Speaker: Joel Budgor, Instructor, ExitCertified
What is the Databricks platform?
Joel Budgor: Databricks is a cloud-based platform for data engineering, data science, and machine learning. Among the features of this platform, it automates the handling of many low-level tasks common to data engineering, so data practitioners can focus on business objectives. It offers a state-of-the-art collaborative tool suite and development platform. It scales to handle massively large complex data sets. To reduce costs, it offers a pay-as-you-go pricing model. The Databricks platform includes robust security features to protect assets and satisfy regulatory requirements. And finally, no mention of Databricks would be complete without highlighting the fact that Databricks is behind some of the industry's most innovative big data platforms, platforms that are defining the future of big data like Spark and Delta Lake and Photon. Indeed, just last year Databricks won two awards from the Association of Computing Machinery: one for their Spark processing engine, which has revolutionized big data processing. The other--for this new product called Photon, their new high-performance query engine, which just set the world speed record for data warehouse performance.
What do you like about teaching Databricks?
Joel Budgor: I'd say there are really two things I enjoy about the Databricks classes. One is the technology itself, the user interface, the tools that they've created, the environment in which you're operating is just incredibly sophisticated and polished and a lot of fun to work in. Even more than that, however, are just the ideas behind the platform: taking a problem and creating a framework that can dissect that problem, break it down into discrete components that can be distributed over a cluster, run in parallel, and organized to produce a collective result at the end is just fascinating to me. And that, that's really what's fun to talk about and think about.
What are the various tracks for Databricks training?
Joel Budgor: Databricks provides three learning paths, each of which culminate in either associate- or professional-level certifications. The first is the data analyst path. It's targeted at people who bring a sequel skill set to the big data world. The second is the data engineering path. It's targeted at professional programmers used to munging and transforming and analyzing data at a primitive level. And the third is the machine language practitioner used to building feature sets and training and validating machine learning models.
