Data Analytics
The process of analyzing data sets is known as data analytics (DA). It aids in the discovery of trends and will also assist in making judgments on the data they contain. Data analytics approaches are widely used in commercial enterprises.
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About Data Analytics
Organizations will be able to make better business judgments. Data analytics is a term that encompasses a wide range of applications. Business intelligence (BI), reporting, and online analytical processing are all included (OLAP). It also entails some areas of advanced analytics. Businesses may use data analytics to raise profits and productivity. It can optimize marketing movements. Customer service activities can also benefit from data analytics. It is possible to gain a competitive advantage by reacting quickly to emerging market trends. The goal of data analytics, on the other hand, is to boost corporate performance. Historical documents or fresh information can be used to examine the data. So all the new-age statistics and programs that can process large amounts of data can be used to bring helpful insights and plan better for the future and look for issues in the present setup. This is a simple meaning of Data Analytics for you.
What is the job prospect for a Data Analytics Course?
The financial rewards of switching to a data analysis career are greater. These are greater than the average IT professional's. Young students with computer skills, experience, and good coordination might choose big data analytics as a career option. It will enable them to earn bigger pay in a shorter time. A job in Data Analytics is advantageous if you are proficient in statistics and maths. It would improve your knowledge of applied algebraic, statistical, discrete mathematics, and other related topics, so data analytics is indeed the end-all solution. Data mining is a bonus advantage for every company that allows for practical judgments.It enables you to have a better standing than your competitors. From top to bottom, it streamlines decision-making layers in a variety of ways. It also coordinates regional efforts, with an increasing number of organizations relying on data professionals. You can gain the necessary abilities for the Data Analyst positions in big companies. It's simple to figure out how to employ popular analytic methods once you get professional training in Data Analysis.
Regardless of your current occupation, you can specialize over time and make use of the newfound skill. Data analytics is viewed as a critical occupation by 75% of professionals. They are unable to recruit personnel with the necessary abilities in 68 percent of cases. There is a strategy in the works to broaden the scope of professional opportunities in the future. As a result, the data analytics course is critical for current market preferences. Cost-effective applications are provided by data analytics and many industries are looking forward to making use of it. It improves decision-making capacity in a variety of industries, including manufacturing and healthcare. It also offers educational services, as well as distributors, media, and even real estate. Many industries are changing, and there are numerous employment opportunities for people who are trained in Data Analytic tools of the current century. These occupations are a good fit for the abilities and requirements. SevenMentor offers the best Data Analytics training in Kolkata and for all of these reasons we suggest you join it.
SevenMentor Institute for Data Analytics Course in Kolkata
The Best Data Analytics Training is provided by the SevenMentor Institute. SevenMentor can help you with big data and Data Science training in Kolkata. Data Analytics qualification is advantageous for learners as it will help them make use of the current job demand and they will be able to find work quickly in a multinational corporation. Everyone can afford our Data Analytics course price in Kolkata because of this our Data Analytic course is open to students from all financial backgrounds. Our primary strength at Data Analytics Training in Kolkata is our trainers. They are seasoned experts with over a decade of expertise and real-life working experience in Data Analysis and Big data processing. You will get knowledge in forecasting, it will also aid you in your decision-making and enable you to make great graphical data representations. Our instructors are subject matter experts that are well-versed in data analytics technologies. We have received real accolades of excellence for our Data Analytics Training. Our students may learn about technology arrangement decisions at Data Analytics Classes in Kolkata. SevenMentor provides students with in-depth knowledge, comprehension, and experience on the subject. We consider learners to be our duty and provide Data Analytics coaching in a simple yet effective manner. As a result, our students may be assured of their ability to achieve their professional objectives. We've set up a laboratory that meets industry standards and includes the most up-to-date applications, tools, and software. We have a full building with cutting-edge technology. SevenMentor has a Wi-Fi connection and modern classrooms with the most up-to-date training materials. We provide flexible batch scheduling at our Data Analytics Classes in Kolkata, with schedules running every day of the year. We believe in meeting the needs of both students and working professionals around the world. We've made batches available on weekday mornings, weekday evenings, and weekends. For example, our batches are accessible based on your requirements. Corporate Training is also available to you online. It will assist you in developing analytic and productive learning skills. Your mastery in data analytics, data visualization, and machine learning is shown through a Data Analytics Certification Course in Kolkata. It demonstrates your dedication and perseverance in the field of data analysis. You may use it to set yourself out from the competition in a crowded market. This certificate from the Best Data Analytics Course in Kolkata can help you stay motivated on your career path.
