Master in Big Data Analytics Course Training in Delhi
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Upgrade Your Skill In Master in Big Data Analytics Course
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India's No-1 Master in Big Data Analytics Course Institute With Most Advanced Course Curriculum
Academic Partner - Hewlett Packard
What Is Master in Big Data Analytics Course & Why It Is The Most Demanding Skill Now a Days?
Big data is revolutionizing businesses and driving expansion throughout the global economy.
The U.S. Bureau of Labor Statistics (BLS) predicts data-related professions will grow by 12% by 2028, creating over 546,000 new jobs. Evermore, top companies require skilled data professionals to fill those emerging roles.
In a fast-growing field, candidates with both experience and advanced degrees are not easy to find. 81% of all data science and analytics job postings seek workers with at least 3 years of preceding work experience, and many of the highest paying roles require a relevant master’s degree.
Madrid Software Trainings’s Masters in big data analytics in Delhi course makes you skilled in tools and systems used by Big Data experts. It includes training on various messaging systems like Hadoop and Spark stack, Cassandra, HDFS, MapReduce, Talend, Apache Kafka, etc. The comprehensive curriculum has been designed by extensive research by our industry experienced professionals.
The course helps students to meet the escalating demand from employers by instructing the competencies that classify an analyst's ability to demonstrate the application of the knowledge, skills, and dispositions through behavior that is directly related to the organization's goals.
What you will learn?
Develop a core analytical expert skillset upon which you will be able to layer more specialized technical skillsets.
Build a relationship with industry leaders and peers for constant support.
Foresee and have a say in the future direction of data analytics.
Gain insight into Hadoop fundamentals
Understand various Hadoop concepts
You will be able to transform information into actionable insights for quick decision making.
New opportunities in this field –
Salaries for big data careers are increasing just as quickly as the demand for skilled experts. The compensation lying in the six-figure range and above market pay to compete in the talent war, according to research from site Robert Half Technology.
You can work as:
Big data engineer
Data architect
Data warehouse manager
Database manager
Business intelligence analyst
Data scientist
Data modeler
Hadoop developer and so on
Why learn from Madrid Software Trainings Institute?
Number 1 –Training institute in Delhi for the last 5 years.
5000+ students – We have trained more than 5000 students across India.
Certified instructors - Cloudera certified industry expert trainers.
Live Projects – We work on live-projects for a better understanding of Big Data analysis.
Industry recognition – Get an industry-accepted certificate that will boost your resume.
Placement Support – We provide 100% placement support.
Best program – We are providing India’s best masters in big data analytics training program.
Practical Training – We focus on providing practical training in our training programs.
Modes of teaching – We provide online and classroom training for Big data analytics training.
Our Master in Big Data Analytics Course Is Designed By Industry Experts That Gives The Candidate an Edge In The Market
Introduction To Big Data
What is Big Data
How Analyties is Used in Big Data
Case Python Concepts
Analyties Concepts of Python
Numpy Package
Introduction to Pandas
Data Manipulation using pandas
Data cleaning Techniques
Introduction to Hadoop
cluster setup (hadoop 1.X)
HDFC Concepts
Mapreduce Concepts
Mapreduce Data Types and Formats
cluster setup (hadoop 2.X)
HDFC High Availability and Federation
YARN (Yet Another Resource Negotiator)
Zookeeper
Pig
Hive
Hbase
Flume
Sqoop
Introduction to Apache Spark
Introduction to Programming in Scala
Using RDD'S to Create Application in Spark
Spark SQL
Job Profile And Salaries Of Master in Big Data Analytics
Upcoming Batches
Weekdays
11-Nov-2024
Weekend
09-Nov-2024
100% Classroom Training by Our Top Ranked Faculty
Course Curriculum Design by Industry Experts
Real Time Assignments Case Study & Projects
Got Better Salary Hike and Promotion
Industry recognized certificates
Mock tests and Mock interview
Dedicated placement coordinator assigned to every candidate
Why Choose Madrid Software Trainings
Live Project Based Training
Recorded Session After Every Class
Assignments & Assessments Test
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Job Placement In Big Data Analytics
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Master in Big Data Analytics Interview Q & A
1.What are the standard 4 Vs of Big data?
The four Vs of Big Data are –
Volume – It's the amount of data.
Variety – It is the various formats of data.
Velocity – It is the ever-rising speed at which the data is growing.
Veracity – It is the degree of precision of data available.
2.What is Hadoop?
Hadoop is an open-source framework for storing, processing, and analyzing complex unstructured data sets for deriving insights and intelligence.
3.Define commodity hardware.
Commodity Hardware refers to the minimal hardware resources needed to run the Apache Hadoop framework. Any hardware that supports Hadoop's least requirements is known as 'Commodity Hardware.'
4. In Hbase, tell about three primary tombstone markers used for deletion purposes.
There are three primary tombstone markers used for deletion in HBase. They are-
Family Delete Marker – To mark all the columns of a column family.
Version Delete Marker – To mark a single version of a single column.
Column Delete Marker – To mark all the versions of a single column.
5.What is the way of deploying Big data solutions?
