Data Analytics
Data analysis is the act of evaluating, cleaning, altering, and interpreting data to find relevant information, influence findings, and aid judgment. Data analysis includes numerous aspects and procedures, including a vast range of techniques that go by many names and are used in a variety of industries, scientific fields, and social sciences.
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About Data Analytics
Data Analytics task:
In today's corporate world, data analysis is critical since it allows companies to make more scientific decisions and function more effectively. The process of analyzing raw data to identify trends and react to inquiries is the definition of data analytics, which covers the field's enormous scope. This does, however, include several tactics and purposes. Aspects of the data analytics method can help with a variety of projects. By combining these features, a successful data analytics tool will give a clear view of where you are, where you have been, and where you should go. In brief, data analytics reveals hidden data insights to provide a clear picture and decision-making skills based on the data offered.
There is an increased demand for data science and Analytics roles in India, and therefore the remunerations have been increasing yearly. As more companies turn to Machine Learning, Big Data, and Artificial Intelligence, the need for data Analytics jobs is on the rise. The Data Science industry has increased to a very large extent and has surpassed many industries since 2012. As a result, switching to a data Analytics is a wise decision, as it yields considerably greater comparative returns. Transitioning from a marketing analytics position to a data Analytics role, for example, results in a compensation increase of 37 percent on average. Similarly, when workers go from digital analytics to data Analytics, they can expect a 31 percent wage increase on average. The compensation increase for someone moving from a data engineering function to a data Analytics one might be as much as 44 percent. Experts with more than 15 years of expertise might earn up to 1.8 crores each year. Similarly, the typical yearly wage increase for data Analytics experts is 20-30%, compared to 15-20% for professionals with other backgrounds. As you'll see, Data Analytics have a lot of potential, and the industry's future seems bright, so register in this Data Analytics Course in Ahmedabad with SevenMentor Institute.
SevenMentor’s Data Analytics course in Ahmedabad-
SevenMentor Institute has collaborated with worldwide groups to help students view themselves in a bigger picture. Experts in the area with years of experience lead the Data Analytics Classes in Ahmedabad. Memory arrays with Hadoop, Spark, and HDFS operations are covered in great depth. Apache Hadoop is used to retrieve information, which is then processed using Apache Spark. The topics of data preparation, retrieval of information, and empirical data analysis are all thoroughly explored. Data mining of structured (RDBMS) and disorganized (Big Data) data using Python and R programming is demonstrated using real-world scenarios. A session covers the fundamentals of Machine Learning and how to create Machine Learning Algorithms for Prediction Modeling with Linear Regression. Numerous mixed box techniques, such as Neural Network models and Rms, are presented in the best Data Analytics training in Ahmedabad, as well as the use of Data Visualization tools to convey results.
Since we accept both freshmen and working professionals, our Data Analytics Courses in Ahmedabad are geared to match a participant's objectives and level of expertise. Learners get in-depth subject knowledge as well as practical experience in performing to international standards. With assignments, Analytics reports, webinars, exercises, and live sessions, learners get a wonderful blend of soft and hard abilities that the profile demands. So our Data Analytics course in Ahmedabad does not only feel good but is also a very fulfilling way of learning new skills in Data Analysis.
The Data Analytics certificate of completion verifies your knowledge in data insights, deep learning, and visualization of data. SevenMentor's Data Analytics Certificate is proof of your effort and hard work. Set yourself apart from your peers and superiors with this qualification. This degree from Ahmedabad's best data analytics coaching institute can help you grow in your career. Our Data Analytics certificate course in Ahmedabad was developed in partnership with prominent IT firm experts by experienced lecturers and industry practitioners. This training can help you land a job with one of the best organizations. The Data Analytics certificate classes in Ahmedabad also contain real-world projects and case studies, both of which are quite beneficial in the business. Come, arrive, and enroll in the greatest Data Analytics certificate training in Ahmedabad and kickstart your career in the hottest area of the IT business.