Online Classes
The Online Data Analytics classes in Kolkata will provide you with a wide overview of the many approaches that can be used to evaluate huge databases using data analytics. Students must be able to construct upgradeable systems for managing and analyzing massive volumes of data using data analysis techniques. The online course helps learners to analyze difficult data and build sophisticated prediction models using the machine learning approach and data visualization. People who wish to understand everything there is to know about Big Data technology should take the Online Data Analytics course in Kolkata. The YARN, HDFS, and MapReduce technologies, which have been the basis of Linux OS systems, will be covered in online Data Analytics Training. Students will learn how to control and analyze huge data sets stored in HDFS, and also how to migrate data from unorganized data systems, through the use of Scoop. Neural networks and SVM algorithms will be covered in our online Data Analysis Training in Kolkata. The curriculum is jam-packed with real-world case studies that will help students solve complicated business problems and increase income. As a result, you'll be able to enroll in India's top online data analytics course.
Course Eligibility
- Freshers
- BE/ Bsc Candidate
- Any Engineers
- Any Graduate
- Any Post-Graduate
- Working Professionals
Syllabus of Data Analytics
- 1. Installation Of Vmware
- 2. MYSQL Database
- 3. Core Java
- 1.1 Types of Variable
- 1.2 Types of Datatype
- 1.3 Types of Modifiers
- 1.4 Types of constructors
- 1.5 Introduction to OOPS concept
- 1.6 Types of OOPS concept
- 4. Advance Java
- 1.1 Introduction to Java Server Pages
- 1.2 Introduction to Servlet
- 1.3 Introduction to Java Database Connectivity
- 1.4 How to create Login Page
- 1.5 How to create Register Page
- 5. Bigdata
- 1.1 Introduction to Big Data
- 1.2 Characteristics of Big Data
- 1.3 Big data examples
- 6. Hadoop
- i) BigData Inroduction,Hadoop Introduction and HDFS Introduction
- 1.1. Hadoop Architecture
- 1.2. Installing Ubuntu with Java on VM Workstation 11
- 1.3. Hadoop Versioning and Configuration
- 1.4. Single Node Hadoop installation on Ubuntu
- 1.5. Multi Node Hadoop installation on Ubuntu
- 1.6. Hadoop commands
- Cluster architecture and block placement
- 1.8. Modes in Hadoop
- Local Mode
- Pseudo Distributed Mode
- Fully Distributed Mode
- 1.9. Hadoop components
- Master components(Name Node, Secondary Name Node, Job Tracker)
- Slave components(Job tracker, Task tracker)
- 1.10. Task Instance
- 1.11. Hadoop HDFS Commands
- 1.12. HDFS Access
- Java Approach
- ii) MapReduce Introduction
- 1.1 Understanding Map Reduce Framework
- 1.2 What is MapReduceBase?
- 1.3 Mapper Class and its Methods
- 1.4 What is Partitioner and types
- 1.5 Relationship between Input Splits and HDFS Blocks
- 1.6 MapReduce: Combiner & Partitioner
- 1.7 Hadoop specific Data types
- 1.8 Working on Unstructured Data Analytics
- 1.9 Types of Mappers and Reducers
- 1.10 WordCount Example
- 1.11 Developing Map-Reduce Program using Eclipse
- 1.12 Analysing dataset using Map-Reduce
- 11.13 Running Map-Reduce in Local Mode.
- 1.14 MapReduce Internals -1 (In Detail) :
- How MapReduce Works
- Anatomy of MapReduce Job (MR-1)
- Submission & Initialization of MapReduce Job (What Happen ?)
