Instructor Led Live Online
Self Learning + Live Mentoring
In - Person Classroom Training
The entire training includes real-world projects and highly valuable case studies.
IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.
MODULE 1: DATA ANALYSIS FOUNDATION
• Data Analysis Introduction
• Data Preparation for Analysis
• Common Data Problems
• Various Tools for Data Analysis
• Evolution of Analytics domain
MODULE 2: CLASSIFICATION OF ANALYTICS
• Four types of the Analytics
• Descriptive Analytics
• Diagnostics Analytics
• Predictive Analytics
• Prescriptive Analytics
• Human Input in Various type of Analytics
MODULE 3: CRIP-DM Model
• Introduction to CRIP-DM Model
• Business Understanding
• Data Understanding
• Data Preparation
• Modeling, Evaluation, Deploying,Monitoring
MODULE 4: UNIVARIATE DATA ANALYSIS
• Summary statistics -Determines the value’s center and spread.
• Measure of Central Tendencies: Mean, Median and Mode
• Measures of Variability: Range, Interquartile range, Variance and Standard Deviation
• Frequency table -This shows how frequently various values occur.
• Charts -A visual representation of the distribution of values.
MODULE 5: DATA ANALYSIS WITH VISUAL CHARTS
• Line Chart
• Column/Bar Chart
• Waterfall Chart
• Tree Map Chart
• Box Plot
MODULE 6: BI-VARIATE DATA ANALYSIS
• Scatter Plots
• Regression Analysis
• Correlation Coefficients
MODULE 1: PYTHON BASICS
• Introduction of python
• Installation of Python and IDE
• Python Variables
• Python basic data types
• Number & Booleans, strings
• Arithmetic Operators
• Comparison Operators
• Assignment Operators
MODULE 2: PYTHON CONTROL STATEMENTS
• IF Conditional statement
• IF-ELSE
• NESTED IF
• Python Loops basics
• WHILE Statement
• FOR statements
• BREAK and CONTINUE statements
MODULE 3: PYTHON DATA STRUCTURES
• Basic data structure in python
• Basics of List
• List: Object, methods
• Tuple: Object, methods
• Sets: Object, methods
• Dictionary: Object, methods
MODULE 4: PYTHON FUNCTIONS
• Functions basics
• Function Parameter passing
• Lambda functions
• Map, reduce, filter functions
MODULE 1 : OVERVIEW OF STATISTICS
MODULE 2 : HARNESSING DATA
MODULE 3 : EXPLORATORY DATA ANALYSIS
MODULE 4 : HYPOTHESIS TESTING
MODULE 1: COMPARISION AND CORRELATION ANALYSIS
• Data comparison Introduction,
• Performing Comparison Analysis on Data
• Concept of Correlation
• Calculating Correlation with Excel
• Comparison vs Correlation
• Hands-on case study : Comparison Analysis
• Hands-on case study Correlation Analysis
MODULE 2: VARIANCE AND FREQUENCY ANALYSIS
• Variance Analysis Introduction
• Data Preparation for Variance Analysis
• Performing Variance and Frequency Analysis
• Business use cases for Variance Analysis
• Business use cases for Frequency Analysis
MODULE 3: RANKING ANALYSIS
• Introduction to Ranking Analysis
• Data Preparation for Ranking Analysis
• Performing Ranking Analysis with Excel
• Insights for Ranking Analysis
• Hands-on Case Study: Ranking Analysis
MODULE 4: BREAK EVEN ANALYSIS
• Concept of Breakeven Analysis
• Make or Buy Decision with Break Even
• Preparing Data for Breakeven Analysis
• Hands-on Case Study: Manufacturing
MODULE 5: PARETO (80/20 RULE) ANALSYSIS
• Pareto rule Introduction
• Preparation Data for Pareto Analysis,
• Performing Pareto Analysis on Data
• Insights on Optimizing Operations with Pareto Analysis
• Hands-on case study: Pareto Analysis
MODULE 6: Time Series and Trend Analysis
• Introduction to Time Series Data
• Preparing data for Time Series Analysis
• Types of Trends
• Trend Analysis of the Data with Excel
• Insights from Trend Analysis
MODULE 7: DATA ANALYSIS BUSINESS REPORTING
• Management Information System Introduction
• Various Data Reporting formats
• Creating Data Analysis reports as per the requirements
MODULE 1: DATA ANALYTICS FOUNDATION
• Business Analytics Overview
• Application of Business Analytics
• Benefits of Business Analytics
• Challenges
