Hadoop / Big Data Training

[vcex_heading style=”bottom-border-w-color” text=”About Bigdata/Hadoop Testing” tag=”h2″]

Big data is not a fad. We are just at the beginning of a revolution that will touch every business and every life on this planet — and data sets are large enough nowadays that traditional data processing technologies such as relational database management systems (RDBMS) or data centers are no longer enough.

What is big data testing? Well, most of us now know about big data. It refers to huge or big data which is difficult to manage by our traditional computing systems. These big data includes social media data, search engine data, stock exchange data and many more. Big data testing course will teach trainees, how to do testing of all these data through a platform called Hadoop. This is an open source software which processes huge data in various servers. This software can manage single server to various machines and can handle high level of errors.

Because of its usefulness, Hadoop is becoming a backbone for various industries and big data testing course is gaining popularity for the same.

Performance and functional testing are the two main parts of big data Hadoop testing. This testing involves data processing verification instead of testing various features of the product. In big data testing, verification of data is done using commodity cluster. This requires excellent testing skills as the processing procedure is quite fast. In big data testing, data quality also matters a lot. A tester should test the quality of data, as it is a part of database testing.

Hadoop or big data testing are mainly categorized into 3 steps:

Data Staging Validation

  • Data from all the sources are checked in order to ensure that correct data is going into system.
  • Comparison of system data and the data sent to Hadoop system is done
  • Verification is done to ensure that right data is extracted and loaded into suitable HDFS location

MapReduce Validation

  • This step works accurately and segregation rules are employed.
  • Validation of data is done after MapReduce step.

Output Validation Phase

  • This step checks whether the transformation rules are appropriately applied or not.
  • Validates the integrity of data and successful loading of data into the target system.
  • Checks final data with HDFS system for validating data corruption.

McKinsey predicts that by 2018 there will be a shortage of 1.5M data experts

If you want to learn what we mean by Big Data, then you should start here.

Why should you learn Hadoop?

  • Global Hadoop Market to Reach $84.6 Billion by 2021 – Allied Market Research.
  • Shortage of 1.4 -1.9 million Big Data Hadoop Analysts in the US alone by 2018–
  • Hadoop Testing Professionals in the US can get a salary of $132,000 – com.

So there’s never been a better time to learn some of the technologies that can handle Big Data.

[vcex_heading style=”bottom-border-w-color” text=”Hadoop/Big Data Testing Course” tag=”h2″]

Are you interested in Hadoop testing course? If yes, then you are on right page! Get software services teach Hadoop testing in such a way that anyone can learn concepts of Hadoop without any difficulty. Our teaching efforts cover all the technical details of Hadoop for making our students, masters of Hadoop. Quality training is a must for learning Hadoop, and that is what we do. We heartily welcomes analytical minds who are interested in learning big data. Our experienced professionals strive to convert a beginner into an expert of big data.

Our Hadoop testing course includes real-time projects, thus making you aware of technical challenges of Hadoop. After completion of Hadoop testing course, we provide big data testing certification to students, which adds value to their career.

It is believed that in the coming 3 years, almost half of the data will migrate to Hadoop. This will generate a high demand for big data professionals in future. Our Hadoop testing course plays a pivotal role in filling the gap between demand and supply of Hadoop professionals. Our big data trainees will get hands-on experience on different components like Pig, HDFS, Impala, MapReduce, Flume and Sqoop. Our professionals provide complete big data testing training which is a perfect blend of technology and analytics. This ensures bright future of our aspirants who want to get big data testing jobs and make a good start in big data.

There is no prerequisite for big data testing training anyone with a technical mind can take advantage of this course.

Hadoop is now deployed in most of the sectors. With time the possibility of complexities in Hadoop big data is expected. Hence there is a need of Hadoop testers who can support Hadoop architects and developers in their projects. Our big data testing training strives to render right skills to trainees, in order to open the door the opportunities as a Hadoop tester for them. Gain practical knowledge on our big data testing tools and explore this new skill under the guidance of our experienced faculties.

Let’s take a deep dive and achieve a good knowledge of Hadoop ecosystem.

Hope the above information is sufficient for you to think about doing big data testing course. Enrol for this course and open the doors for Hadoop testing jobs.

