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    SpicyMags.xyz

    Data Analytic From Beginner To Advance

    Posted By: ELK1nG
    Data Analytic From Beginner To Advance

    Data Analytic From Beginner To Advance
    Published 5/2025
    MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
    Language: English | Size: 8.97 GB | Duration: 15h 11m

    Learn Data Analytics with Excel & Power BI: Data Cleaning, Visualization, Dashboards & Business Insights

    What you'll learn

    Understand the data analytics lifecycle and apply the problem-solving framework to real-world challenges.

    Clean, analyze, and visualize data using Microsoft Excel, including pivot tables and advanced formulas.

    Build interactive dashboards in Power BI to communicate insights and track KPIs.

    Apply statistical techniques like hypothesis testing and correlation to drive data-informed decisions.

    Create a personal portfolio website to showcase your analytics projects and skills to potential employers.

    Complete real-world projects and case studies from start to finish, simulating professional data tasks.

    Requirements

    No prior experience is required—this course is designed for complete beginners!

    Willingness to learn and practice

    A stable internet connection

    A laptop or desktop computer (Windows or Mac)

    A Microsoft Excel (guided in the course)

    A free Power BI (guided in the course)

    Description

    Ready to launch your data analytics career using easy-to-learn, in-demand tools? This comprehensive course will take you from beginner to advanced with just Excel and Power BIStart by mastering Microsoft Excel: you’ll learn essential skills like data cleaning, applying formulas, conditional formatting, creating charts, and working with pivot tables. Once you're comfortable with Excel, you'll transition to Power BI, where you'll discover how to import data, establish relationships, apply DAX (Data Analysis Expressions), and create interactive dashboards using visuals and slicers. These skills are essential for analyzing and visualizing data effectively, helping you solve real-world business problems.This course is designed specifically for beginners, non-technical professionals, and anyone looking to switch careers to data analytics. Whether you want to enhance your current skill set or build a new career in data, this course provides hands-on experience and real-world case studies. By the end, you’ll have the confidence to analyze complex data and create stunning reports and dashboards, all while building a portfolio that demonstrates your new skills to potential employers.Tools You’ll Learn:Microsoft Excel: Data cleaning, formulas, charts, pivot tables, conditional formatting, and data visualization.Power BI: DAX, data modeling, relationships, visuals, slicers, and dynamic reports.Projects You’ll Build:Sales Performance AnalysisProject Management AnalysisWho This Course is For:Beginners exploring data analytics careersBusiness professionals working with Excel dataJob seekers looking to build a data portfolioStudents, freelancers, and non-coders

    Overview

    Section 1: Introduction

    Lecture 1 Introduction

    Lecture 2 What To Expect In This Course

    Lecture 3 Free Video

    Lecture 4 Free Video

    Lecture 5 Free Video

    Lecture 6 Free Video

    Lecture 7 Free Video

    Section 2: Data sources and access

    Lecture 8 How to install microsoft excel on windows

    Lecture 9 An introduction to spreadsheets

    Lecture 10 Important spreadsheet terminology

    Lecture 11 Spreadsheet file format

    Lecture 12 Spreadsheet text file format

    Lecture 13 How to import data into Microsoft excel through Get Data feature.

