch Eldad reveal the secrets of In-Chip Technology, discover why querying databases is a lot like fetching beer from the fridge, and see a real-life demonstration of how you can analyze one billion rows of data easily with this new and innovative technology.

In-memory technology has become an increasingly popular solution for high performance analytics. But keeping huge datasets in RAM is expensive, and fetching that data from RAM to the CPU is slow and frustrating.

Enter In-Chip technology, the revolutionary analytics stack that sidesteps both these issues by storing relevant data within the CPU cache itself, applying vectorization, and directly replacing the CPU instruction set to make full use of existing computational resources.

The result: users can query truly Big Data using off-the-shelf hardware, at a fraction of the time and costs of in-memory systems.

Eldad Farkash

Co-Founder & CTO,

Eldad started his career in Business Intelligence while developing at age 16 at Gilon Systems, Israel's largest Database Integrator.

While working early on MDX compilers, Eldad envisioned a future where columnar in-memory database would become pervasive. He recognized the evolution of hardware and understood that it would change the way BI could be architected, away from OLTP, OLAP or traditional in-memory. This thinking is at the genesis of Sisense's unique technology.

Eldad and his team of Data Scientists, Hardware and Software engineers focus on Sisense's mission: Making Business Intelligence a Reality for Everyone.

Eldad dedicates his engineering depth and passion for world-class user experience (UX) to building leading edge solutions for all types of data, from On-Premises to Cloud Databases and Hadoop.

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