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This module will introduce you to the various concepts of big data analytics, and the seven Vs of big data—Volume, Velocity, Veracity, Variety, Value, Vision, and Visualization. Explore big data concepts, platforms, analytics, and their applications using the power of Hadoop 3.
Hands-on: No hands-on
Here you will learn the features in Hadoop 3.x and how it improves reliability and performance. Also, get introduced to MapReduce Framework and know the difference between MapReduce and YARN.
Hands-on: Install Hadoop 3.x
Learning Objectives: Learn to install and configure a Hadoop Cluster.
Hands-on: Install and configure eclipse on VM
Learn about various components of the MapReduce framework, and the various patterns in the MapReduce paradigm, which can be used to design and develop MapReduce code to meet specific objectives.
Hands-on :Use case - Sales calculation using M/R
Learn about Apache Spark and how to use it for big data analytics based on a batch processing model. Get to know the origin of DataFrames and how Spark SQL provides the SQL interface on top of DataFrame.
Look at various APIs to create and manipulate DataFrames and dig deeper into the sophisticated features of aggregations, including groupBy, Window, rollup, and cubes. Also look at the concept of joining datasets and the various types of joins possible such as inner, outer, cross, and so on
Understand the concepts of the stream-processing system, Spark Streaming, DStreams in Apache Spark, DStreams, DAG and DStream lineages, and transformations and actions.
Hands-on: Process Twitter tweets using Spark Streaming
Learn to simplify Hadoop programming to create complex end-to-end Enterprise Big Data solutions with Pig.
Learn about the tools to enable easy data ETL, a mechanism to put structures on the data, and the capability for querying and analysis of large data sets stored in Hadoop files.
Look at demos on HBase Bulk Loading & HBase Filters. Also learn what Zookeeper is all about, how it helps in monitoring a cluster & why HBase uses Zookeeper.
Learn how to import and export data between RDBMS and HDFS.
Understand how multiple Hadoop ecosystem components work together to solve Big Data problems. This module will also cover Flume demo, Apache Oozie Workflow Scheduler for Hadoop Jobs.
Learn to constantly make sense of data and manipulate its usage and interpretation; it is easier if we can visualize the data instead of reading it from tables, columns, or text files. We tend to understand anything graphical better than anything textual or numerical.
Hands-on: Use Data Visualization tools to create a powerful visualization of data and insights.
Learn a simple way to access servers, storage, databases, and a broad set of application services over the internet.
Hands-on: Implement Cloud computing and deploy models.
DESCRIPTION- Aadhar card Database is the largest biometric project of its kind currently in the world. The Indian government needs to analyse the database, divide the data state-wise and calculate how many people are still not registered, how many cards are approved and how they can bifurcate it according to gender, age, location, etc.
DESCRIPTION- The Citi group of banks is one of the world’s largest providers of financial services, In recent years, they adopted a fully Big Data-driven approach to drive business growth and enhance the services provided to customers because traditional systems are not able to handle the huge amount of data pouring in. Using Hadoop, they will be storing and analyzing banking data to come up with multiple insights.
DESCRIPTION- On Ecommerce Web sites, clickstream analysis is the process of collecting, analyzing and reporting aggregate data about which pages a website visitor visits and in what order. With increasing number of ecommerce businesses, there is a need to track and analyse clickstream data. When using traditional databases to load and process clickstream data, there are several complexities in storing and streaming customer information and it also requires a huge amount of processing time to analyse and visualize it.
It was good to attend the 2-day workshop for agile certification. Thanks for the trainer who was very energetic and gave real-life examples to explain some topics which made the learning easy. I would definitely recommend KnowledgeHut!
The training helped me understand SCRUM and clear the certification in the first attempt and score 100%!
A very well-organized course with an excellent Instructor and balanced course material and content.
Hadoop has now become the de facto technology for storing, handling, evaluating and retrieving large volumes of data. Big Data analytics has proven to provide significant business benefits and more and more organizations are seeking to hire professionals who can extract crucial information from structured and unstructured data. KnowledgeHut brings you a full-fledged course on Big Data Analytics and Hadoop development that will teach you how to develop, maintain and use your Hadoop cluster for organizational benefit.
This course will prepare you for everything you need to learn about Big Data while gaining practical experience on Hadoop.
After completing our course, you will be able to understand:
There are no restrictions but participants would benefit if they have elementary computer knowledge.
Yes, KnowledgeHut offers this training online.
Your instructors are Hadoop experts who have years of industry experience.
Any registration cancelled within 48 hours of the initial registration will be refunded in FULL (please note that all cancellations will incur a 5% deduction in the refunded amount due to transactional costs applicable while refunding) Refunds will be processed within 30 days of receipt of written request for refund. Kindly go through our Refund Policy for more details: http://www.knowledgehut.com/refund
In an online classroom, students can log in at the scheduled time to a live learning environment which is led by an instructor. You can interact, communicate, view and discuss presentations, and engage with learning resources while working in groups, all in an online setting. Our instructors use an extensive set of collaboration tools and techniques which improves your online training experience.
Gain in depth knowledge of Big Data Analytics concepts and tools
Process large data sets with Big Data tools to extract information from seemingly disparate sources
Query databases using Hadoop MapReduce to create scalable, flexible and cost effective solutions
Perform data analytics using Pig, Hive and Sqoop
Implement Integration with HBase and MapReduce
Schedule jobs using Oozie and execute Flume jobs
Understand the use of best practices for Hadoop development
Reinforce concepts by working on a Big Data Analytics Project
Basic programming knowledge is desired though not a prerequisite for attending this course