Data Analytics
Data analytics is defined as the science of studying raw data to draw inferences about that data. Many data analytics approaches and procedures have been mechanized into mechanical processes and algorithms that deal with raw data and are intended for human consumption.
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About Data Analytics
Data analytics procedures and methods have converted into a digital process and software based algorithms can operate on raw data more effectively. As a result, data analytics is a broad phrase that incorporates a wide range of data analysis techniques. Data analytics techniques may be used to any sort of data to get the knowledge that can be utilized to improve things. Trends and metrics that might otherwise be lost in a sea of data can be discovered using data analytics techniques. This data may then be utilized to improve a company's or system's overall efficiency by optimizing procedures.
Types of Data Analytics
Descriptive analytics: This outlines what occurred throughout a certain period. Is it true that the number of views has increased? Are this month's sales better than earlier months'?
Diagnostic analytics: Diagnostic analytics is more concerned with why something occurred. Such a scenario requires more distinguished information as well as some amount of speculation. Has the weather had an impact on beer sales? Has the most recent marketing effort influenced sales?
Predictive analytics: Predictive analytics is focused on what would be anticipated to occur shortly. When was the last time we experienced a very warm summer? This year, how many weather models anticipate a warm climate?
Normative analytics: This is when data is used to propose a course of action. If the probability of a warm summer is more than 58 percent as shown by the average of these five weather predictions, must we add a late shift to the brewery and rent an extra tank to improve output as beer demand rises.
Importance and uses of Data Analytics
Data analytics is a crucial part of understanding large sets of data and information within a human context. Companies cut operational charges by developing efficient ways of conducting business and access large volumes of customer information by incorporating Data Analytics into their business program. Data analytics may also be used to assist a firm make better business decisions and assess consumer patterns and satisfaction, which can lead to the development of fresh superior products and solutions. Data analytics can do a lot more than just identifying production problems. Data analytics is used by game firms to create incentive schedules for players that keep a lot of them engaged in the game. Most of the same data analytics are used by content producers to keep you clicking, viewing, or reorganizing material to obtain another look or click. Overall the use of Data Analytics in an extremely digitized world has become one of the most important things for the IT sector and this has resulted in an increased number of high pay jobs for Data Analysts in India.
SevenMentor Data Analytics Course
The Basic module consists of five courses in which we tackle the basics of Data Science, Statistics, Code, SQL Programming, and some domain-specific expertise. These courses provide the groundwork for us to sail through the rest of the adventure with as little difficulty as possible.
Data Analysis approaches is the second session in our Data Analytics course in Bangalore. The methodology section will teach us the core data science and analytics methodologies that can help you tackle any challenge.
Moving on to the next section of the Data Analytics course, the Domain Exposure module will give a window into real-world problems from various domains and explain how to tackle them using Data Science and Analytics methods.
One of the major topics covered in this SevenMentor Data Science and Business Analytics course is data visualization and insights. This module will assist you in presenting data in the best possible way for easy intake and rapid insight extraction in Tableau and Power BI.
Through the Data Analytics course in Bangalore, you get to conduct hands-on practical projects with a real-time project under the direction of industry professionals, from teaching you Data Science to exposing you to Data Analytics and everything in between. SevenMentor Institute will award you an industry-accredited certification in Data Analytics if you complete the assignment successfully.
Best Data Analytics Course in Bangalore
SevenMentor Institute's dedication reflects the time and effort they put in for each student to give a unique learning experience for everybody. The instructors have relevant expertise in a variety of industries and are certified in the field of data analytics by Google and IBM. When the mix of principles and applications is aligned with market needs, the learning experience becomes one-of-a-kind. All of our instructors not only deliver excellent instruction but also ensure that the correct mix of knowledge and experience is maintained. Every student's requirement for a distinct course is unique, which sets us apart from the competition. SevenMentor has an advantage over any other school because of our excellent quality and rigorous adherence. We have more than 500 students that have completed the Data Analytics courses by our best-in-class training module.
Spreadsheet, Advanced Excel, Tableau, SQL, Power BI, Basics of R and Python are all covered in SevenMentor's Data Analytics Course in Bangalore. Aside from theory sessions, students are given hands-on exercises and projects to help them apply what they've learned. Learning is never a barrier; it is always an opportunity to gain experience. Our Bangalore classroom activities are a good illustration of practical and fun learning experiences that students receive. SevenMentor also gives you the option of selecting from a variety of batches as per your need. SevenMentor is therefore the top Data Analyst course provider in Bangalore, making Data Science learning simple and distinctive with all of the creative techniques.
