CERTIFIED DATA ANALYST TRAINING COURSE

MODULE 1: DATA ANALYSIS FOUNDATION

• Data Analysis Introduction
• Data Preparation for Analysis
• Common Data Problems
• Classification of Analytics
• Various Tools for Data Analysis

MODULE 2: 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
• Hands-on Case Study: Trend 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: VARIANCE AND FREQUENCY ANALYSIS

• Concept of Variability and Variance
• Data Preparation for Variance Analysis
• Business use cases for Variance and
   Frequency Analysis
• Performing Variance and Frequency
   Analysis
• Hands-on case study 1: Variance Analysis
• Hands-on case study 2: Frequency Analysis

MODULE 1: DATA SCIENCE ESSENTIALS

• Introduction to Data Science
• Data Science Terminologies
• Classifications of Analytics
• Data Science Project workflow

MODULE 2: DATA ENGINEERING FOUNDATION

• Introduction to Data Engineering
• Data engineering importance
• Ecosystems of data engineering tools
• Core concepts of data engineering

MODULE 3: PYTHON FOR DATA ANALYSIS

• Introduction to Python
• Python Data Types, Operators
• Flow Control statements, Functions
• Structured vs Unstructured Data
• Python Numpy package introduction
• Array Data Structures in Numpy
• Array operations and methods
• Python Pandas package introduction
• Data Structures : Series and DataFrame
• Pandas DataFrame key methods

MODULE 4: VISUALIZATION WITH PYTHON

• Visualization Packages (Matplotlib)
• Components Of A Plot, Sub-Plots
• Basic Plots: Line, Bar, Pie, Scatter
• Advanced Python Data Visualizations

MODULE 5: STATISTICS

• Descriptive And Inferential statistics
• Types Of Data, Sampling types
• Measures of Central Tendencies
• Data Variability: Standard Deviation
• Z-Score, Outliers, Normal Distribution
• Central Limit Theorem
• Histogram, Normality Tests
• Skewness & Kurtosis
• Understanding Hypothesis Testing
• P-Value Method, Types Of Errors
• T Distribution, One Sample T-Test
• Independent And Relational T Tests
• Direct And Indirect Correlation
• Regression Theory

MODULE 6: MACHINE LEARNING INTRODUCTION

• Machine Learning Introduction
• ML core concepts
• Unsupervised and Supervised Learning
• Clustering with K-Means
• Regression and Classification Models.
• Regression Algorithm: Linear Regression
• ML Model Evaluation
• Classification Algorithm: Logistic Regression

MODULE 1: DATA ANALYSIS FOUNDATION

• Data Analysis Introduction
• Data Preparation for Analysis
• Common Data Problems
• Classification of Analytics
• Various Tools for Data Analysis

MODULE 2: 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
• Hands-on Case Study: Trend 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: Procurement Decision with break even

MODULE 5: PARETO (80/20 RULE) ANALSYSIS

• Pareto rule Introduction
• Preparation Data for Pareto Analysis
• Insights on Optimizing Operations with Pareto Analysis
• Performing Pareto Analysis on Data
• Hands-on case study: Pareto Analysis

MODULE 6: VARIANCE AND FREQUENCY ANALYSIS

• Concept of Variability and Variance
• Data Preparation for Variance Analysis
• Business use cases for Variance and Frequency Analysis
• Performing Variance and Frequency Analysis
• Hands-on case study 1: Variance Analysis
• Hands-on case study 2: Frequency Analysis

MODULE 7: COMPARISION AND CORRELATION ANALYSIS

• Data comparison Introduction
• Concept of Correlation
• Calculating Correlation with Excel
• Comparison vs Correlation
• Performing Comparison Analysis on Data
• Performing correlation Analysis on Data
• Hands-on case study 1: Comparison Analysis
• Hands-on case study 2 Correlation Analysis

