Big Data Overview Training in Helena

Enroll in or hire us to teach our Big Data Overview class in Helena, Montana by calling us @303.377.6176. Like all HSG classes, Big Data Overview may be offered either onsite or via instructor led virtual training. Consider looking at our public training schedule to see if it is scheduled: Public Training Classes
Provided there are enough attendees, Big Data Overview may be taught at one of our local training facilities.
We offer private customized training for groups of 3 or more attendees.

Course Description


We all know - Big Data is here in a Big way. However, processing that data can still be a Big challenge. This course provides an in-depth overview of the choices you have in processing Big Data. It provides an introduction to what Big Data is, the types of data you might have, approaches to working on and processing the data, and the capabilities, strengths, and weaknesses of those approaches.

After taking this course, you will have a clear understanding of what Big Data is and of the various types of data you may encounter. You will know different techniques and technologies for working with your data, where those technologies are a good fit, and where they are not. You will be well prepared for evaluating what approach is best suited for your needs.

Course Length: 1 Days
Course Tuition: $495 (US)


Some knowledge of databases and data processing is useful, but not required.

Course Outline

Section 1: Understanding Big Data
Big Data Characteristics
Relational Model Overview
Working with Big Data
Data Consistency and CAP
Session 2: NewSQL Databases
NewSQL Overview
Product Overviews
Session 3: NoSQL Overview
Differences from Relational Model
Types of NoSQL Stores
Document Data Model
Graph Data Model
Wide Columnar
Session 4: Hadoop and MapReduce
Session 5: Other Processing Technologies
Apache Pig and Hive
Apache Impala
Apache Storm
Apache Spark
Session 6: MongoDB
Overview and Architecture
Summary of Strenghts/Weaknesses
Session 7: Cassandra Database
Overview and Architecture
Summary of Strenghts/Weaknesses
Session 8: Other Databases and Tools

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