    Section 3: Function you need to know as a data analyst

    Lecture 14 10 Basic function in Microsoft Excel

    Section 4: Problem solving skills and data analytics process

    Lecture 15 Problem Solving

    Lecture 16 Data analysis process

    Section 5: Data aggregations and descriptie statistics

    Lecture 17 Descriptive Statistics

    Lecture 18 Pivot Table Overview

    Lecture 19 Pivot Table Walkthrough

    Section 6: An introduction to data visualisation

    Lecture 20 Data Visualization Intoduction

    Lecture 21 Data Visualization Walkthrough

    Section 7: Samples and distributions

    Lecture 22 Sample and sample size

    Lecture 23 Hypothesis testing

    Lecture 24 Hypothesis testing walkthrough

    Section 8: Indentifying patterns

    Lecture 25 Line of best fit

    Lecture 26 Line of best fit equation

    Lecture 27 Line of best fit walkthrough

    Section 9: Microsoft Excel Project

    Lecture 28 Micorsoft Project Introduction

    Lecture 29 Microsoft Excel Project: Data Importation

    Lecture 30 Microsoft Excel Project: Data Cleaning

    Lecture 31 Microsoft Excel Project: Data Transformation

    Lecture 32 Microsoft Excel Project: Exploratory Data Analysis

    Lecture 33 Microsoft Excel Project: Data Modeling

    Lecture 34 Microsoft Excel Project: KPI

    Lecture 35 Microsoft Excel Project: Analysis

    Lecture 36 Microsoft Project: Data Visualization

    Lecture 37 Microsoft Excel Project: Template

    Lecture 38 Microsoft Project: Import KPI to Dashboard

    Lecture 39 Microsoft Project: How to design Line Chart

    Lecture 40 Microsoft Project: How to design Doughnut Chart

    Lecture 41 Microsoft Project: How to design Bar Chart

    Lecture 42 Microsoft Project: How to design Column Chart

    Lecture 43 Microsoft Project: How to design a Doughnut Chart 2

    Lecture 44 Microsoft Project: How to design Slicer

    Lecture 45 Microsoft Project: How to design Title

    Section 10: Communicating our findings

    Lecture 46 Crafting experiences through data stories

    Lecture 47 EPIC communication

    Section 11: Design for impactful communication

    Lecture 48 The four pillars of effective communication design

    Lecture 49 Presentation design principles

    Section 12: Introduction to dashboard and reporting

    Lecture 50 Dashboards and reports

    Lecture 51 Power BI as a dashboarding tool

    Lecture 52 How to install Power BI into Windows Laptop

    Lecture 53 Importing data in Power BI

    Section 13: Creating Visuals in Power BI

    Lecture 54 Creating a visualization

    Lecture 55 Comparisons in Power BI: Line charts

    Lecture 56 Comparisons in Power BI: Column charts

    Lecture 57 Compositions in Power BI

    Lecture 58 Relationships in Power BI: Scatter Charts

    Lecture 59 Maps in Power BI

    Section 14: Formatting Visuals in Power BI

    Lecture 60 Basic formatting of visualisations

    Lecture 61 Communicating additional information through visualisations

    Lecture 62 Conditional formatting in Power BI

    Section 15: Data Model in Power BI

    Lecture 63 An introduction to data models in Power BI

    Lecture 64 Importance of data model

    Section 16: Data Transformations In Power Bi

    Lecture 65 Getting started with Power Query Editor

    Lecture 66 Data type in power bi

    Lecture 67 Spliting and replacing value in power bi

    Lecture 68 Analyzing data profile and groupby with power query

    Section 17: Calculated Column With Dax

    Lecture 69 Concatenating column using dax

    Lecture 70 Dax variable

    Lecture 71 Using control flow and string functions

    Lecture 72 Referencing columns using the RELATED function

    Section 18: Dax Aggregation

    Lecture 73 Creating a simple year table

    Lecture 74 Creating a table of unique values and descriptions

    Lecture 75 Creating a simple measure

    Lecture 76 Creating a compound measure

    Section 19: First Power BI Project

    Lecture 77 Dashboard planning

    Lecture 78 Creating power BI template with power point

    Lecture 79 Project: Dashboard KPI

    Lecture 80 Project: Creating a quick measure

    Lecture 81 Project: Creating calendar table with dax

    Lecture 82 Project: Creating growth rate

    Lecture 83 Project: Formating line chart

    Lecture 84 Project: Formating doughnut chart

    Lecture 85 Project: Formating bar chart and creating conditional column with power query

    Lecture 86 Project: Formating slicer

    Lecture 87 Project: Creating a greating message

    Lecture 88 Project: How to hide some element on your dashboard

    Lecture 89 Project: Dynamically add image into dashboard

    Lecture 90 Project: Creating a drillthrough in your dashboard

    Section 20: Exploratory data analysis in power bi

    Lecture 91 EDA Overview

    Lecture 92 EDA Key Influncer

    Lecture 93 Power BI analyze feature

    Lecture 94 Looking for trends and patterns with conditional formating

    Section 21: Final Project: Tracking Njiwa’s Water Funds

    Lecture 95 Project: Formating column chart

    Lecture 96 Final Project: Project Overview

    Lecture 97 Final Project: Data Importation

    Lecture 98 Final Project: Data Cleaning

    Lecture 99 Final Project: Data Modeling

    Lecture 100 Final Project: Data Enrichment

    Lecture 101 Final Project: Calculate Water Improvement Percenatage

    Lecture 102 Final Product: Calculate Cumulative Cost and Budget

    Lecture 103 Final Project: Calculating Incompleted Project

    Lecture 104 Final Project: Calculating Other Metrics

    Lecture 105 Final Project: Importing Template From Power Point Into Power BI Desktop

    Lecture 106 Final Project: Formating Card In Power BI Desktop Desktop

    Lecture 107 Final Project: Formating Guage Map Power BI Desktop

    Lecture 108 Final Project: Formating Bar Chart Power BI Desktop

    Lecture 109 Final Project: Formating Pie Chart Power BI Desktop

    Lecture 110 Final Project: Formating Shape Map Power BI Desktop

    Lecture 111 Final Project: Creating Buton Power BI Desktop

    Section 22: Portfolio Website

    Lecture 112 Creating A Portfolio Website.

    Complete beginners who want to start a career in data analytics,Students and recent graduates looking to build job-ready skills in Excel, SQL, and Power BI,Professionals in non-technical roles who want to make data-driven decisions,Career switchers seeking hands-on experience and a portfolio to break into tech,Freelancers and entrepreneurs who want to analyze their own business data,Anyone interested in learning how to turn raw data into actionable insights and impactful dashboards