Data Analysis

MS-DAEXPBI : Introduction to Data Analytics with Excel and Power BI

Course Duration

2 Days

Delivery

ILT/VILT

Overview

Overview Course Curriculum Training Schedule Exam & Certification FAQs

This course outline is designed to provide a comprehensive introduction to data analytics. Adjust the content based on the participants' backgrounds, skill levels, and the intended depth of coverage. Additionally, hands-on activities and real-world projects should be tailored to reinforce theoretical concepts with practical experience.

An Introduction to Data Analytics course is designed to provide participants with foundational knowledge and skills in handling and analyzing data.

What You'll Learn

Upon completing the "Introduction to Data Analytics" course, participants can expect to achieve several key outcomes, gaining foundational knowledge and skills in the field of data analytics. The course is designed to equip participants with a solid understanding of essential concepts and provide practical skills that can be applied in various professional settings.

Grasp the fundamental concepts and principles of data analytics.
Understand the role of data analytics in making informed decisions.
Learn techniques for collecting and cleaning data for analysis.
Understand the importance of data quality in analytics.
Gain skills in exploratory data analysis to uncover patterns and trends in data.
Use statistical and visual methods to analyze and interpret data.
Familiarity with basic statistical concepts used in data analytics.
Understand measures of central tendency, dispersion, and probability.
Learn to create effective visualizations to communicate data insights.
Use tools and techniques for data visualization.

Who Should Attend

The "Introduction to Data Analytics" course is designed for a broad audience interested in gaining foundational knowledge and skills in the field of data analytics. The course is suitable for individuals from various professional backgrounds and is particularly beneficial for those looking to understand the basics of data analysis and its applications.

Prerequisites

To ensure participants can fully engage with and benefit from the "Introduction to Data Analytics" course, certain prerequisites are recommended. These prerequisites help establish a baseline of knowledge and skills, enabling participants to grasp foundational concepts and actively participate in the course.

Participants should have basic computer skills, including file management and internet navigation.
A basic understanding of spreadsheet software is beneficial.
Familiarity with tasks such as data entry, basic formulas, and simple data manipulations.
Basic understanding of mathematical concepts, including arithmetic and algebra.
Familiarity with elementary statistical concepts is beneficial but not mandatory.
Participants should have critical thinking skills to analyze and interpret data.
A genuine interest in data and a willingness to learn and explore new concepts.
While not mandatory, having access to data analysis tools such as Microsoft Excel, Google Sheets, or any other similar software is beneficial.

Learning Journey

Coming Soon...

Module 1: Understanding Data Analytics

Definition and importance of data analytics
Applications and use cases in various industries
Role of data analytics in decision-making

Module 2: Basics of Data and Data Types

Introduction to structured and unstructured data
Types of data (numerical, categorical, text)
Data sources and collection methods

Module 3: Introduction to Data Analysis Tools

Overview of popular data analysis tools (Excel)
Choosing the right tool for different tasks
Introduction to data visualization tools (Power BI)

Module 4: Data Cleaning and Preprocessing

Importance of data cleaning
Identifying and handling missing data
Dealing with outliers and inconsistencies
Using Power Query to transform data

Module 5: Exploratory Data Analysis (EDA)

Descriptive statistics and summary metrics
Data distribution and visualization
Correlation analysis

Module 6: Introduction to Statistical Concepts

Basic statistical concepts (mean, median, mode)
Probability distributions
Hypothesis testing and confidence intervals

Module 7: Data Visualization

Importance of data visualization
Choosing the right chart or graph
Design principles for effective visualizations

Frequently Asked Questions (FAQs)

Why should I pick up this course and get certified?

Career Advancement: Boost your earning potential and unlock new job opportunities.
Stay Relevant: Keep your skills current in the ever-changing tech landscape.
Problem-Solving Prowess: Hone your critical thinking and problem-solving abilities.
Hands-On Experience: Apply your knowledge through practical labs and projects.
Expand Your Network: Connect with industry experts and like-minded professionals.
Why take this course with Trainocate?

Here’s what sets us apart:
- Global Reach, Localized Accessibility: Benefit from our geographically diverse training hubs in 24 countries (and counting!).
- Top-Rated Instructors: Our team of subject matter experts (with high average CSAT and MTM scores) are passionate to help you accelerate your digital transformation.
- Customized Training Solutions: Choose from on-site, virtual classrooms, or self-paced learning to fit your organization and individual needs.
- Experiential Learning: Dive into interactive training with our curated lesson plans. Participate in hands-on labs, solve real-world challenges, and take on comprehensive assessments.
- Learn From The Best: With 30+ authorized training partnerships and countless awards from Microsoft, AWS, Google – you're guaranteed learning from the industry's elite.
- Your Bridge To Success: We provide up-to-date course materials, helpful exam guides, and dedicated support to validate your expertise and elevate your career.

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