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Best Institutes for Big Data Analytics training in Kannur with Course Fees

List of 2+ Big Data Analytics training institutes located near to you in Kannur as on June 6, 2020. Get access to training curriculum, placement training, course fees, contact phone numbers and students reviews.



training institutes Login2 IT Solutions
Kannur - Kannur City
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training institutes IIHT KHARGHAR
Kannur - Kannur City
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Address: 26, 1st Floor, S.N. Park, Sector-3, Belpada Kannur-410210

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Big Data Analytics Training Institutes in Kannur - by Location

Yet5.com Provides complete list of best Big Data Analytics training institutes in Kannur and training centers with contact address, phone number, training reviews, course fees, job placement, course content, special offers and trainer profile information by area.




Learning Big Data Analytics course in Kannur - Benefits, Advantages & Placements.

We have identified the benefits of learning big-data-analytics course in Kannur.
Big Data Analytics training in Kannur is part of Bigdata training course class, Big Data is a term used for Data Sets, data processing, and application software.Big data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data.characteristics of big data are Volume, Velocity, Variety, Machine Learning, Digital Footprint. This gives Introduce to the Storage, Map Reduce, and Query Stack. business benefit from Big Data Establishing the business importance of Big Data, Addressing the challenge of extracting useful data, Integrating Big Data with traditional data.
This course has a revised syllabus which briefly explains the concepts of big data and analytics.
The city also known as Cannanore is in Kerala . The city has its administrative head quarters in Thiruvananthapuram the capital city of Kerala . the city is is famous for looms and lores because of the loom industries. The city gives special importance to education as the city has a lot of good universities and colleges like Indian Naval Academy in Ezhimala , Kannur University, Government College of Engineering, Kannur and many other institutions. There is a cyberpark in kannur wich has IT companies and hence the job opportunities are high. The city is a homely place and is feasible t live in. education cost is efficient and hene differs according to the course.
You have travel connectivity to big-data-analytics course educational training institutes in Kannur. The district has good roads connecting to Bangalore, Mangalore and cochin. The nearest airport from the city is in Calicut and Mangalore. The Kannur international airport is under construction. The kannur ailway station in the southern railway zone region has frequent trains connecting to almost all the metro cities in the southern region. The localities utilizes the auto Rickshaw, taxies and busses in the city to reach nook and corner of the areas in the city.




Big Data Analytics course Content / syllabus in kannur

Below is the Big Data Analytics course content in kannur used by the training institutes as part of the Big Data Analytics course training. The Big Data Analytics course syllabus covers basic to advanced level course contents which is used by most of Big Data Analytics training classes in kannur .


1.Overview of Big Data
This includes topics such as history of big data, its elements, career related knowledge, advantages, disadvantages and similar topics.

2. Using Big Data in Businesses
This module should focus on the application perspective of Big Data covering topics such as using big data in marketing, analytics, retail, hospitality, consumer good, defense etc.

3. Technologies for Handling Big Data
Big Data is primarily characterized by Hadoop. This module cover topics such as Introduction to Hadoop, functioning of Hadoop, Cloud computing (features, advantages, applications) etc

4. Understanding Hadoop Ecosystem
This includes learning about Hadoop and its ecosystem which includes HDFS, MapReduce, YARN, HBase, Hive, Pig, Sqoop, Zookeeper, Flume, Oozie etc.

5. Dig Deep to understand the fundamental of MapReduce and HBase
This module should cover the entire framework of MapReduce and uses of mapreduce.

6. Understanding Big Data Technology Foundations
This module covers the big data stack i.e. data source layer, ingestion layer, source layer, security layer, visualization layer, visualization approaches etc.

7. Databases and Data Warehouses
This module should cover all about databases, polygot persistence and their related introductory knowledge

8. Using Hadoop to store data
This includes an entire module of HDFS, HBase and their respective ways to store and manage data along with their commands.

9. Learn to Process Data using Map Reduce
This emphasizes on developing simple mapreduce framework and the concepts applied to it.

10. Testing and Debugging Map Reduce Applications
After the applications are developed, the next step is to test and debug it. This modules imparts this knowledge.

11. Learn Hadoop YARN Architechture
This module covers the background of YARN, advantages of YARN, working with YARN, backward compatibility with YARN, YARN Commands, log management etc.

12. Exploring Hive
This modules introduces you with all the necessary knowledge of Hive.

13. Exploring Pig
This modules introduces you with all the necessary knowledge of PIG.

14. Exploring Oozie
This modules introduces you with all the necessary knowledge of Oozie.

15. Learn NoSQL Data Management
This modules covers all about NoSQL including document databases, relationships, graph databases, schema less databases, CAP Theorem etc.

16. Integrating R and Hadoop and Understanding Hive in Detail
This module introduces you to RHadoop, ways to do text mining and related knowledge.
In this article, I’ve covered the complete syllabus of Big Data Technologies. This syllabus should give you a comprehensive overview of the topics that you should cover in your upcoming big data training. If you realize, that your training doesn’t have any of the mentioned module in the syllabus, I’d recommend you to get in touch with the course administrator and get this thing sorted.


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