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Microsoft Excel Data Analysis And Business Modeling

Learn the core concepts of MS data analysis and business modeling to develop the right skills for transforming worksheet data into actionable insights.

(XLS-DA-BM.AB1) / ISBN : 978-1-64459-368-4
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Über diesen Kurs

In today’s data-driven world, every business (big or small) thrives on its ability to transform data into action items. This Excel Business Modeling and Data Analysis course teaches you how to use MS Excel for analyzing data and building financial models that help businesses make informed decisions. Other than learning basic excel formulas, functions, data manipulation and chart creation, you’ll also learn how to use data analysis tools like PivotTables, data tables, scenario analysis (what-if situations), and data consolidation. Use of analytical techniques for building financial models like budgets and forecasts is also covered in the Excel data analysis training course. To make it a fun learning experience for you, we have also included interactive activities like hand-on labs, flashcards, and quizzes along with the course content.

Fähigkeiten, die Sie erwerben werden

  • Translating Excel basics to relatable analytics
  • Using Power Query for cleaning and connecting data
  • Create custom functions with LAMBDA (without VBA)
  • Utilizing new charts and data types for visualizing data like a pro 
  • Utilizing data manipulation techniques like advanced XLOOKUP function 
  • Using 3D Maps for highlighting geographical trends
  • Confidently building powerful business data models
Kursübersicht herunterladen

1

Introduction

  • What you should know before reading this course?
  • How to use this course?
2

Basic worksheet modeling

  • Answers to this lesson's questions
  • Problems
3

Range names

  • How can I create named ranges?
  • Answers to this lesson’s questions
  • Remarks
  • Problems
4

Lookup functions

  • Syntax of the lookup functions
  • Answers to this lesson’s questions
  • Problems
5

The INDEX function

  • Syntax of the INDEX function
  • Answers to this lesson’s questions
  • Problems
6

The MATCH function

  • Syntax of the MATCH function
  • Answers to this lesson’s questions
  • Problems
7

Text functions and Flash Fill

  • Text function syntax
  • Answers to this lesson’s questions
  • Problems
8

Dates and date functions

  • Answers to this lesson’s questions
  • Problems
9

IF, IFERROR, IFS, CHOOSE, SWITCH, and the IS functions

  • Answers to this lesson’s questions
  • Problems
10

Time and time functions

  • Answers to this lesson’s questions
  • Problems
11

The net present value functions: NPV and XNPV

  • Answers to this lesson’s questions
  • Problems
12

The internal rate of return: IRR, XIRR, and MIRR functions

  • Answers to this lesson’s questions
  • Problems
13

More Excel financial functions

  • Answers to this lesson’s questions
  • Problems
14

Circular references

  • Answers to this lesson’s questions
  • Problems
15

The Paste Special command

  • Answers to this lesson’s questions
  • Problems
16

Three-dimensional formulas and hyperlinks

  • Answers to this lesson’s questions
  • Problems
17

The auditing tool and the Inquire add-in

  • Excel auditing options
  • Answers to this lesson’s questions
  • Problems
18

Sensitivity analysis with data tables

  • Answers to this lesson’s questions
  • Problems
19

The Goal Seek command

  • Answers to this lesson’s questions
  • Problems
20

Using the Scenario Manager for sensitivity analysis

  • Answer to this lesson’s question
  • Remarks
  • Problems
21

The COUNTIF, COUNTIFS, COUNT, COUNTA, and COUNTBLANK functions

  • Answers to this lesson’s questions
  • Remarks
  • Problems
22

The SUMIF, AVERAGEIF, SUMIFS, AVERAGEIFS, MAXIFS, and MINIFS functions

  • Answers to this lesson’s questions
  • Problems
23

Summarizing data with histograms and Pareto charts

  • Answers to this lesson’s questions
  • Problems
24

Summarizing data with descriptive statistics

  • Answers to this lesson’s questions
  • Problems
25

Summarizing data with database statistical functions

  • Answers to this lesson’s questions
  • Problems
26

Consolidating data

  • Answer to this lesson’s question
  • Problems
27

Creating subtotals

  • Answers to this lesson’s questions
  • Problems
28

The OFFSET function

  • Answers to this lesson’s questions
  • Remarks
  • Problems
29

The INDIRECT function

  • Answers to this lesson’s questions
  • Problems
30

Spin buttons, scrollbars, option buttons, check boxes, combo boxes, and group list boxes