• Data Sources
• Data Reliability and Validity
MODULE 2: OPTIMIZATION MODELS
• Predictive Analytics with Low Uncertainty;Case Study
• Mathematical Modeling and Decision Modeling
• Product Pricing with Prescriptive Modeling
• Assignment 1 : KERC Inc, Optimum Manufacturing Quantity
MODULE 3: PREDICTIVE ANALYTICS WITH REGRESSION
• Mathematics behind Linear Regression
• Case Study : Sales Promotion Decision with Regression Analysis
• Hands on Regression Modeling in Excel
MODULE 4: DECISION MODELING
• Predictive Analytics with High Uncertainty
• Case Study-Monte Carlo Simulation
• Comparing Decisions in Uncertain Settings
• Trees for Decision Modeling
• Case Study : Supplier Decision Modeling - Kickathlon Sports Retailer
MODULE 1: MACHINE LEARNING INTRODUCTION
• What Is ML? ML Vs AI
• ML Workflow, Popular ML Algorithms
• Clustering, Classification And Regression
• Supervised Vs Unsupervised
MODULE 2: ML ALGO: LINEAR REGRESSSION
• Introduction to Linear Regression
• How it works: Regression and Best Fit Line
• Hands-on Linear Regression with ML Tool
MODULE 3: ML ALGO: LOGISTIC REGRESSION
• Introduction to Logistic Regression;
• Classification & Sigmoid Curve
• Hands-on Logistics Regression with ML Tool
MODULE 4: ML ALGO: KNN
• Introduction to KNN; Nearest Neighbor
• Regression with KNN
• Hands-on: KNN with ML Tool
MODULE 5: ML ALGO: K MEANS CLUSTERING
• Understanding Clustering (Unsupervised)
• Introduction to KMeans and How it works
• Hands-on: K Means Clustering
MODULE 6: ML ALGO: DECISION TREE
• Decision Tree and How it works
• Hands-on: Decision Tree with ML Tool
MODULE 7: ML ALGO: SUPPORT VECTOR MACHINE (SVM)
• Introduction to SVM
• How It Works: SVM Concept, Kernel Trick
• Hands-on: SVM with ML Tool
MODULE 8: ARTIFICIAL NEURAL NETWORK (ANN)
• Introduction to ANN, How It Works
• Back propagation, Gradient Descent
• Hands-on: ANN with ML Tool
MODULE 1: DATABASE INTRODUCTION
• DATABASE Overview
• Key concepts of database management
• CRUD Operations
• Relational Database Management System
• RDBMS vs No-SQL (Document DB)
MODULE 2: SQL BASICS
• Introduction to Databases
• Introduction to SQL
• SQL Commands
• MY SQL workbench installation
MODULE 3: DATA TYPES AND CONSTRAINTS
• Numeric, Character, date time data type
• Primary key, Foreign key, Not null
• Unique, Check, default, Auto increment
MODULE 4: DATABASES AND TABLES (MySQL)
• Create database
• Delete database
• Show and use databases
• Create table, Rename table
• Delete table, Delete table records
• Create new table from existing data types
• Insert into, Update records
• Alter table
MODULE 5: SQL JOINS
• Inner join, Outer Join
• Left join, Right Join
• Self Join, Cross join
• Windows Functions: Over, Partition, Rank
MODULE 6: SQL COMMANDS AND CLAUSES
• Select, Select distinct
• Aliases, Where clause
• Relational operators, Logical
• Between, Order by, In
• Like, Limit, null/not null, group by
• Having, Sub queries
MODULE 7: DOCUMENT DB/NO-SQL DB
• Introduction of Document DB
• Document DB vs SQL DB
• Popular Document DBs
• MongoDB basics
• Data format and Key methods
• MongoDB data management
MODULE 1: BIG DATA INTRODUCTION
• Big Data Overview
• Five Vs of Big Data
• What is Big Data and Hadoop
• Introduction to Hadoop
• Components of Hadoop Ecosystem
• Big Data Analytics Introduction
MODULE 2: HDFS AND MAP REDUCE
• HDFS – Big Data Storage
• Distributed Processing with Map Reduce
• Mapping and reducing stages concepts
• Key Terms: Output Format, Partitioners, Combiners, Shuffle, and Sort
MODULE 3: PYSPARK FOUNDATION
• PySpark Introduction
• Spark Configuration
• Resilient distributed datasets (RDD)
• Working with RDDs in PySpark
• Aggregating Data with Pair RDDs
MODULE 4: SPARK SQL and HADOOP HIVE
• Introducing Spark SQL
• Spark SQL vs Hadoop Hive
MODULE 1: TABLEAU FUNDAMENTALS
• Introduction to Business Intelligence & Introduction to Tableau
• Interface Tour, Data visualization: Pie chart, Column chart, Bar chart.