[vcex_heading style=”bottom-border-w-color” text=”Hadoop/Bigdata Training Syllabus” tag=”h3″]
[vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292348224{margin-left: 30px !important;}”]Introduction to Big Data and Hadoop. [/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292367808{margin-left: 30px !important;}”]Why we need Hadoop.[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292383191{margin-left: 30px !important;}”]Hadoop distributions.[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292399898{margin-left: 30px !important;}”]Technologies used for various components in Hadoop. [/vcex_list_item]
[vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292477591{margin-left: 30px !important;}”]Hadoop Installation[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292493183{margin-left: 30px !important;}”]Features of HDFS[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292509927{margin-left: 30px !important;}”]Pillars of Hadoop – HDFS, MapReduce, and YARN.[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292526371{margin-left: 30px !important;}”]Hadoop Architecture[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292544567{margin-left: 30px !important;}”]MapReduce[/vcex_list_item]
[vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292593102{margin-left: 30px !important;}”]MapReduce architecture [/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292606678{margin-left: 30px !important;}”]MapReduce example [/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292620111{margin-left: 30px !important;}”]Advantages of MapReduce [/vcex_list_item]
[vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292697101{margin-left: 30px !important;}”]Introduction to YARN [/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292710215{margin-left: 30px !important;}”]Difference between MRV1 & MRV2[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292725213{margin-left: 30px !important;}”]YARN Application workflow in MapReduce[/vcex_list_item]
[vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292769485{margin-left: 30px !important;}”]Introduction to Hive[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292786893{margin-left: 30px !important;}”]Hive Installation[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292800012{margin-left: 30px !important;}”]Hive Basics[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292812596{margin-left: 30px !important;}”]Primitive Datatypes[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292826165{margin-left: 30px !important;}”]Collections_Arrays_Maps[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292837828{margin-left: 30px !important;}”]Create Table[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292852116{margin-left: 30px !important;}”]Insert Into Table[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292867300{margin-left: 30px !important;}”]Alter Table[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292891398{margin-left: 30px !important;}”]HDFS CLI – Interacting with HDFS[/vcex_list_item]
[vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292970964{margin-left: 30px !important;}”]Built-in Functions[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510292985837{margin-left: 30px !important;}”]The Case-When statement, the Size function, the Cast function[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293001875{margin-left: 30px !important;}”]The Explode function[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293017373{margin-left: 30px !important;}”]Sub-Queries[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293041036{margin-left: 30px !important;}”]Views[/vcex_list_item]
[vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293116475{margin-left: 30px !important;}”]Partitioning[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293129092{margin-left: 30px !important;}”]Bucketing[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293140971{margin-left: 30px !important;}”]Windowing[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293155747{margin-left: 30px !important;}”]Windowing – Example[/vcex_list_item]
[vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510294508367{margin-left: 30px !important;}”]HQL Primer – Select Statements[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293222563{margin-left: 30px !important;}”]HQL Primer – Group By, Order By and Having[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293238683{margin-left: 30px !important;}”]More Group By Examples[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293258721{margin-left: 30px !important;}”]Order By[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293272795{margin-left: 30px !important;}”]Having[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293293419{margin-left: 30px !important;}”]HQL Primer – Joins[/vcex_list_item]
[vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293432443{margin-left: 30px !important;}”]Spark Installation[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293450346{margin-left: 30px !important;}”]APACHE SPARK (BigData Analytics) Introduction[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293467554{margin-left: 30px !important;}”]Why Spark when Hadoop is already there[/vcex_list_item]
[vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293564976{margin-left: 30px !important;}”]Difference between Hadoop vs Spark[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293582056{margin-left: 30px !important;}”]Spark Overview[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293600047{margin-left: 30px !important;}”]Using Hadoop through Spark[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293615297{margin-left: 30px !important;}”]Spark Features[/vcex_list_item]
[vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293744239{margin-left: 30px !important;}”]Spark ECO Systems[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293760254{margin-left: 30px !important;}”]Spark Architecture(Spark Core)[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293775296{margin-left: 30px !important;}”]Introduction to Scala[/vcex_list_item]
[vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293868758{margin-left: 30px !important;}”]Platforms and editors[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293926567{margin-left: 30px !important;}”]Running Spark on a Cluster[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510293945095{margin-left: 30px !important;}”]SparkSQL, DataFrames, and DataSets[/vcex_list_item]
[vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510294023482{margin-left: 30px !important;}”]Advanced Examples of Spark Programs[/vcex_list_item]
[vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510294122438{margin-left: 30px !important;}”]Machine Learning with MLLib[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510294140397{margin-left: 30px !important;}”]Introduction to Spark Streaming[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510294156901{margin-left: 30px !important;}”]Introduction to GraphX[/vcex_list_item]
[vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510294204172{margin-left: 30px !important;}”]Introduction to Hbase[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510294448069{margin-left: 30px !important;}”]Introduction to Sqoop[/vcex_list_item][vcex_list_item icon=”fa fa-book” color=”#81d742″ css=”.vc_custom_1510294239830{margin-left: 30px !important;}”]Introduction to OOzie[/vcex_list_item]
[vcex_heading style=”bottom-border-w-color” text=”Join Now for Free 7 Days Software Testing Sessions” tag=”h3″ text_align=”center” css=”.vc_custom_1487228325217{margin-top: 20px !important;margin-bottom: 20px !important;}”]