Price
$239
Course Type
Online
Duration
6 hours
Date
Various dates throughout the year
Entry Requirements
Beginner Level

About this course

Data Just Right LiveLessons provides a practical introduction to solving common data challenges, such as managing massive datasets, visualizing data, building data pipelines and dashboards, and choosing tools for statistical analysis. You will learn how to use many of today's leading data analysis tools, including Hadoop, Hive, Shark, R, Apache Pig, Mahout, and Google BigQuery.

Data Just Right LiveLessons shows how to address each of today's key Big Data use cases in a cost-effective way by combining technologies in hybrid solutions. You'll find expert approaches to managing massive datasets, visualizing data, building data pipelines and dashboards, choosing tools for statistical analysis, and more.

Keywords: data analytics, datasets, Hadoop, Hive, Shark, R, Apache Pig, Mahout, Google BigQuery

What are the requirements?

  • ¢Basic familiarity with SQL ¢Some experience with a high-level programming language such as Java, JavaScript, Python, R ¢Experience working in a command line environment

What am I going to get from this course?

  • Over 81 lectures and 5 hours of content!
  • What You Will Learn: ¢Mastering the four guiding principles of Big Data success”and avoiding common pitfalls ¢Emphasizing collaboration and avoiding problems with siloed data ¢Hosting and sharing multi-terabyte datasets efficiently and economically ¢"Building for infinity" to support rapid growth ¢Developing a NoSQL Web app with Redis to collect crowd-sourced data ¢Running distributed queries over massive datasets with Hadoop and Hive ¢Building a data dashboard with Google BigQuery ¢Exploring large datasets with advanced visualization ¢Implementing efficient pipelines for transforming immense amounts of data ¢Automating complex processing with Apache Pig and the Cascading Java library ¢Applying machine learning to classify, recommend, and predict incoming information ¢Using R to perform statistical analysis on massive datasets ¢Building highly efficient analytics workflows with Python and Pandas ¢Establishing sensible purchasing strategies: when to build, buy, or outsource ¢Previewing emerging trends and convergences in scalable data technologies and the evolving role of the "Data Scientist"

What is the target audience?

  • Professionals who need practical solutions to common data challenges that can be implemented with limited resources and time.
Enquire now

Enquire now