• Bar chart, Tree Map, Line Chart
• Area chart, Combination Charts, Map
• Dashboards creation, Quick Filters
• Create Table Calculations
• Create Calculated Fields
• Create Custom Hierarchies
MODULE 2: POWER-BI BASICS
• Power BI Introduction
• Basics Visualizations
• Dashboard Creation
• Basic Data Cleaning
• Basic DAX FUNCTION
MODULE 3: DATA TRANSFORMATION TECHNIQUES
• Exploring Query Editor
• Data Cleansing and Manipulation:
• Creating Our Initial Project File
• Connecting to Our Data Source
• Editing Rows
• Changing Data Types
• Replacing Values
MODULE 4: CONNECTING TO VARIOUS DATA SOURCES
• Connecting to a CSV File
• Connecting to a Webpage
• Extracting Characters
• Splitting and Merging Columns
• Creating Conditional Columns
• Creating Columns from Examples
• Create Data Model
The practice of analysing datasets to make judgments about the information they contain is known as data analytics. You can take raw data and use data analytical tools to find patterns and gain insightful conclusions from it.
Higher education must be nimble and responsive while certificates, degrees, and executive-level programmes must be sensitive to the needs of the workforce in order to fulfil the skyrocketing need for data scientists.
A degree is not often required for work as a data analyst, but it is crucial to get the right certification from an accredited college. The time it takes to learn the skills needed for success in data analytics might range from six weeks to two years. A 6-month training programme is a good way to learn about and get expertise in data analytics. The variability is accounted for by the several distinctive paths one could pursue to become a data analytics specialist.
A great profession in data analytics exists. To put it simply, there has never been a better time to work with data. Data is generated at a rate of 2.5 quintillion bytes per day, and this rate is only increasing. The price would change depending on the type of instruction you want. From 30,000 to 1,000,000 Indian rupees are charged for the Data Analytics Training in Vijayawada.
Since data analytics is in high demand, the career prospects for data analysts is highly promising. Before the end of 2020, IBM predicted, there would be an additional 364,000 employment!
Marketing Analyst
Business Intelligence Analyst
Data Analyst
Operations Analyst
Data Scientist
Quantitative Analyst
Data Analyst Consultant
Data Engineer
Project Manager
IT Systems Analyst
Additionally, advanced coding knowledge is not necessary for data analysts. They should have knowledge of data management software, data visualisation software, and analytics software instead. Data analysts need to have strong mathematics skills, just like the majority of data-related occupations.
Data analysis will rule the future. The improvement of data gathering, processing, and interpretation will lead to increased productivity. The world's most in-demand talents today include skilled data analysts. Even at the entry-level, Data Analysts earn enormous pay and fantastic benefits due to the high demand for their services and the small pool of qualified candidates.
The use of data-driven decision-making inside firms is supported by both business analysts and data analysts. In contradiction to data analysts, who often work more closely with the data itself, business analysts are frequently more proactive in addressing business challenges and offering recommendations. Both jobs are highly sought after and offer high salaries.
The national average salary for a Data Analyst in India is INR 6,00,000 per year. (Glassdoor)
The national average salary for a Data Analyst is USD 69,517 per year in the United States. (Glassdoor)
The national average salary for a Data Analyst in Australia is AUD 85,000 per year. (Glassdoor)
The national average salary for a Data Analyst in the UK is £36,535 per annum. (Glassdoor)
The national average salary for a Data Analyst in Canada is C$58,843 per year. (Payscale)
The national average salary for a Data Analyst in Germany is 46,328 EUR per annum. (Payscale)
The national average salary for a Data Analyst in Switzerland is CHF 95,626 per year. (Glassdoor)
The national average salary for a Data Analyst in UAE is AED 106,940 per year. (Payscale)
The national average salary for a Data Analyst in Saudi Arabia is SAR 95,960 per year. (Payscale.com)
The national average salary for a Data Analyst in South Africa is ZAR 286,090 per year. (Payscale.com)
The income growth that comes with a data analytics career is one of its profitable aspects. The pay for big data positions is rising in line with the demand for qualified data analysts. revealed that a data analyst in Vijayawada earns an average of 2,86,272 LPA!
