Big Data Hadoop Certification Training Course
Big Data is the amount of data that cannot fit into the memory of a single computer system. With each passing day, Big data is growing bigger, is more difficult to make sense of, is being generated at a much faster rate and this trend is only going to intensify in our data-driven digital world.
Companies of all shapes and sizes have been getting to grips with new ways of handling the incredible volume of information that is becoming available to us every day with Big Data Hadoop.
For example, users of Facebook upload around one billion pieces of content to the social network site every day. In industry, machinery and vehicles are fitted with sensors and trackers that record their every move, and whenever we call a call centre, an audio recording of our conversation is made, and stored in a huge digital database. Big Data Hadoop Certification Training Course help you elaborate these.
In addition, whenever we go online (as most of us increasingly do for a number of reasons – shopping, socialising, making travel arrangements) we leave behind a digital footprint – a record of websites we visit, products viewed, even how long we leave the mouse cursor over certain areas of the screen, in some circumstances.
We collectively refer to both these huge datasets we are building i.e. Big Data Hadoop, and the practice of interpreting, analysing and acting upon insights gleaned from this information, as “big data” – and it is changing the world we live in.
But Big Data Hadoop is not just for the big boys, it matters to every company – no matter how small or traditional. To cater for this huge demand many companies have sprung up to offer services to other businesses, enabling them to launch big data initiatives of their own. In other words, to leverage the information they have available to improve effectiveness and efficiencies in their business, and ultimately increase profits.Big Data Hadoop Certification Training Course help you learn all these in detail.
A lot of the software and analytics tools needed to carry out big data Hadoop analysis are built on open source principles – meaning they are essentially in the public domain and free for anyone to use for any purpose.
For example, Big Data Hadoop is a framework – a collection of software tools and applications – designed to allow organizations of any size to store and analyze huge amounts of information. It is designed to run on cheap, commonly-available hardware rather than expensive, specialist equipment that would previously have been necessary.
Companies including Amazon, Google, IBM, HP, as well as newer names such as Hortonworks, MapR and Cloudera offer big data solutions and support, as well as tailored versions of the free products, designed to work out-of-the-box and with less complex setup requirements. This also enables companies to minimise infrastructure investments or avoided completely by using cloud-based storage and analysis tools that can be rented when needed.
Big Data Hadoop Certification Training Course is best designed to suit your needs and customized for everyone.
If you also want to take admission in Big Data Hadoop Certification Training Course, then join Samyak Computer Classes today.
Duration
2.5 Months including Lab
Eligibility
Undergraduates, Graduates
Post-Graduates
Job Aspirants
Pre-requisites
Data Analytics Basic
SQL
Hadoop has the ability to store as well as process bulks of data in any format. With data volumes going larger day by day with the evolution of social media, considering this technology is really, really important.
Unmatched computing power: The distributed computing model of Hadoop processes big data in a fast pace. The more computing nodes, the more processing power.
Effective fault tolerance: There is no need to panic in hardware failure as Hadoop has the facility to protect data and applications. In case a node fails, jobs are automatically redirected to other nodes hence no obstruction in distributed computing. It also stores multiple copies of data.
Superb flexibility: There is no need to preprocess data before its storage just you used to do in conventional relational databases. You can store as much data as you want and use it later. Unstructured, text, images and videos can also be stored easily.
Scalability: By adding nodes you can enhance your system to handle more data. There is no need to be a pro in system administration.
Affordable: As the open source network is free, it uses commodity hardware for the storage of large data.
1.The Motivation & Limitation for Hadoop
- Problems with TraditionalLarge-Scale Systems
- Why Hadoop&Hadoop Fundamental Concepts
- History of Hadoop with Hadoopable problems
- Motivation & Limitation of Hadoop
- Available version Hadoop 1.x & 2.x
- Available Distributions of Hadoop (Cloudera, Hortonworks)
- Hadoop Projects & Components
- The Hadoop Distributed File System (HDFS)
2.Hadoop Ecosystem& Cluster
Hadoop Ecosystem projects & Components overview
- HDFS – File System
- HBase – The Hadoop Database
- Cassandra – No-SQL Database
- Hive – SQL Engine
- Mahout
Hadoop Architecture overview Cluster Daemons&Its Functions
- Name Node
- Secondary Node
- Data Nodes
3. Planning Hadoop Cluster& Initial Configuration
- General Planning Considerations
- Choosing the Right Hardware
- Network Considerations
- Configuring Nodes
- Planning for Cluster & Its Management
- Types of Deployment
- Cloudera Manager
4. Installation &Deployment of Hadoop
- Installing Hadoop (Cloudera)
- Installation – Pig, Hive, HBase, Cassandra etc
- Specifying the Hadoop Configuration
- Performing Initial HDFS Configuration
- Performing Initial YARN and MapReduce Configuration
- Hadoop Logging&Cluster Monitoring
5. Load Data and Run Application
- Ingesting Data from External Sources withFlume
- Ingesting Data from Relational Databaseswith Sqoop
- REST Interfaces
- Best Practices for Importing Data
6. Manage, Maintain, Monitor, and troubleshoot of cluster
- General System Monitoring
- Monitoring Hadoop Clusters
- Common Troubleshooting Hadoop Clusters
- Common Misconfigurations
- Managing Running Jobs
- Scheduling Hadoop Jobs
7. Upgrade, Rolling andBackup
- Cluster Upgrading
- Checking HDFS Status
- Adding and Removing Cluster Nodes
- Name Node Meta Data Backup
- Data Backup
- Distributed Copy
- Parallel Data Ingestion
8. Conclusion & FAQs
Samyak IT Solutions Pvt Ltd is an ISO 9001:2008 Certified Company and has international level acceptance for its certifications. Students from Samyak are given preference in placements as they have proper hands on job related knowledge already, that any industry needs these days.
NSDC certification is aimed at improving the employability of individuals and making them more skilled and productive. The certification is available in a wide range of fields, including healthcare, beauty and wellness, retail, hospitality, IT, and many others.
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