Big Data engineer Job profile

Big Data engineer Job profile

More and more companies are utilizing the power of Big Data for their business growth. Many companies are hiring right Big Data developers for analysis of data.

If you are Java developer with 5-6 years of strong programming experience then learning Big Data will be a good addition to your skills. You may find high paying job.

Required Skills & Experience

Following skills are in demand:

• 5-10 years of experience in development and deployment of Java applications
• Strong analytical skills and experience in such work
• Machine Learning software experience will be on highs preference
• Experienced with big data (i.e. Hadoop, Hive, Spark)

If you learn these skills you may get high paying jobs with perks.

People are getting jobs of 200 to 400k

Learn Big data at:

• Big Data and Hadoop Training - Online and class room
• Big Data tutorials

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Big Data Hadoop Training

Training in Big Data and Hadoop Technologies

Big Data is very high in demand in the job market, developers are learning Big Data and Hadoop for getting new jobs in the market.

These technologies top in demand and pay high salary to expert developers and data scientists.

Big Data offers top salary in the IT industry to right candidates. Candidates having right experience will get huge salary as compared to other developers in industry.

Following technologies is required to become expert Big Data developer:

• Java
• MySQL
• Hadoop
• HBase
• HDFS
• Yarn
• MapReduce
• Scoop
• Pyton
• Hive
• Impala
• Flume
• Apache Pig
• Apache Spark

These are the must technologies you should learn. Apart from this list there are 100s of more tools and utilities that you may have to learn.

Here are links to Big Data Hadoop Training and tutorials:

• Big Data and Hadoop Training - Online and class room
• What is Big Data?
• HBase Step-by-Step Tutorial
• Big Data - Tutorials of Big Data

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How popular is HBase?

HBase is very popular NoSQL Database on the top of Hadoop's HDFS. Hadoop uses its HDFS for management of data over cluster of nodes. Hadoop does not provides random access of data.

HBase works on the top of Hadoop's hdfs and add random access layer as NoSQL Database. It can handle unlimited data set. HBase is very popular as NoSQL database.

HBase is very popular although its popularity graph is less then MongoDB. Here is one of the comparison graph:

Developers are using HBase for managing Big Data environment.

You can learn HBase on devmanuals.com

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Job Description of Big Data Developer

Job Description of Big Data Developer

Developers applying for Big Data development position should learn major things of Big Data technologies.

Strong experience on development in

• Java projects 
• Core Java
• Spring framework
• EJB
• Webservices development

Big Data skills:

• Hadoop Ecosystem components (Horton works distribution)
• Pivotal Ecosystem components (HAWQ, Gemfire, Spring XD)
• Spark Framework
•  NoSQL database (HBase/ Cassandra/ MongoDB etc.)

Skills:

• Basic level understanding of Business Intelligence concepts
• Good analytical and critical reasoning ability
• Good communications skills

Responsibilities:

• Define technical designs (TDD) based on Detailed Functional Specifications (DFS)
• Ability to understand architecture and translating the architecture in design
• Coding; reviewing; testing and debugging
• Prepare and execute unit test cases
• Performance tuning and trouble shooting

Further reading:

• What is Big Data?
• Big Data - Tutorials of Big Data
• Big Data and Hadoop Training - Online and class room

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Big Data Technologies

Big Data Technologies

What are Big Data Technologies in 2017?

Here are the list of latest Big Data Technologies:

1. Hadoop -Distributed HDFS
2. Hbase - NoSQL database for Big Data
3. MapReduce
4. Hive
5. Pig
6. WibiData
7. Platfora
8. Various Storage technologies
9. SkyTree - for machine learning
10. Predictive analytics
11. Data virtualization
12. Data integration - Amazon Elastic MapReduce (EMR), Apache Hive, Apache Pig, Apache Spark, MapReduce, Couchbase, Hadoop, and MongoDB

Further reading:

• What is Big Data?
• Big Data - Tutorials of Big Data
• Big Data and Hadoop Training - Online and class room

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How to use Hadoop and NoSQL to process large datasets in Java?

How to use Hadoop and NoSQL to process large datasets in Java?

Requirement:
a) To process huge dataset of text with ratings (in text format)
b) store them in some NoSQL database
c) do some processing
d) Application should be fast
e) Fast analysis

How it it can be achieved?

In this case Apache Mahout can be used.

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Big Data Analytics

Big Data Analytics

Big Data Analytics is another stream of Big Data which focuses on the analysis of data stored in Big Data system and generation of meaning full reports for business decision making.

Big Data Analytics involves the processing and analysis of data and then generation of reports in various format. Mostly PDF of web based dashboard is used for reporting.

Apache Spark is one of the mos used technology for Big Data Analytics. Apache Spark is very fast and is used for real-time analysis of data.

Here is list of Top 10 Big Data Analytics Tools.

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Hadoop

Hadoop

What is Hadoop?

Hadoop is Java based framework and software system which can be installed in thousands of servers to store all the types of data.

Hadoop is open source and its main Big Data handling system. Hadoop is developed at Apache Software Foundation. Hadoop consists of many modules, all the modules works together to provide a system for storage and processing of data in distributed computing environment.

Hadoop cluster automatically handles hardware failure and there is no data loss or downtime in such cases.

Hadoop is very robust system for Big Data which can handle data of any size. Big companies like Twitter, Amazon, Facbook, Yahoo and Google are using Hadoop for handling such a huge quantity of data.

Hadoop is using the distributed file system which is know as Hadoop Distributed File System (HDFS).

The Apache Hadoop composed of the following modules:

1. Hadoop Common 
2. Hadoop Distributed File System (HDFS) 
3. Hadoop YARN
4. Hadoop MapReduce

Further reading:

• What is Big Data?
• Big Data - Tutorials of Big Data
• Big Data and Hadoop Training - Online and class room

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Big Data

Big Data

Big Data is buzzword these days, everyone is talking about Big Data online and offline. Companies are looking for Big Data experts, developers are joining training courses to learn Big Data.  So, much talking about Big Data. So... What really is Big Data?

What is Big Data?

Big Data is here to solve problem of huge data. Huge data means several TB to Petabyte, Exabyte, Zettabyte, or a Yottabyte of data. Such huge data can't be managed by traditional database management system.

So, Big Data technologies was developed to save these data very fast. Analyze such huge set of data very fast.

Benefits of Big Data

The ultimate goal is to manage such data and analyze it to get meaning full report. After analyzing data it is used for business improvements or research work.

Further reading:

• What is Big Data?
• Big Data - Tutorials of Big Data
• Big Data and Hadoop Training - Online and class room

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Introduction to HBase

What is HBase?

HBase is non-relational database for Big Data environment which runs in Hadoop HDFS.

• HBase saves data in HDFS.
• HBase is open source
• HBase is non-relational
• Hbase can handle unlimited data
• HBase is fast
• Can be used for real time data analytics

Check complete introduction and tutorials of HBase.

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