MODULE 8: DATA ANALYSIS BUSINESS REPORTING

• Management Information System Introduction
• Various Data Reporting formats
• Creating Data Analysis reports as per the requirements
• Presenting the reports
• Hands-on case study: Create Data Analysis Reports

MODULE 1: DATA ANALYTICS FOUNDATION

• Business Analytics Overview
• Application of Business Analytics
• Visual Perspective
• Benefits of Business Analytics
• Challenges
• Classification of Business Analytics
• Data Sources
• Data Reliability and Validity
• Business Analytics Model

MODULE 2: OPTIMIZATION MODELS

• Prescriptive Analytics with Low Uncertainty
• Mathematical Modeling and Decision Modeling
• Break Even Analysis
• Product Pricing with Prescriptive Modeling
• Building an Optimization Model
• Case Study 1 : WonderZon Network Optimization
• Assignment 1 : KERC Inc, Optimum Manufacturing Quantity

MODULE 3: PREDICTIVE ANALYTICS WITH REGRESSION

• Mathematics beyond Linear Regression
• Hands on: Regression Modeling in Excel
• Case Study 2 : Sales Promotion Decision with Regression Analysis
• Assignment 2 : Design Marketing Decision board for QuikMark Inc.

MODULE 4: DECISION MODELING

• Prescriptive Analytics with High Uncertainty
• Comparing Decisions in Uncertain Settings
• Decision Trees for Decision Modeling
• Case Study 3 : Decision modeling of Internet Plans, Monte Carlo Simulation
• Case Study 4 : Kickathlon Sports Retailer Supplier Decision Modeling

MODULE 1: BUSINESS INTELLIGENCE INTRODUCTION

• What Is Business Intelligence (BI)?
• What Bi Is The Core Of Business Decisions?
• BI Evolution
• Business Intelligence Vs Business Analytics
• Data Driven Decisions With Bi Tools
• The Crisp-Dm Methodology

MODULE 2: BI WITH TABLEAU: INTRODUCTION

• The Tableau Interface
• Tableau Workbook, Sheets And Dashboards
• Filter Shelf, Rows And Columns
• Dimensions And Measures
• Distributing And Publishing

MODULE 3: TABLEAU: CONNECTING TO DATA SOURCE

• Connecting To Data File , Database Servers
• Managing Fields
• Managing Extracts
• Saving And Publishing Data Sources
• Data Prep With Text And Excel Files
• Join Types With Union
• Cross-Database Joins
• Data Blending
• Connecting To Pdfs

MODULE 4: TABLEAU : BUSINESS INSIGHTS

• Getting Started With Visual Analytics
• Drill Down And Hierarchies
• Sorting & Grouping
• Creating And Working Sets
• Using The Filter Shelf
• Interactive Filters
• Parameters
• The Formatting Pane
• Trend Lines & Reference Lines
• Forecasting
• Clustering

MODULE 5: DASHBOARDS, STORIES AND PAGES

• Dashboards And Stories Introduction
• Building A Dashboard
• Dashboard Objects
• Dashboard Formatting
• Dashboard Interactivity Using Actions
• Story Points
• Animation With Pages

MODULE 6: BI WITH POWER-BI

• Power BI basics
• Basics Visualizations
• Business Insights with Power BI

Data analytics is the discipline of combining heterogeneous data from various sources, forming deductions, and making predictions to promote innovation, obtain a competitive corporate edge, and assist in strategic decision-making.

Postgraduate-level data science courses are offered as a path of speciality in engineering, computer science, and management. The minimum requirement for a Data Analytics course is a bachelor's degree from an accredited university with at least 50% overall or the equivalent, ideally in the fields of science or computer science.

One of the most sought-after occupations for 2022 is data analysis. The price would change depending on the type of instruction you want. From 403 USD to 1286.31 USD are charged for the Data Analytics Training.