- Assigning & Execution of Tasks
- Monitoring & Progress of MapReduce Job
- Completion of Job
- Handling of MapReduce Job
- Task Failure
- TaskTracker Failure
- JobTracker Failure
- 1.15 Advanced Topic for MapReduce (Performance and Optimization) :
- Job Sceduling
- In Depth Shuffle and Sorting
- 1.16 Speculative Execution
- 1.17 Output Committers
- 1.18 JVM Reuse in MR1
- 1.19 Configuration and Performance Tuning
- 1.20 Advanced MapReduce Algorithm :
- 1.21 File Based Data Structure
- Sequence File
- MapFile
- 1.22 Default Sorting In MapReduce
- Data Filtering (Map-only jobs)
- Partial Sorting
- 1.23 Data Lookup Stratgies
- In MapFiles
- 1.24 Sorting Algorithm
- Total Sort (Globally Sorted Data)
- InputSampler
- Secondary Sort
- 1.25 MapReduce DataTypes and Formats :
- 1.26 Serialization In Hadoop
- 1.27 Hadoop Writable and Comparable
- 1.28 Hadoop RawComparator and Custom Writable
- 1.29 MapReduce Types and Formats
- 1.30 Understand Difference Between Block and InputSplit
- 1.31 Role of RecordReader
- 1.32 FileInputFormat
- 1.33 ComineFileInputFormat and Processing whole file Single Mapper
- 1.34 Each input File as a record
- 1.35 Text/KeyValue/NLine InputFormat
- 1.36 BinaryInput processing
- 1.37 MultipleInputs Format
- 1.38 DatabaseInput and Output
- 1.39 Text/Biinary/Multiple/Lazy OutputFormat MapReduce Types
- iii)TOOLS:
- 1.1 Apache Sqoop
- Sqoop Tutorial
- How does Sqoop Work
- Sqoop JDBCDriver and Connectors
- Sqoop Importing Data
- Various Options to Import Data
- Table Import
- Binary Data Import
- SpeedUp the Import
- Filtering Import
- Full DataBase Import Introduction to Sqoope
- 1.2 Apache Hive
- 1.2 Apache Hive
- What is Hive ?
- Architecture of Hive
- Hive Services
- Hive Clients
- How Hive Differs from Traditional RDBMS
- Introduction to HiveQL
- Data Types and File Formats in Hive
- File Encoding
- Common problems while working with Hive
- Introduction to HiveQL
- Managed and External Tables
- Understand Storage Formats
- Querying Data
- 1.3 Apache Pig :
- What is Pig ?
- Introduction to Pig Data Flow Engine
- Pig and MapReduce in Detail
- When should Pig Used ?
- Pig and Hadoop Cluster
- Pig Interpreter and MapReduce
- Pig Relations and Data Types
- PigLatin Example in Detail
- Debugging and Generating Example in Apache Pig
- 1.4 HBase:
- Fundamentals of HBase
- Usage Scenerio of HBase
- Use of HBase in Search Engine
- HBase DataModel
- Table and Row
- Column Family and Column Qualifier
- Cell and its Versioning
- Regions and Region Server
- HBase Designing Tables
- HBase Data Coordinates
- Versions and HBase Operation
- Get/Scan
- Put
- Delete
- 1.5 Apache Flume:
- Flume Architecture
- Installation of Flume
- Apache Flume Dataflow
- Apache Flume Environment
- Fetching Twitter Data
- 1.6 Apache Kafka:
- Introduction to Kafka
- Cluster Architecture
- Installation of kafka
- Work Flow
- Basic Operations
- Real time application(Twitter)
- 4)HADOOP ADMIN:
- Introduction to Big Data and Hadoop
- Types Of Data
- Characteristics Of Big Data
- Hadoop And Traditional Rdbms
- Hadoop Core Services
- Hadoop single node cluster(HADOOP-1.2.1)
- Tools installation for hadoop1x.
- Sqoop,Hive,Pig,Hbase,Zookeeper.
- Analyze the cluster using
- a)NameNode UI
- b)JobTracker UI
- SettingUp Replication Factor
- Hadoop Distributed File System:
- Introduction to Hadoop Distributed File System
- Goals of HDFS
- HDFS Architecture
- Design of HDFS
- Hadoop Storage Mechanism
- Measures of Capacity Execution
- HDFS Commands
- The MapReduce Framework:
- Understanding MapReduce
- The Map and Reduce Phase
- WordCount in MapReduce
- Running MapReduce Job
- WordCount in MapReduce
- Running MapReduce Job
- Hadoop single node Cluster
- Hadoop single node Cluster Setup :
- Hadoop single node cluster(HADOOP-2.7.3)
- Tools installation for hadoop2x
- Sqoop,Hive,Pig,Hbase,Zookeeper
- Hadoop single node Cluster Setup :
- Hadoop single node cluster(HADOOP-2.7.3)
- Tools installation for hadoop2x
- Sqoop,Hive,Pig,Hbase,Zookeeper.