  • Answers to this lesson’s questions
  • Problems
31

Conditional formatting

  • Answers to this lesson’s questions
  • Problems
32

Excel tables and table slicers

  • Answers to this lesson’s questions
  • Problems
33

Basic charting

  • Answers to this lesson’s questions
  • Problems
34

Advanced charting

  • Answers to this lesson’s questions
  • Problems
35

Filled and 3D Maps

  • Questions answered in this lesson
  • Problems
36

Sparklines

  • Answers to this lesson’s questions
  • Problems
37

Importing data from a text file or document

  • Answers to this lesson’s question
  • Problems
38

The Power Query Editor

  • Answers to this lesson’s questions
  • Problems
39

Excel’s new data types

  • Answers to this lesson’s questions
  • Problems
40

Sorting in Excel

  • Answers to this lesson’s questions
  • Problems
41

Filtering data and removing duplicates

  • Answers to this lesson’s questions
  • Problems
42

Array formulas and functions

  • Answers to this lesson’s questions
  • Problems
43

Excel’s new dynamic array functions

  • Answers to this lesson’s questions
  • Problems
44

Validating data

  • Answers to this lesson’s questions
  • Remarks
  • Problems
45

Importing past stock prices, exchange rates, and...tocurrency prices with the STOCKHISTORY function