What is covered in the Data Analytics Course?
You'll learn about Hadoop Distributed File System (HDFS), MapReduce, YARN, and the foundations of the Linux operating system in this data analytics course. This course will show you how to use Pig, Hive, Python, and Scala to process and analyze large data sets stored in HDFS. Learn how to utilize SQOOP to move data from RDBMS to Big Data sets. The Machine Learning Training with Python and R programming module introduces analytic methodologies for manipulating massive volumes of data and obtaining meaningful business insights. In this course, you'll learn how to use Python and R to do regression analysis and construct prediction models. Without a doubt, this is one of the best data analytics training courses in Ahmedabad.
Online Classes
The Online Data Analytics course in Ahmedabad gives you a broad understanding of the many methodologies that allow you to analyze massive datasets using data analytics. Learners will be able to use data analysis tools to build upgradeable solutions for handling and processing enormous amounts of data. Students learn how to assess complex data as well as construct advanced forecasting models using machine learning techniques and data visualization in this online course. The Online Data Analytics course is for people who want to learn everything there is to know about Big Data technologies. Online Data Analytics classes in Ahmedabad will cover the YARN, HDFS, and MapReduce concepts, which have been the underpinnings of Linux OS systems. By the use of Scoop, participants will learn how to handle and analyze large data sets stored in HDFS, as well as how to move data from disorganized data systems. Our online Data Analysis Training in Ahmedabad will also cover neural networks and SVM techniques. The program is packed with actual case examples that will assist students in solving complex business difficulties and increasing revenues. As a consequence, you get the opportunity to enroll in India's best 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
Beginner, Intermediate, Advance
We are providing Training to the needs from Beginners level to Experts level.
Course Duration
90 Hours
Course will be 90 hrs to 110 hrs duration with real-time projects and covers both teaching and practical sessions.
Total Learners
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) | Ahmedabad | Book Now |
17/12/2024 |
Data Analytics |
Online | Regular Batch (Mon-Sat) | Ahmedabad | Book Now |
14/12/2024 |
Data Analytics |
Online | Weekend Batch (Sat-Sun) | Ahmedabad | Book Now |
14/12/2024 |
Data Analytics |
Online | Weekend Batch (Sat-Sun) | Ahmedabad | Book Now |
Students Reviews
With great professors and classroom amenities, SevenMentor is Ahmedabad's best training facility. I've comprehended the major concepts from the Data Analysis course, and I've developed confidence in myself.
- Pranav Humane
SevenMentor, thank you for your thoughtful and adaptable instruction. I'm thrilled to have completed the Data Analytics course and have also been offered a great job with Sevenmentor. My professional career has gotten off to a great start.
- Love Shah
SevenMentor is one of the most prestigious IT schools in the world. I took their Data Analytics course and was happy with the information I obtained. I strongly encourage you to participate in this Data Analytics course in Ahmedabad. Thank you so much for everything.
- Abhi Garg
We covered key topics like RDBMS, Business BI, and Deep Learning in this course, making it one of the best classes for Data Analysis. If you're interested in the IT profession, I strongly advise you to take this course.
- Sakshi Humane
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Corporate Training
For the Corporate Data Analytics training in Ahmedabad, SevenMentor has a team of teachers with years of experience teaching and working in the technology business. The lecturers are industry experts with many years of operating experience and a thorough grasp of business growth and technological applications. We provide IT, software, and maintenance, server management courses, and business development training to a range of small and large enterprises on a daily basis. SevenMentor provides specific training as well as on-the-job training in the above-stated areas for business people interested in the Data Analytics course in Ahmedabad. It is a very short and efficient training that will certainly help businesses improve their employees' knowledge and talents. We also arrange collaborative sessions with a variety of companies to facilitate the exchange of knowledge and skills across industries. Many corporate clients have rated us as the best in the field for a range of software-related seminars. Most businesses have praised us for giving the best corporate Data Analytics training in Ahmedabad.
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