- Yarn:
- Introduction to YARN
- Need for YARN
- YARN Architecture
- YARN Installation and Configuration
- Hadoop Multinode cluster setup:
- hadoop multinode cluster
- Checking HDFS Status
- Breaking the cluster
- Copying Data Between Clusters
- Adding and Removing Cluster Node
- Name Node Metadata Backup
- Cluster Upgrading
- Hadoop ecosystem:
- Sqoop
- Hive
- Pig
- HBase
- zookeeper
- >7. MONGODB
- 8. SCALA
- 1.1 Introduction to scala
- 1.2 Programming writing Modes i.e. Interactive Mode,Script Mode
- 1.3 Types of Variable
- 1.4 Types of Datatype
- 1.5 Function Declaration
- 1.6 OOPS concepts
- 9. APACHE SPARK
- 1.1 Introduction to Spark
- 1.2 Spark Installation
- 1.3 Spark Architecture
- 1.4 Spark SQL
- Dataframes: RDDs + Tables
- Dataframes and Spark SQL
- 1.5 Spark Streaming
- Introduction to streaming
- Implement stream processing in Spark using Dstreams
- Stateful transformations using sliding windows
- 1.6 Introduction to Machine Learning
- 1.7 Introduction to Graphx
- Hadoop ecosystem:
- Sqoop
- Hive
- Pig
- HBase
- zookeeper
- 10. TABLEAU
- 11. DATAIKU
- 12. Product Based Web Application Demo based on java(EcommerceApplication)
- 13. Data deduplication Project
- 14. PYTHON
- 1.Introduction to Python
- What is Python and history of Python?
- Unique features of Python
- Python-2 and Python-3 differences
- Install Python and Environment Setup
- First Python Program
- Python Identifiers, Keywords and Indentation
- Comments and document interlude in Python
- Command line arguments
- Getting User Input
- Python Data Types
- What are variables?
- Python Core objects and Functions
- Number and Maths
- Week 1 Assignments
- 2.List, Ranges & Tuples in Python
- Introduction
- Lists in Python
- More About Lists
- Understanding Iterators
- Generators , Comprehensions and Lambda Expressions
- Introduction
- Generators and Yield
- Next and Ranges
- Understanding and using Ranges
- More About Ranges
- Ordered Sets with tuples
- 3.Python Dictionaries and Sets
- Introduction to the section
- Python Dictionaries
- More on Dictionaries
- Sets
- Python Sets Examples
- 4. Python built in function
- Python user defined functions
- Python packages functions
- Defining and calling Function
- The anonymous Functions
- Loops and statement in Python
- Python Modules & Packages
- 5.Python Object Oriented
- Overview of OOP
- Creating Classes and Objects
- Accessing attributes
- Built-In Class Attributes
- Destroying Objects
- 6. Python Object Oriented
- Overview of OOP
- Creating Classes and Objects
- Accessing attributes
- Built-In Class Attributes
- Destroying Objects
- 7. Python Exceptions Handling
- What is Exception?
- Handling an exception
- try….except…else
- try-finally clause
- Argument of an Exception
- Python Standard Exceptions
- Raising an exceptions
- User-Defined Exceptions
- 8. Python Regular Expressions
- What are regular expressions?
- The match Function
- The search Function
- Matching vs searching
- Search and Replace
- Extended Regular Expressions
- Wildcard
- 9. Python Multithreaded Programming
- What is multithreading?
- Starting a New Thread
- The Threading Module
- Synchronizing Threads
- Multithreaded Priority Queue
- Python Spreadsheet Interfaces
- Python XML interfaces
- 10. Using Databases in Python
- Python MySQL Database Access
- Install the MySQLdb and other Packages
- Create Database Connection
- CREATE, INSERT, READ, UPDATE and DELETE Operation
- DML and DDL Oepration with Databases
- Performing Transactions
- Handling Database Errors
- Web Scraping in Python
- 11.Python For Data Analysis –
- Numpy:
- Introduction to numpy
- Creating arrays
- Using arrays and Scalars
- Indexing Arrays
- Array Transposition
- Universal Array Function
- Array Processing
- Arrary Input and Output
- 12. Pandas:
- What is pandas?
- Where it is used?