  • Answers to this lesson’s questions
  • Problems
46

Using PivotTables and slicers to describe data

  • Answers to this lesson’s questions
  • Problems
47

The Data Model

  • Answers to this lesson’s questions
  • Problems
48

Power Pivot

  • Answers to this lesson’s questions
  • Problems
49

Use Analyze Data to find patterns in your data

  • Answers to this lesson’s questions
  • Problems
50

An introduction to optimization with Excel Solver

  • Answers to this lesson’s questions
  • Problems
51

Using Solver to determine the optimal product mix

  • Answers to this lesson’s questions
  • Problems
52

Using Solver to schedule your workforce

  • Answers to this lesson’s question
  • Problems
53

Using Solver to solve transportation or distribution problems

  • Answer to this lesson’s question
  • Problems
54

Using Solver for capital budgeting

  • Answer to this lesson’s question
  • Problems
55

Using Solver for financial planning

  • Answers to this lesson’s questions
  • Problems
56

Using Solver to rate sports teams

  • Answer to this lesson’s question
  • Problems
57

Warehouse location and the GRG Multistart and Evolutionary Solver engines

  • Answers to this lesson’s questions
  • Problems
58

Penalties and the Evolutionary Solver

  • Answers to this lesson’s questions
  • Problems
59

The traveling salesperson problem

  • Answers to this lesson’s questions
  • Problems
60

Estimating straight-line relationships

  • Answers to this lesson’s questions
  • Problems
61

Modeling exponential growth

  • Answers to this lesson’s questions
  • Problems
62

The power curve

  • Answers to this lesson’s questions
  • Problems
63

Using correlations to summarize relationships

  • Answers to this lesson’s questions
  • Problems
64

Introduction to multiple regression

  • Answers to this lesson’s questions
  • Problems
65

Incorporating qualitative factors into multiple regression

  • Answers to this lesson’s questions
  • Problems
66

Modeling nonlinearities and interactions

  • Answers to this lesson’s questions
  • Problems for Lessons 51–53
67

Analysis of variance: One-way ANOVA

  • Answers to this lesson’s questions
  • Problems
68

Randomized blocks and two-way ANOVA

  • Answers to this lesson’s questions
  • Problems
69

An introduction to probability

  • Answers to this lesson’s questions
  • Problems
70

An introduction to random variables

  • Answers to this lesson’s questions
  • Problems
71

The binomial, hypergeometric, and negative binomial random variables

  • Answers to this lesson’s questions
  • Problems
72

The Poisson and exponential random variable

  • Answers to this lesson’s questions
  • Problems
73

The normal random variable and Z-scores

  • Answers to this lesson’s questions
  • Problems
74

Using the lognormal random variable to model stock prices

  • Answers to this lesson’s questions
  • Remarks
  • Problems
75

Weibull and beta distributions: Modeling machine life and duration of a project

  • Answers to this lesson’s questions
  • Problems
76

Using moving averages to understand time series

  • Answer to this lesson’s question
  • Problem
77

Ratio-to-moving-average forecast method

  • Answers to this lesson’s questions
  • Problem
78

Making probability statements from forecasts

  • Answers to this lesson’s questions
  • Problems
79

The Winters method and the Forecast Sheet tool

  • Answers to this lesson’s questions
  • Remarks
  • Problems
80

Forecasting in the presence of special events

  • Answers to this lesson’s questions
  • Problems
81

Introduction to Monte Carlo simulation

  • Answers to this lesson’s questions
  • Problems
82

Calculating an optimal bid

  • Answers to this lesson’s questions
  • Problems
83

Simulating stock prices and asset-allocation modeling

  • Answers to this lesson’s questions
  • Problems
84

Fun and games: Simulating gambling and sporting-event probabilities

  • Answers to this lesson’s questions
  • Problems
85

Using resampling to analyze data

  • Answer to this lesson’s question
  • Problems
86

Advanced sensitivity analysis

  • Answer to this lesson’s question
  • Problems
87

Pricing stock options

  • Answers to this lesson’s questions
  • Problems
88

Determining customer value

  • Answers to this lesson’s questions
  • Problems
89

The economic order quantity inventory model

  • Answers to this lesson’s questions
  • Problems
90

Inventory modeling with uncertain demand

  • Answers to this lesson’s questions
  • Problems
91

Queuing theory: The mathematics of waiting in line

  • Answers to this lesson’s questions
  • Problems
92

Estimating a demand curve

  • Answers to this lesson’s questions
  • Problems
93

Pricing products by using tie-ins

  • Answer to this lesson’s question
  • Problems
94

Pricing products by using subjectively determined demand

  • Answers to this lesson’s questions
  • Problems
95

Nonlinear pricing

  • Answers to this lesson’s questions
  • Problems
96

Recording macros

  • Answers to this lesson’s questions
  • Problems
97

The LET and LAMBDA functions and the LAMBDA helper functions

  • Answers to this lesson’s questions
  • Problems

1

Basic worksheet modeling

  • Performing Mathematical Calculations using Formulas
2

Lookup functions

  • Accumulating Data Using the VLOOKUP Function
3

The INDEX function

  • Extracting Data Using the INDEX Function
4

The MATCH function

  • Finding the Required Data Using the MATCH Function
5

Text functions and Flash Fill

  • Creating Email Addresses Using the Excel Text Functions
6

Dates and date functions

  • Calculating the Number of Workdays Using a Date Function
7

IF, IFERROR, IFS, CHOOSE, SWITCH, and the IS functions

  • Computing Annual Sales Using the IF Function
8

Time and time functions

