Hadoop for Database Professionals
Gluent has a new training offering for database professionals wanting to understand how Hadoop fits into their world.
Since joining Gluent I’ve been heads down finalizing the company’s first public training offering: Hadoop for Database Professionals. This one day course will provide folks who are familiar with relational database management system concepts a look at what Hadoop is and why it’s relevant to them. At Gluent we have seen first-hand how Hadoop can open up a whole new world for data access and analytics that wasn’t available before. While Gluent is primarily focused on a hybrid approach, using RDBMS + Hadoop, the training will only touch on this topic briefly. We’ll provide a more well-rounded discussion about Hadoop and it’s components, bringing the new world technologies to the forefront.
The seminar will begin with the basics to give you a starting point with Hadoop. We’ll jump right in with a discussion on the architecture, components, and how it differs from the relational database that we’re all so familiar with. From there, we will dive deeper into the technologies that are built-in to Hadoop and a part of the greater Hadoop ecosystem.
We’ll also bust some common myths about Hadoop along the way to ensure you have your facts straight. Amazingly enough, many misconceptions about the technology still exist!
After some mythbusting, the course will move into more detail about SQL engines on Hadoop. The data stored in HDFS can be accessed using a familiar language, and our good friend, SQL. The evolution of SQL on Hadoop technologies is advancing rapidly, with improved performance and even ACID-like capabilities, in some cases. Gone are the days of hand-coding MapReduce in Java!
The day will wrap up with some real-world examples of how Hadoop has been successfully implemented in various use cases. From a data lake to advanced analytics platform, we’ll describe the different ways that we have seen Hadoop used in the wild.
The course will provide attendees with knowledge to begin speaking about, and working with, Hadoop, and ultimately help them answer the question “Why Hadoop?”.
If you’re interested, please register for one of the 3 public courses that are available. Space is limited in each session as to provide the best possible interaction between student and instructor, so register quickly.
March 7–8, 2017, 1pm-5pm GMT (spread across 2 days to accommodate non-US based attendees)