The concept of data analytics has become more well-known in recent years as a result of the rise in data generation. Since the DataMites Data Analytics Courses in Vijayawada is intended to train candidates beginning at level 1, knowledge base of programming languages, databases, data structures, mathematics, and algorithms is simply helpful. However, there aren't any formal qualifications for the course.
If you want to pursue a career in the analytics industry, DataMites is the finest college for you. The primary mentors are knowledgeable and industry-oriented, and the course curriculum is skillfully laid out. With projects and internship opportunities, we provide practical training! If you wish to pursue a career in the analytics field, DataMites is the finest educational facility for you. The course content is well-developed, and the key mentors are knowledgeable and dedicated to the business. There are projects and internship possibilities for technical skills!
The most prestigious qualification in data analytics is the Certified Data Analyst designation, which attests to your competence in confidently evaluating data utilising a range of technologies. A certificate demonstrates your proficiency in handling data, conducting exploratory research, comprehending the fundamentals of analytics, and visualising, presenting, and elaborating on your findings. The DataMites Certified Data Analyst Course in Vijayawada is recognised by IABAC as well as the renowned Jain University.
Your greatest option in the field is the DataMites data analyst certification course in Vijayawada. Our data analytics course provides you with substantial proof that you are qualified to help companies, including well-known multinationals, interpret the data at hand. It is evidence that you are qualified to carry out the responsibilities of a particular employment role in conformance with industry standards, as opposed to a data analytics certificate.
There are several ways to get your first work in this in-demand industry, and you may locate data analytics careers in a variety of different businesses. DataMites is available to upskill you in becoming a data analytics professional, whether you're just starting out in the professional world or switching to a new field.
You may grow in your career and apply for the highest-paying opportunities with the help of data analytics training in Vijayawada that is specifically designed for the needs of the sector. With the surge in the use of analytics, having the capacity to work with data is no longer optional. The value of these skills will only increase as more sectors and businesses jump on board.
An international centre for data science called DataMitesTM has received approval from the International Association of Business Analytics Certifications (IABAC).
50,000+ hopefuls were trained
The three-phase learning method was carefully designed to deliver the best training possible.
Participate in relevant case studies and initiatives that are based in reality.
Get certified in JainX Data Analytics and the global IABAC.
Assistance with finding a job and an internship
For its data analytics training programmes, DataMites charges roughly 42,000 Indian rupees in Vijayawada.
For a data analyst with the requisite training in data analytics and the required level of skill on your part, the sky is the limit. DataMites offers data analytics certification courses in Vijayawada that last six months.
You has to go through the DataMites Certified Data Analyst Training in Vijayawada if you're contemplating about working in data analysis. Our curriculum will doubtless provide the understanding, talents, and credentials needed to start a career in data analysis from start to end.
Freshmen and students alike are welcome to enrol in the course. The best career path for you to take if you want to go from an IT to a business profile is to become a data analyst. You will be well-positioned to succeed in this sector if you have strong coding and IT skills. DataMites Training is open to individuals who do not work in information technology, including those in the human resources, banking, marketing, and sales sectors.
You can choose from a variety of flexible learning choices at DataMites, including data analytics training online in Vijayawada, self-study courses, and data analytics classroom training in Vijayawada. Each training session is specifically designed to help participants become experts in their chosen field.
It may seem like there is never enough time to learn everything there is to know about a data analytics career. Data analysts should be familiar with analytics, data visualisation, and data management tools but do not need to have sophisticated coding abilities.
The Certified Data Analyst curriculum, one of the best data analytics programmes offered by DataMites, has earned accreditation from the internationally recognised IABAC and JainX authority, whose credentials you would obtain after completing the course. The most effective method for beginning a career in data analytics is to obtain the DataMites Certified Data Analyst credential.
Applicants may participate in sessions provided by Datamites for a period of three months on any question or revision you desire to resolve with our Flexi-Pass for Data Analytics Certification Training.
That is not an issue for you. To schedule a class that fits your schedule, simply speak with your trainers about the issue. Every session of the online data analytics training in Vijayawada will be recorded and uploaded, allowing you to simply pick up the material you missed at your own pace and comfort. Certainly, it has never been this simple to understand data analytics!
Data analytics has grown to be a large field, so we want to train knowledgeable experts in the domain. DataMites has highly knowledgeable instructors who have hands-on expertise in the data sector. They will provide you with the greatest learning environment for your next significant endeavour.
When you register for the certification examinations and collect your participation certificate, bring your official photo identification, such as a passport or driver's licence.
Without a doubt, we'll give you a certificate of completion for your data analytics course in Vijayawada after it's through.
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The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -
The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.
No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.