Data Analytics
Data Analytics is described as the science of analyzing raw data in order to conclude it before presenting. A number of data analytics approaches and procedures have been automated into mechanical processes and algorithms that deal with original data and are intended for usage.
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About Data Analytics
Techniques and processes for data analytics have been changed to digitalization and application algorithms may now function more efficiently on raw data. Due to this, data analytics has become a broad term that refers to a variety of data analysis approaches. Any type of data may be analyzed using data analytics techniques to obtain information that can be used to improve things. Trends and metrics that would otherwise be lost in a torrent of data can be discovered using data analytics techniques. By improving operations, this data may be used to increase an industry's system effectiveness. Interpreting vast volumes of data and information in a human context requires data analytics. Companies may save operating costs by building efficient business processes and get access to massive amounts of consumer data by implementing Data Analytics into their company strategy. Data analytics can also be used to help a company make informed business decisions and measure customer trends and happiness, which can lead to the creation of new, better goods and services. Data analytics may be used for much more than merely detecting manufacturing problems. Game companies employ data analytics to develop reward programs for gamers that keep them interested in the game. Content producers utilize many of the same data analytics to keep you clicking, viewing, or restructuring stuff in order to get a new look or click. Overall in an increasingly digitized world, data analytics has become one of the most significant aspects of the IT sector, resulting in a surge in the number of high-paying Data Analytics positions in India. Thus Data Analytics is a very important aspect of the process of development, design and functioning of any software business process. It is used to gain valuable insights into the performance of a company, product, or employee and analyze the weak points in our system by the use of large amounts of data and statistical methods. As of 2021 the Data Analyst, Data Science and Machine Learning jobs are on the rise and their demand is tremendous in every field from supermarket sales to Software distribution. So come and make use of an opportunity that is available for the Data Analyst and Statistician profiles in India and abroad by joining the best Data Analyst course in Indore.
SevenMentor’s Best Data Analytics Course in Indore
SevenMentor Institute's passion is seen in the time and effort they devote to each student to provide a one-of-a-kind learning experience for everybody. The lecturers are Amazon, Microsoft and Google certified in the field of data analytics and have significant experience in many businesses. Your learning experience becomes better when the blend of principles and applications is aligned with market demands. Not only do all of our teachers provide outstanding education, but they also guarantee that the right blend of expertise and experience is maintained. Each student's needs for a certain course are different, which distinguishes us from the competitors. Because according to our great quality and strict adherence, SevenMentor has an edge over any other institution. Its best-in-class training module has helped more than 500 students complete a Data Analytics course. Data visualization and insights are one of the primary topics addressed in this Data Science and Business Analytics course. The classes will help you show data in Tableau and Power BI in the best possible manner for easy ingestion and speedy insight retrieval. From educating you about Data Science to exposing you to Data Analytics and everything in between, the Data Analytics course in Indore allows you to just do hands-on practical projects with a serious project under the supervision of industry specialists. If you finish the assignment satisfactorily, SevenMentor Institute will grant you an industry-recognized certification in Data Analytics. All these features of our Data Analytics Training in Indore will help you gain the best learning experience and help you become the most educated Data Analytics Expert in the IT industry.
Benefits of Data Analytics Course in Indore
The Fundamental module is made up of five courses that cover the fundamentals of Computer Science, Mathematics, Code, SQL Scripting and some copyright knowledge. The courses lay the foundation for us to sail through the rest of the experience as smoothly as possible. The technique portion will teach us the fundamental data science and analytics approaches that can assist you in solving any problem. The Domain Exposure module, which is the next element of the Data Analytics course, would provide a glimpse into real-world challenges from diverse domains and teach how to solve them using Data Science and Analytics approaches. In SevenMentor's Data Analytics Course in Indore, you'll learn about spreadsheets, advanced Powerpoint, Tableau, Sybase, Power BI, and the fundamentals of R and Python. Students are provided hands-on activities and assignments in addition to theoretical sessions to help them apply what they've learned. Learning is never a hindrance; it is always an opportunity for growth. Our Indore classroom activities are an excellent example of students' practicality and provide enjoyable learning experiences. SevenMentor additionally allows you to choose from a range of batches according to your requirements. As a result, SevenMentor is the best Data Analyst course provider in Indore, making Data Science learning simple and unique through a variety of innovative ways.
