The Big Data course is designed to offer a comprehensive training on Hadoop Ecosystems and Big Data. The course will give a detailed insight behind the art of writing MapReduce programs and also enable understanding on management of large data sets with Pig Latin, Hive and HBase. The training also offers in-depth analysis on HDFS (Hadoop Distributed File System) and managing Hadoop Cluster.
How big is Big Data?
The growth of internet and advancement in real-time system has led to an increased requirement in proper storage of large dataset and enable quick access. This large records and new data-type generate from areas like social network sites and other real-time systems. This is what we refer as Big Data.
Let's see an example: Facebook stated that 500+ terabytes of new data gets added every day into their databases. "So what's the big deal here, Facebook can buy a dozen of hard disks every day to store this data". Storing the data is not a problem for Facebook, it’s the retrieval. Imagine how long it will take to search your Facebook photo into petabytes or exabytes of data that has been uploaded by users till now. You may end up waiting a couple of hours for sure.
Recent study indicates that there are more than 150 million personal blogs, Facebook has more than 700 million and Twitter has more than 250 million registered users. This clearly indicates such a gargantuan proportion of data generating each day and it needs proper management.
Big Data is usually classified by three main measurement approaches: Volume, Velocity and Variety.
Volume: A Home Computer has 1-2 TBs of storage. Today, a single one way flight from Mumbai to Delhi generate 200 TBs of flight data; Facebook ingest 500+ TBs of data every day; Online Stores, Health Care, are generating and storing very big amount of data. Large amount of data gets generated each day from real-time sources such as traffic control system.
Velocity: There was a time when we used to believe that yesterday's data is recent. Now a couple of minutes old messages and tweets are not interested to us. Clickstreams, Ad impressions saves millions of events every second; Stock trading changes, Mobile Phones, Online Videos, Real Time Gaming, Sensors etc. are generating millions of events per second. This high velocity represents BIG DATA.
Variety: Data isn't just numbers and strings now, real world have data in many different formats including 3D data, audio, video, unstructured text of log files, financial transactions and many more forms which we can expect to see in future. Traditional databases are unable to store and process this vast amount of unstructured and structured Big Data in a reasonable time frame.
What is the solution then?
There are some complex data management tools available to manage distribution of the data of which Hadoop is one common name that we often come across. Developed by Apache Foundation, it is an open source framework that facilitates storing and managing large set of data in a distributed environment.
Why learn Hadoop?
Hadoop can be considered as the most common requirement in IT sector for those who have planned for Big Data management. Understanding Hadoop offers a comprehensive idea behind the usage of the application. Moreover it helps to determine the pros and cons using the application when dealing with large data sets.
“Big Data” has come a long way and is probably the most significant contribution in the field of data management. The rise of this new technology is also increasing the requirement for quality professional and here, learning Hadoop comes in play for those willing to switch to this new domain.
There has never been a better time to get Hadoop training.
Top companies using Hadoop
Module Goals: In this part we will understand the problems with traditional systems and how Hadoop can resolves these shortcomings
- Problems with Traditional Systems
- Problems that can be solved with Hadoop
Hadoop: Basic Concepts and HDFS
Module Goals: Prime objective of this module is to know the internals of Hadoop Architecture and HDFS. We will also know what is NameNode, Secondary NameNode, and DataNode in Hadoop cluster.
- Hadoop Architecture
- Hadoop Components
- The Hadoop Distributed File System (HDFS)
- NameNode, Secondary NameNode, and DataNode
Hadoop Clusters Ecosystem
Module Goals: Learning common Linux shell commands and getting an overview of Hadoop Jobs, Tasks and see how a production Hadoop cluster runs.
- Common Linux Shell commands
- Hadoop Cluster Overview
- Hadoop Jobs and Tasks
- Production Hadoop Clusters
Introduction to MapReduce
Module Goals: An overview of MapReduce programming, you will create your first MapReduce program ie. WordCount.
- MapReduce Overview
- Example: WordCount
- Writing a MapReduce Program in Java
Basic MapReduce API Concepts
Module Goals: In-depth details for MapReduce Programming
- Writing MapReduce Drivers, Mappers, and Reducers in Java
- Hadoop Development by Using Eclipse
- Writing a MapReduce Program Using Streaming API
Hadoop 2.0 New Features
Module Goals: In this part we will learn all the new features of Hadoop 2.0 and understand the YARN framework.
- NameNode High Availability
- HDFS Federation
- Programming in YARN framework
- Running MR in YARN
- MRv2 and YARN
Partitioners and Reducers
Module Goals: In this part we will learn how Partitioners and Reducers Work Together, how to decide the number for mappers or reducers.
- How Partitioners and Reducers Work Together
- Determining the Optimal Number of Reducers for a Job
- Writing Customer Partitioners
Data Loading techniques from an RDBMS into HDFS by
Module Goals: Diving more deeper into Hadoop tools like Sqoop: To transfer bulky data between Hadoop and relational datbases, Flume: To move large amount of Log data. Hive and Pig to analyze data and more.
- Using Sqoop
- Managing Real-Time Data Using Flume
- Hive Overview
- Pig Overview
- HBase Overview
- The ZooKeeper Service
- Introduction to Oozie
- Creating Oozie Workflows
Data Input and Output
Module Goals: In this part we understand how to work with I/O operations in Hadoop.