  • Calculating Race Timings Using the Time Functions
9

The net present value functions: NPV and XNPV

  • Calculating Net Present Value Using the NPV Function
10

More Excel financial functions

  • Determining Depreciation Using Excel Financial Functions
11

The Paste Special command

  • Using the Paste Special Command to Convert Data
12

Three-dimensional formulas and hyperlinks

  • Summarizing Data Using Three-Dimensional Formulas
13

The COUNTIF, COUNTIFS, COUNT, COUNTA, and COUNTBLANK functions

  • Counting Cells with Criteria Using COUNTIF and COUNTIFS Functions
14

The SUMIF, AVERAGEIF, SUMIFS, AVERAGEIFS, MAXIFS, and MINIFS functions

  • Calculating with Criteria Using the COUNTIF and SUMIF Functions
15

Summarizing data with histograms and Pareto charts

  • Creating Bin Ranges Using Histograms
16

Summarizing data with database statistical functions

  • Summarizing Data
17

Consolidating data

  • Consolidating Data
18

Creating subtotals

  • Creating a Subtotal using the SUBTOTAL Function
19

The OFFSET function

  • Using the OFFSET Function to Create Lagged Values
20

The INDIRECT function

  • Using the INDIRECT Function to Tabulate Data
21

Excel tables and table slicers

  • Using Excel Tables to Perform Calculations
22

Basic charting

  • Creating a Scatter Chart
23

Sparklines

  • Creating Sparklines
24

Importing data from a text file or document

  • Importing Data from a Text File
25

The Power Query Editor

  • Using the Power Query Editor to Transform Data
26

Sorting in Excel

  • Sorting Data
27

Array formulas and functions

  • Performing Calculations Using Array Functions and Formulas
28

Using PivotTables and slicers to describe data

  • Creating a PivotTable and PivotChart
29

The Data Model

  • Using the Distinct Count Option for Calculation
30

Using Solver to determine the optimal product mix

  • Determining the Profit-Maximizing Product Mix Using Solver
31

Using Solver to solve transportation or distribution problems

  • Finding an Optimal Solution Using Solver
32

Using Solver for capital budgeting

  • Obtaining Maximum NPV using Solver
33

Using Solver for financial planning

  • Determining the Monthly Payment Using Solver
34

The traveling salesperson problem

  • Solving the Traveling Salesperson Problem
35

Estimating straight-line relationships

  • Creating a Scatter Chart and Adding a Trendline
36

Modeling exponential growth

  • Creating an Exponential Trend Curve
37

The power curve

  • Creating a Power Curve
38

Using correlations to summarize relationships

  • Using Correlations to Find the Relationship Between Variables
39

Introduction to multiple regression

  • Using Multiple Regression to Find the Optimal Forecasting Equation
40

An introduction to random variables

  • Using Variance and Standard Deviation to Measure the Spread of Data
41

The binomial, hypergeometric, and negative binomial random variables

  • Computing Binomial Probabilities
42

The Poisson and exponential random variable

  • Computing Poisson Distribution
43

The normal random variable and Z-scores

  • Calculating Z-Scores
44

Using the lognormal random variable to model stock prices

  • Calculating the Future Price of a Stock Using a Lognormal Variable
45

Weibull and beta distributions: Modeling machine life and duration of a project

  • Determining Probability Using the Beta Random Variable
46

Using moving averages to understand time series

  • Creating a Moving Average Graph
47

Ratio-to-moving-average forecast method

  • Using the Ratio-to-Moving-Average Forecasting Method
48

The Winters method and the Forecast Sheet tool

  • Estimating Smoothing Constants
49

Introduction to Monte Carlo simulation

  • Simulating the Values of a Normal Random Variable
50

Calculating an optimal bid

  • Determining the Optimal Bid using Simulation
51

Simulating stock prices and asset-allocation modeling

  • Determining Asset Allocation
52

Fun and games: Simulating gambling and sporting-event probabilities

  • Simulating the Outcome of a Sporting Event
53

Using resampling to analyze data

  • Implementing Resampling
54

Advanced sensitivity analysis

  • Creating a Spider Plot
55

Pricing stock options

  • Using Formula Protection in a Worksheet
56

Determining customer value

  • Determining Customer Value
57

Inventory modeling with uncertain demand

  • Determining the Economic Order Quantity (EOQ)
  • Determining the Reorder Point
58

Estimating a demand curve

  • Plotting a Linear Demand Curve
59

Pricing products by using subjectively determined demand

  • Finding the Optimal Price Using Subjectively Determined Demand

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Besides working on the latest excel features, you’ll also learn to use advanced tools like XLOOKUP and LAMBDA functions.

Most businesses (big or small) need meaningful data insights for making informed decisions, which is why there is a growing need of skilled Data Analysts across all industry verticals. With uCetify’s Microsoft Excel Data Analysis and Business Modeling course you can develop the right skill set needed for this job profile.

At uCertify, we provide 24/7 tech support to the users for all of our courses.

Definitely Yes. All those wanting to upskill themselves and learn advanced excel tools for data manipulation and analysis will benefit greatly from this course.

Completing this course will open doors to some exciting job opportunities like data analyst, financial analyst, management consultant, business, market research analyst, supply chain analyst, human resource analyst, and data journalist.

Get Ready to Become a Data Analysis Pro

Learn how to utilize the power of MS excel to analyze data and drive your career towards success.

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