The IT Skills Taught in Databricks Training
Big data came to the forefront of technology in the mid- to late 2000s. As organizations started to gather more and more data, they struggled in finding ways to store and process it, which ultimately may have resulted in a fewer major innovations. Although the Apache Hadoop project gained popularity quickly, many organizations faced technical challenges in working with the distributed processing framework. But when a group of UC Berkeley students built Apache Spark, it was quickly recognized as the next major step of big data processing. Those students went on to start the company Databricks, leveraging their intimate knowledge of the Apache Spark framework to build a web-based platform for working with Spark. Databricks offers automated cluster management and IPython-style notebooks that make working with data very easy for data scientists and developers alike. Databricks also developed Delta Lake, the open source storage layer for data lakes. Due to its ability to execute and the completeness of its vision, Databricks has been named a leader in Gartner’s Magic Quadrant for Data Science and Machine Learning for three years in a row.
In order to help fulfill its customers’ growing needs for training, Databricks chose ExitCertified to be its lone certified training partner in North America. So if you’re looking for a one-day Apache Spark Overview class or a more in-depth Apache Spark Programming class, ExitCertified has you covered. These classes assume that you have a development background that includes either Python or Scala knowledge. If you need a primer on either language, there are one-day classes for each that you should take prior to Apache Spark Programming.
Beyond the basic Spark training, you can choose to move on to classes on Delta Lake, machine learning, or Spark tuning. While the Delta Lake class targets IT operations and professionals in data engineering, the machine learning classes are appropriate for developers and data scientists. The labs for Spark courses generally use notebooks that students can run on the Databricks Community edition for free during and any time after class.