- Series in pandas
- Index objects
- Reindex
- Drop Entry
- Selecting Entries
- Data Alignment
- Rank and Sort
- Summary Statics
- Missing Data
- Index Heirarchy
- 13. Matplotlib: Python For Data Visualization
- 14. Welcome to the Data Visualiztion Section
- 15. Introduction to Matplotlib
- 16. Django Web Framework in Python
- 17. Introduction to Django and Full Stack Web Development
- 15. R Programming
- 1.1 Introduction to R
- 1.2 Installation of R
- 1.3 Types of Datatype
- 1.4 Types of Variables
- 1.5 Types of Operators
- 1.6 Types of Loops
- 1.7 Function Declaration
- 1.8 R Data Interface
- 1.9 R Charts and Graphs
- 1.10 R statistics
- 16) Advance Tool for Analysis
- 1.1 git
- 1.2 nmpy
- 1.3 scipy
- 1.4 github
- 1.5 matplotlib
- 1.6 Pandas
- 1.7 PyQT
- 1.8Theano
- 1.9 Tkinter
- 1.10 Scikit-learn
- 1.11 NPL
- 17. Algorithm
- 1.naive bayes
- 2.Linear Regression
- 3.K-nn
- 4.C-nn
Trainer Profile of Data Analytics
Our Trainers explains concepts in very basic and easy to understand language, so the students can learn in a very effective way. We provide students, complete freedom to explore the subject. We teach you concepts based on real-time examples. Our trainers help the candidates in completing their projects and even prepare them for interview questions and answers. Candidates can learn in our one to one coaching sessions and are free to ask any questions at any time.
- Certified Professionals with more than 8+ Years of Experience
- Trained more than 2000+ students in a year
- Strong Theoretical & Practical Knowledge in their domains
- Expert level Subject Knowledge and fully up-to-date on real-world industry applications
Data Analytics Exams & Certification
SevenMentor Certification is Accredited by all major Global Companies around the world. We provide after completion of the theoretical and practical sessions to fresher’s as well as corporate trainees.
Our certification at SevenMentor is accredited worldwide. It increases the value of your resume and you can attain leading job posts with the help of this certification in leading MNC’s of the world. The certification is only provided after successful completion of our training and practical based projects.
Proficiency After Training
- Learn the all aspects of Data Analytics
- proficient in HIVE, R, Scala, and SQL, or Structured Query Language
- Understand the ecosystem of Data Analytics
- Practicals on Pig Hive Hbase
- Practicals on commercial distributions
Key Features
Skill level
From Beginner to Expert
We are providing Training to the needs from Beginners level to Experts level.
Course Duration
12 weeks
Course will be 90 hrs to 110 hrs duration with real-time projects and covers both teaching and practical sessions.
Total Learner
2000+ Learners
We have already finished 100+ Batches with 100% course completion record.
Frequently Asked Questions
Batch Schedule
DATE | COURSE | TRAINING TYPE | BATCH | CITY | REGISTER |
---|---|---|---|---|---|
16/12/2024 |
Data Analytics |
Online | Regular Batch (Mon-Sat) | Kolkata | Book Now |
17/12/2024 |
Data Analytics |
Online | Regular Batch (Mon-Sat) | Kolkata | Book Now |
21/12/2024 |
Data Analytics |
Online | Weekend Batch (Sat-Sun) | Kolkata | Book Now |
21/12/2024 |
Data Analytics |
Online | Weekend Batch (Sat-Sun) | Kolkata | Book Now |
Students Reviews
SevenMentor is the best training institute for many different courses and this is a good feature. I will recommend everyone to get at least one training session at SevenMentor if you are in Kolkata.
- Sonali Khude
Wow, I am impressed with the Training for Data Analytics. They have such great trainers that it feels like a very friendly course at their institute. Thank you SevenMentor
- Dinesh Tawde
Thanks to the trainers and support staff at the SevenMentor. I did not just complete a valuable course but also received a nice placement in good company. This data analytics course has really made my life a success story.
- Ritu Jogdand
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Corporate Training
SevenMentor offers a team of professors with years of expertise teaching and working in the technology industry for Corporate Data Analytics Classes in Kolkata. The instructors are industry specialists with years of expertise in the field and a solid understanding of company development and technical applications. On such a regular basis, we provide IT, software, and repair, as well as server management courses and business development training to a variety of small and large businesses. For business owners interested in the Data Analytics course in Kolkata, SevenMentor gives customized training as well as on-the-job training in the above-mentioned domains. It's quick and effective training that will undoubtedly aid organizations in improving their employees' knowledge and abilities. We also organize collaborative sessions with a variety of businesses to encourage the transfer of information and skills across industries. For a variety of software-related lectures, several corporate clients have ranked us as the finest in the sector. The majority of companies have complimented us on providing the best corporate Data Analytics Training in Kolkata.
Our Placement Process
Eligibility Criteria
Placements Training
Interview Q & A
Resume Preparation
Aptitude Test
Mock Interviews
Scheduling Interviews
Job Placement
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