Certification for Data Analytics course in Indore
Our top-rated Data Analytics Course in Indore provides a Data Analytics Certification in collaboration with some of the most well-known IT organizations. Our syllabus will assist you in becoming a highly trained professional and obtaining employment with one of the world's most prominent companies. The Data Analytics certification from SevenMentor will guide you through the process of establishing a professional CV, practicing interviews to build confidence, and preparing for professional interviews.
Through our in-house placement plan, we will also assist you in getting interviews at leading organizations in India. We have a proven track record, having placed over 200 students in various Data Analyst jobs in prominent businesses throughout India.
Online Classes
SevenMentor also offers online Data Analytics Training in Indore, so you can learn how to develop Data Analyst abilities from the home. SevenMentor's Online program distinguishes itself from the competition by providing personalized training courses and an emphasis on students' learning abilities. SevenMentor's Online Data Analytics Classes in Indore includes both recorded and live classes. You may go at your own pace while watching the pre-recorded lectures, giving you more learning options. Participants may ask our professional trainer questions and obtain answers during the interactive sessions, which are designed for dialogues and personalized instruction. Our instructors provide exam workshops, and the hands-on technique is supported by our trainers' monitoring of work to ensure that you have real-world application expertise. The trainers give exam sessions as well as the hands-on technique, which is supported by our instructors checking your performance. Online Data Analytics Classes in Indore also ensure that you have actual application expertise. Ultimately, our Online Data Analysis Course gives students the information they require. In addition, our Online Data Analysis Course in Indore comes with legitimate and industry-recognized certifications. As a consequence, SevenMentor's accredited Online Data Analyst Certification Training in Indore is the best approach to get the best learning experience and increase your chances of a successful profession while being at home.
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 Begianners 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 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) | Indore | Book Now |
17/12/2024 |
Data Analytics |
Online | Regular Batch (Mon-Sat) | Indore | Book Now |
14/12/2024 |
Data Analytics |
Online | Weekend Batch (Sat-Sun) | Indore | Book Now |
14/12/2024 |
Data Analytics |
Online | Weekend Batch (Sat-Sun) | Indore | Book Now |
Students Reviews
Indore's leading IT and software consulting firm is SevenMentors. They have some of the best lecturers on the market, and I am grateful for the chance to finish my Data Analyst Course with their institute.
- Rupali Thorve
SevenMentor's Corporate Training program has been used by employees from our company. The overall experience was incredible, and students learned a variety of new skills, including SQL database administration, R-based data and analytics, and more. Thank you for the last-minute training program.
- Tanuja Desai
I am delighted to have the opportunity to collaborate with SevenMentor on Data Analyst Training. They have the top teachers and the most extensive learning resources. SevenMentor is often suggested for any course in the subject of information technology.
- Ketaki Salunke
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Corporate Training
Working professionals can also benefit from SevenMentor's Corporate Data Analyst Training in Indore. Our team of 50 qualified instructors from throughout India teach our Indore-based Corporate Data Analyst Training in Indore. Every month, we deliver IT and business development training to a wide range of small and large enterprises. In addition to Core Data Analyst Course, we offer software/hardware administration, server management training, and client data management courses to our clients. The instructors are industry specialists with extensive operational experience and a solid understanding of company growth and the use of technology to benefit businesses. We provide our customers one-of-a-kind Corporate services as well as collaborative sessions for cross-company knowledge transfer. Please feel free to contact us all about our Corporate Data Analyst Course in Indore, in which the greatest trainers in the business can educate your staff on the most efficient Data Analysis methodologies. Unless you're a new firm or a venture, please feel free to contact us about our Corporate Data Analyst Classes in Indore.
Our Placement Process
Eligibility Criteria
Placements Training
Interview Q & A
Resume Preparation
Aptitude Test
Mock Interviews
Scheduling Interviews
Job Placement
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