The data warehouse has been an analytics workhorse for decades. Unprecedented volumes of data, new types of data, and the need for advanced analyses like machine learning brought on the age of the data lake. But Hadoop by itself doesn’t really live up to the hype. Now, many companies have a data lake, a data warehouse, or a mishmash of both, possibly combined with a mandate to go to the cloud. The end result can be a sprawling mess, a lot of duplicated effort, a lot of missed opportunities, a lot of projects that never made it into production, and a lot of financial investment without return.Get an inside look at some successful production data architectures of organizations with massive workloads. Look under the hood at how other companies have gotten high scale machine learning projects working, and how data architectures are changing over time. Then apply this new knowledge, discuss how it applies to the problems you’re facing, and where we’re all going from here.

Takeaways:

• Look at successful data architectures from companies like Philips, Anritsu, Uber
• Learn to eliminate duplication of effort between data science and BI data engineering teams
• Avoid some of the traps that have caused so many big data analytics implementations to fail
• Get AI and ML projects into production where they have real impact, without bogging down essential BI
• Study analytics architectures that work, why and how they work, and where they’re going from here

Speaker: Paige Roberts, Open Source Relations Manager, Vertica

In 23 years in the data management industry, I’ve worked as an engineer, a trainer, a support technician, a technical writer, a marketer, a product manager, and a consultant. I’ve built data engineering pipelines and architectures, documented and tested open source analytics implementations, spun up Hadoop clusters, picked the brains of stars in data analytics and engineering, worked with a lot of different industries, and questioned a lot of assumptions.

Now, I promote understanding of Vertica, distributed data processing, open source, high scale data engineering, and how the analytics revolution is changing the world.

Vertica is trusted by thousands of leading data-driven enterprises around the world, including AT&T, Etsy, Twitter, Intuit, Uber and more to deliver speed, scale and reliability on mission-critical analytics. The Vertica Analytics Platform is purpose built from the very first line of code for Big Data analytics. It is designed for use in data warehouses and other big data workloads where speed, scalability, simplicity, and openness are crucial to the success of analytics. Vertica relies on a tested, reliable distributed architecture and columnar compression to deliver blazingly fast speed. All based on the same powerful, unified architecture, the Vertica Analytics Platform provides you with the broadest range of deployment models, so that you have complete choice as your analytical needs evolve.

Social Media Links:@VerticaBigData | Vertica LinkedIn