One can deploy a Big Data solution in three steps:
Data Ingestion – This is the initial step in the operation of a Big Data solution. You begin by collecting data from multiple sources, including social media platforms, log files, business documents, and anything relevant to your business. Data can either be extracted through synchronized streaming or in consignment jobs.
Data Storage – Once the data is extracted, you must store the data in a database. It can be HDFS or HBase. While HDFS storage is excellent for chronological access, HBase is best for random read/write access.
Data Processing – The last step in the deployment of the solution is data processing. Typically, data processing is done via Spark, MapReduce, Flink, Hadoop, and Pig
6.What is Rack awareness?
Rack mindfulness is a calculation that recognizes and chooses DataNodes closer to the NameNode dependent on their rack data. It is applied to the NameNode to decide how data blocks and their copies will be put. During the establishment cycle, the default supposition will be that all hubs have a similar rack.
7.What are the configuration parameters in a MapReduce framework?
The configuration parameters in the MapReduce framework include:
The input format of data.
The output format of data.
The input and output locations of jobs in the distributed file system.
The JAR file.
The class containing the map function
The class containing the reduce function
8.Mention the crucial features of JobTracker.
It is a procedure that runs on a different node (not on a DataNode).
It communicates with the NameNode to recognize data location.
It tracks the implementation of MapReduce workloads.
It finds TaskTracker nodes based on the obtainable slots.
It finds the best TaskTracker nodes to execute explicit tasks on particular nodes.
9.What is indexing in HDFS?
HDFS files information blocks relying upon their sizes. Likewise, clarify that the finish of an information block focuses on where the following data blocks' arrangement is put away.
10.What are the three modes in which Hadoop can run?
Standalone mode: Hadoop's default mode uses a local file system for input and output operations. This mode is primarily used for debugging purposes, and it does not sustain the employ of HDFS. Further, there is no custom configuration required for mapred-site.xml, core-site.xml, and hdfs-site.xml files in this mode. This mode works much faster than other modes.
Pseudo-distributed mode: In this mode, you need configuration for all the 3 files mentioned above. In this case, all daemons are running on one node, and thus both Master and Slave nodes are the same.
Fully distributed mode: This is Hadoop's production phase (what Hadoop is known for), where data is used and distributed across several nodes on a Hadoop cluster. Separate nodes are allotted as Master and Slave.
FAQ
1. Who Should Do a Data Science Course?
Beginners and working professionals, both are eligible to do pg program in data science. To become a data scientist, you could earn a Bachelor's degree in Computer science, Social sciences, Physical sciences, and Statistics. You need to know programming languages like Python, Perl, C/C++, SQL, and Java.
2.What Are The Most Valuable Skill For a Data Science Professional ?
The most valuable skills for data science professionals are as follows:
Probability & Statistics
Multivariate Calculus & Linear Algebra
Programming, Packages, and Software
Data Wrangling
Database Management
Data Visualization
Machine Learning / Deep Learning
Cloud Computing
Microsoft Excel
DevOps
3. Is This Courses Useful For Non-Tt Professional
Any person with a structural thought process, good logical thinking skills, conviction towards learning new tools, and with a good business perspective can get into the field of data sciences. It’s not exceptional coders or highly knowledgeable people that are required.
4. What Is The Average salary Of a Data Scientist
The salary depends upon the company you are entering. The average data scientist’s salary is ₹698,412. As your experience and skills grow, your earnings rise dramatically as senior-level data scientists around more than ₹1,700,000 a year in India!
5. What Are The Top Algorithms That Every Data Science Professional Must Know
The top algorithms are:
Decision Tree
Logistic Regression
Linear Regression
SVM (Support Vector Machine) ...
Naive Bayes
KNN
K-Means Clustering
Random Forest
Dimensionality Reduction Algorithms
Neural Network
6. How Much Math In Statistics Is Used In Data Science
Math and Statistics for Data Science are essential because these disciples form the basic foundation of all the Machine Learning Algorithms. But, practical data science doesn't require very much math at all. It only requires skill in using the right tools. In statistics, you should know about probability distributions, statistical significance, hypothesis testing, and regression.
7. Which Programming Language Is Most Widely Used For Data Science
Python is the most popular and widely used data science programming language in the world today. It is an open-source, easy-to-use language that has been around. This general-purpose and vibrant language is innately object-oriented. It also ropes numerous paradigms, from functional to structured and procedural programming.
8.What Are The Top Companies In India To Work For After Completing Data Science Course
Many companies in India recruit Data Science professionals from entry-level to higher positions. Some of the top recruiters of Data Science and Big Data professionals in India for which you can work after completing the data science course are Equifax, Accenture, Amazon, Deloitte, LinkedIn, MuSigma, Flipkart, IBM, Citrix, Myntra, Juniper Network, etc
9. Do We Get Placement Support After Completing The Course
Yes, Madrid Software Trainings provide 100% placement support after the course and don’t throw at the deep end!
10.Do We Get Online Training Also In Data Science From Madrid Software Trainings
Yes, Madrid Software Trainings also provides online training for data science.
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India's No-1 Master in Big Data Analytics Course Institute With Most Advanced Course Curriculum
Academic Partner - Hewlett Packard
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