Certification and Job Placement
In conjunction with the most famous firms in the IT sector, the top-rated Data Science and Analytics institute in Bangalore offers a Data Analytics Certificate. Our comprehensive Syllabus will help you develop into a highly trained professional and earn a position at one of the world's most prestigious businesses. The SevenMentor’s Data Analytics certification will walk you through the process of creating a professional CV, conducting practice interviews to increase your confidence, and preparing you to ace your professional interviews.
We will also help you get interviews at top companies in India through our in-house placement scheme. We have a distinguished track record as we placed more than 200 students in various roles of Data Analysts in major companies around India. So Join the most helpful training for the Data Analyst course and get a 100% placement guarantee in top Data Analyst profiles/jobs.
Online Classes
SevenMentor also provides online Data Data Analytics Training in Bangalore, which enables you to master Data Analyst development skills from the convenience of your own home. The Online program from SevenMentor stands out from the competitors by offering customized training sessions and a focus on students' learning capacities. The Online Data Analytics Course in Bangalore offered by SevenMentor comprises pre-recorded videos as well as live sessions. You may complete the pre-recorded videos at your own pace, providing you with more flexibility in your study. The interactive sessions are for conversations and individualized training, giving students the chance to ask our experienced trainers questions and get answers. Our teachers offer test sessions, and the hands-on method is supplemented by monitoring of work by our trainers, ensuring that you have real application knowledge. Online Data Analytics Classes in Bangalore also ensure that you have practical implementation knowledge even though our instructors offer test sessions, as well as the hands-on method, which is supplemented by monitoring of work by our lecturers. Overall, our Online Data Analysis Training is quite good at giving students the information they need. Our Online Course for Data Analysis in Bangalore additionally comes with a genuine and industry-recognized certification As a result, the certified Online Data Analyst Training in Bangalore at SevenMentor is the greatest way to acquire the finest learning opportunity and boost your chances of a successful career 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 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 Learners
2000+ Learners
We have already finished 100+ Batches with 100% course completion record.
Frequently Asked Questions
What is the most efficient method of registering for the Data Analysts Training (online or offline)?
Batch Schedule
DATE | COURSE | TRAINING TYPE | BATCH | CITY | REGISTER |
---|---|---|---|---|---|
23/12/2024 |
Data Analytics |
Online | Regular Batch (Mon-Sat) | Bangalore | Book Now |
24/12/2024 |
Data Analytics |
Online | Regular Batch (Mon-Sat) | Bangalore | Book Now |
28/12/2024 |
Data Analytics |
Online | Weekend Batch (Sat-Sun) | Bangalore | Book Now |
28/12/2024 |
Data Analytics |
Online | Weekend Batch (Sat-Sun) | Bangalore | Book Now |
Students Reviews
SevenMentors is Bangalore's leading IT and software training provider. They have the greatest professors in the world, and I am glad for the opportunity to complete my Data Analyst Course with them.
- Amol Tapkir
Personnel from our organization had taken part in SevenMentor's Corporate Training program. Their entire experience was amazing, and they gained many new skills such as SQL database administration, R-based data and statistics, and so on. Thank you very much for the impromptu training session.
- Jignesh Yadav
I am happy for the chance to work with SevenMentor for Data Analyst Training. They have the best instructors and the most comprehensive learning materials. Any course in the field of information technology is usually recommended to be undertaken at SevenMentor.
- Anjali Memane
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Corporate Training
SevenMentor also provides Corporate Data Analyst Training in Bangalore for working professionals. Our Bangalore-based Corporate Data Analyst Courses are taught by a team of 50 expert professors from around India. We provide IT and business development training to a variety of small and large businesses regularly. We provide software and hardware maintenance, server maintenance courses, and client database administration courses to our clients in addition to Core Data Analyst Training. The lecturers are industry experts with substantial operating experience and a thorough grasp of business development and the application of technology in business improvements. We provide our customers with unique Corporate offerings, as well as collaborative sessions for knowledge sharing across enterprises. Unless you're a new company or a venture, please contact us about our Corporate Data Analyst Classes in Bangalore, where the best trainers in the field can teach your personnel the most effective Data Analysis methods.
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Eligibility Criteria
Placements Training
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Aptitude Test
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