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Overview
Become an expert in Hadoop by getting hands-on knowledge on MapReduce, Hadoop Architecture, Pig & Hive, Oozie, Flume and Apache workflow scheduler. Build familiarity with HBase, Zookeeper, and Sqoop concepts while working on industry-based use-cases and projects.
Why get Big Data Hadoop Developer Certification from Cognixia?
As job opportunities multiply for IT professionals in Big Data & Hadoop, career opportunities for industry-savvy professionals are everywhere. According to a recent study, by 2020, the Big Data & Hadoop market is estimated to grow at a compound annual growth rate (CAGR) of 58%, surpassing $16 billion.
Cognixia’s Big Data Hadoop Developer certification course highlights the key ideas and proficiency for managing Big Data with Apache’s open source platform – Hadoop. Not only does it impart in-depth knowledge on core ideas through the course, it also facilitates executing it through a variety of hands-on applications. Through this course, IT experts working in organizations of all sizes can learn to code within the MapReduce framework. The course also covers advanced modules like Yarn, Zookeeper, Oozie, Flume and Sqoop.
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What you'll learn
- Learn to write complex codes in MapReduce on both MRv1 & MRv2 (Yarn) and understand Hadoop architecture
- Perform analytics and learn high-level scripting frameworks Pig & Hive
- Build an advanced understanding of Hadoop system, including Oozie, Flume and Apache workflow scheduler
- Gain familiarity with other concepts, such as Hbase, Zookeeper and Sqoop
- Get hands-on expertise in numerous configurations surroundings of Hadoop cluster
- Learn about optimization & troubleshooting
- Acquire in-depth knowledge on Hadoop architecture by learning about Hadoop Distribution file system (vHDFS one.0 & vHDFS a pair of.0)
- Get to work on Real Life Project on Industry standards
- Project 1: “Twitter Analysis”
- To date, approximately 20% of all data is in structured form. The limitation of RDBMS is that we can isolate and store only structured data. Hadoop, however, enables us to store or process all data – structured or unstructured.
- Today, Twitter has become a significant source of data, as well as a reliable tool for analyzing what the consumer is thinking about (sentiment analysis). This helps in figuring out which topics and discussions are trending at any given time. During this case study, we’ll aggregate data from Twitter through various means, to conduct an exploratory analysis.
- Project 2: “Click Stream Analysis”
- E-commerce websites have had a tremendous impact on local economies across the globe. As part of their operation, e-commerce websites maintain a detailed record of user-activity, storing it as clickstream. This activity is used to analyze the browsing patterns of a particular user, thus helping e-commerce technology to recommend products with high accuracy, during current and future visits. This also helps e-commerce marketers, as well as their technology platforms, to design personalized promotional emails for its users.
- In this case study, we’ll see how we can analyze the clickstream and user data by using Pig and Hive. We’ll gather the user data with the help of RDBMS and capture user behavior (clickstream) data by using Flume in HDFS. Next, we’ll analyze this data using Pig and Hive. We’ll also be automating the clickstream analysis by putting workflow engine Oozie to use.
