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What is Big Data? + Key Reasons to Learn Big Data Analytics starting with a vendor-agnostic approach:
This Intro to Big Data is a unique approach to help you act on data for real business gain – not what a tool can do, but what you can do with the output from the tool. Big data as defined by Wiki is a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.
In this hands-on Introduction to Big Data Course, learn to leverage big data analysis tools and techniques to foster better business decision-making – before you get into specific products like Hadoop training (just to name one). Learn ways of storing data that allow for efficient processing and analysis, and gain the skills you need to store, manage, process, and analyze massive amounts of unstructured data to create an appropriate data lake.
Defining Big Data
Delivering business benefit from Big Data
Analyzing your data characteristics
Overview of Big Data stores
Selecting Big Data stores
Integrating disparate data stores
Employing Hadoop MapReduce
The building blocks of Hadoop MapReduce
Handling streaming data
Abstracting Hadoop MapReduce jobs with Pig
Performing ad hoc Big Data querying with Hive
Creating business value from extracted data
Defining a Big Data strategy for your organization
Enabling analytic innovation
Course Tuition Includes:
After-Course Instructor Coaching
When you return to work, you are entitled to schedule a free coaching session with your instructor for help and guidance as you apply your new skills.
After-Course Computing Sandbox
You'll be given remote access to a preconfigured virtual machine for you to redo your hands-on exercises, develop/test new code, and experiment with the same software used in your course.
Free Course Exam
You can take your Learning Tree course exam on the last day of your course or online any time after class.
Standard Course Hours: 9:00 am – 4:30 pm
*Informal discussion with instructor about your projects or areas of special interest: 4:30 pm – 5:30 pm
I really learned the 'how-to' from the exercises. I tend to be a very hands-on person. I learned almost all of what I know by doing, so I really thought that the exercises helped me learn the material. They also helped me feel a bit more confident that I can actually perform these functions in the real world.
- P. Ward, Web Developer
The Raymond Corporation