• 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 is £36,535 per annum in the UK.  (Glassdoor)
• The national average salary for a Data Analyst is INR 6,00,000 per year in India. (Glassdoor)
• The national average salary for a Data Analyst is C$58,843 per year in Canada. (Payscale)
• The national average salary for a Data Analyst is AUD 85,000 per year in Australia. (Glassdoor)
• The national average salary for a Data Analyst is AED 106,940 per year in UAE. (Payscale)
• The national average salary for a Data Analyst is SAR 95,960 per year in Saudi Arabia. (Payscale.com)
• The national average salary for a Data Analyst is ZAR 286,090 per year in South Africa. (Payscale.com)
• The national average salary for a Data Analyst is 46,328 EUR per annum in Germany. (Payscale)
• The national average salary for a Data Analyst is CHF 95,626 per year in Switzerland. (Glassdoor)

Because there is an increasing demand for data specialists and a small supply, those in this industry have strong employment prospects. DataMites is the best educational facility for you if you want to pursue a career in the analytics industry. The course material is well developed, and the major mentors are skilled and committed to the industry. For real skills, projects and internship opportunities are available!

In light of the increase in data generation, the idea of data analytics has been more well-known recently. Because the DataMites Data Analytics Training is intended to train applicants beginning at level 1, there are no formal prerequisites; nevertheless, prior knowledge of programming languages, databases, data structures, mathematics, and algorithms is merely ideal.

The top qualification in data analytics is Certified Data Analyst, which verifies your capacity to confidently assess data using a range of technologies. A certification demonstrates your proficiency in manipulating data, conducting exploratory research, comprehending the fundamentals of analytics, and visualising, presenting, and expanding on your results. The DataMites CDA Course has earned recognition from both IABAC and the renowned Jain University.

Your greatest option in the field is the DataMites data analyst certification course. Our data analytics course provides you with concrete proof that you are qualified to help companies, including well-known multinationals, interpret the data at hand. It is evident that you are qualified to carry out the responsibilities of a particular employment role in accordance with industry standards, as opposed to a data analytics certificate.

DataMitesTM is a global institute for data science that has received approval from the International Association of Business Analytics Certifications (IABAC).

• more than 50,000 candidates were trained
• The three-phase learning technique was painstakingly constructed to deliver the best training possible.
• Participate in worthwhile initiatives and case studies.
• Get the JainX Data Analytics Certification and the global IABAC certification.
• Assistance in finding internships and jobs

If you're pondering working in data analysis, you must undergo the DataMites Certified Data Analyst Training. The learning, expertise, and credentials needed to launch a data analysis job from inception are guaranteed to be offered by our program.

At DataMites, the certified data analyst training fee would be 538 USD in the US, 501.84 Euro in the European Countries and 42,000 INR in India.

Having completed data analytics training and is a certified data analytics professional has many advantages in a data-driven environment. At DataMites, you will receive training in data analytics for four months.

The Certified Data Analyst curriculum, one of the best data analytics programmes provided by DataMites, has been approved by the prestigious organisations IABAC and JainX, whose credentials you would acquire after passing the course. The DataMites Certified Data Analyst credential is the finest method to start a career in data analytics.

Given the size of the subject of data analytics, we wish to train informed experts in it. Because of their extensive expertise and practical experience in the data industry, our instructors at DataMites can offer the best learning environment for your forthcoming significant step.

Candidates may participate in Datamites sessions for a three-month period regarding any question or revision they wish to clear with our Flexi-Pass for Data Analytics Certification Training.

DataMites offers a three-phase learning process. Candidates will be given books and self-study videos to use throughout Phase 1 to assist them learn what they need to know about the programme. Phase 2 is the main part of the intensive live online training, and at the end of it, you'll get the IABAC Data Analytics Certification, which is a universal certification. We will also assign tasks and placements during the third phase.

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: -

• 1. Job connect
• 2. Resume Building
• 3. Mock interview with industry experts
• 4. Interview questions

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.