- Creating Custom Writable and Writable-Comparable Implementations
- Saving Binary Data Using SequenceFile and Avro Data Files
- Issues to Consider When Using File Compression
- Implementing Custom InputFormats and OutputFormats
Diving Deeper into the Hadoop API
Module Goals: Learning in-detail about Hadoop API and you will also get some tips for practical development.
- Using the ToolRunner Class
- Setting Up and Tearing Down Mappers and Reducers
- Decreasing the Amount of Intermediate Data with Combiners
- Accessing HDFS Programmatically
- Using The Distributed Cache
- Using the Hadoop API's Library of Mappers, Reducers, and Partitioners
- Practical Development Tips and Techniques
Strategies for Debugging MapReduce Code
Module Goals: In this part we will understand how to debug MapReduce code which can be a life saver when your get stuck
- Writing and Viewing Log Files
- Retrieving Job Information with Counters
- Creating Map-Only MapReduce Jobs
Common MapReduce Algorithms and Examples
Module Goals: In this part we understand the different algorithms to sort and search and index large data sets. We will also work on some more examples and projects.
- Sorting and Searching Large Data Sets
- Indexing Data
- Computing Term Frequency - Inverse
- Document Frequency
- Calculating Word Co-Occurrence
- Performing Secondary Sort
This course is designed in a way to offer you the following:
- Knowing the internals of MapReduce and HDFS
- Learning how to write MapReduce code
- Getting unique insights that help you tune, secure, and manage your Hadoop deployment
- Knowing about best practices for Hadoop development, debugging, and implementation of workflows and
- common algorithms
- Knowing how to leverage Hive, Pig, Sqoop, Flume, Oozie and other Hadoop ecosystem projects
- Optimal hardware configurations and network considerations for integrating a Hadoop cluster with the data center
- Writing and executing joins to link data sets in MapReduce
- Advanced Hadoop API topics required for real-world data analysis
How are online classes conducted?
All the classes are conducted online via GotoWebinar. A simple but robust conferencing tool that enable users to interact online with voice and text. In order to be a part of the training, an access to a computer backed by stable internet connectivity is essential.
Do you conduct classes on weekdays or weekends?
Considering all the obstacles that may come on your professional way, we decided to keep our classes only in the weekends.
What is the required minimum internet bandwidth to participate in the LIVE classes?
For seamless connectivity we recommend having internet bandwidth with 1 Mbps speed. However it is seen that the online classroom works well even with 512 Kbps or 256 Kbps connection.
What about the certification process?
Every individual joining the course and finish it successfully is eligible to receive the final certificate of training. In this course, certificates are provided after completing your project.
Do you provide physical certificate?
Yes, the certificate issued is a hard-copy endorsed by industry experts. They will be mailed at the physical address for delivery.
What if I miss a class?
Skipping a class is not indeed a good option. However in case of unforeseen circumstances if you miss a class, then you can watch the recording of the missed class from our archive. Alternatively we also offer flexibility to join other batches to complete the missed class.
What if I don’t get answers to my queries raised in the class?
This generally does not happen. But in any case if you do not receive your answer to the query simply get back to the support team for quick resolution.
How long do I have access to the online course materials?
All the course materials are accessible life-time. Once you join the course you will be given the provision to access the same. Moreover there is no restriction to reach our support team for one enrolled in a course.
Who will teach?
All our instructors are working professionals having adequate knowledge and experience on information technology. With their real-life experience they offer more insights behind the development which helps gain critical knowledge needed to get established as a successful techie.
What is On-Demand 24x7 Tech support?
Our technical support team is well set to manage any of your technical requests. With this facility you can reach the instructors and even seek clarification of any queries from our support team. However it is advisable to notify us one day before so as to arrange and cater your request effectively. Our support teams are available during general office hours from 9:00 AM to 7:00 PM (Monday – Saturday).
How can I avail the support?
In order to avail our support facility all you need is to contact us via Skype ID which will be allocated to you after enrollment. In case you fail to reach our support team, please drop us an email at email@example.com stating your date and time of availability. Once received, you will get an automated confirmation message from our support team followed by further action.
Will I get a real life project to work upon?
Yes, every project that you accomplish along with the training is based on real-life scenario. This helps to grasp the technology in a firm manner. Moreover the project will also be mentioned in the certificate for ease of reference.
Do I get the support after the completion of the course?
Absolutely! Our support team is available to reach even after you complete the course. So if at any point of time you need some clarification, do get in touch with the team and we ensure your request is met.
What's your refund policy?
Our sole aim is to provide you the best of the training. But if our style does not match with your criteria you are always free to drop from the course. However the refund is valid within ten days of your purchase. In order to ask for refund, you can get in touch with our support team and they will do the needful.
How can I make the payment?
Our payment mode is online. You can pay it through our secured online payment gateway using Credit Card, Debit Card or Net banking. In case of foreign nationals we have the option for payment through PayPal.
So if you are looking for a jumpstart in career in Hadoop, just do not hesitate to call us up and we will take care of the rest. Following are our contact details:
Customer Care: +91 999 755 8888