*** Course access includes downloadable resource files and case studies, quizzes and homework exercises, 1-on-1 instructor support, LIFETIME access and a 100% money-back guarantee! ***
Pivot Tables are an absolutely essential tool for anyone working with data in Excel.
Pivots allow you to quickly explore and analyze raw data, revealing powerful insights and trends otherwise buried in the noise. In other words, they give you answers. Whether you're exploring product sales, analyzing which marketing tactics drove the strongest conversion rates, or wondering how Boston condo prices have trended over the past 15 years, Excel Pivot Tables provide fast, accurate and intuitive solutions to even the most complicated questions.
This course gives you a deep, 100% comprehensive understanding of Excel Pivot Tables and Pivot Charts. I'll show you when, why, and how to use Pivot Tables, introduce advanced sorting, filtering, and calculation tools, and guide you through interactive, hands-on demos and exercises every step of the way.
We'll start by covering everything you need to know to get up and running with Excel Pivot Tables, including:
We'll then explore and analyze datasets from a number of real-world case studies, including:
Whether you're looking for a quick primer, trying to diversify your Excel skill set, or hoping to step up your analytics game in a major way, you've come to the right place. In today's increasingly data-driven world, analytics skills are in short supply and incredibly high demand, and those with the ability to transform data into insight are leading the charge. I'm here to help you become an analytics ROCK STAR.
Full course includes downloadable resources and project files, homework and course quizzes, lifetime access and a 30-day money-back guarantee. Compatible with Excel 2007, Excel 2010, Excel 2013 or Excel 2016.
In this lecture we'll get familiar with the course materials and curriculum, including core topic areas, downloadable resources, homework exercises and quizzes.
In this lecture I'll show you how to download the resources that we'll be using throughout the course
In this lecture I'll introduce you to the IMDb Movie Database, which we'll be working with through the first several sections of the course.
In this lecture, I'll outline some key assumptions and expectations to keep in mind before diving in.
Learn how PivotTables are used, and why they are one of the most powerful and versatile tools for analyzing and exploring raw data in Excel.
A PivotTable is only as strong as the data behind it. Let's take a few minutes to talk about some key DO's and DON'Ts of preparing raw data for analysis.
In this lecture we'll explore a few different ways to easily insert PivotTables in Excel.
When you analyze data with a PivotTable, think of yourself as a pilot and the Field List as your cockpit. In this lecture, we'll learn how to use the field list to slice, dice, and filter our data with ease.
In this lecture, we'll review some of the tools available in the PivotTable "Analyze" and "Design" tabs, including slicers and timelines, calculated fields, PivotCharts and table styles.
Learn how to clear, select, move and copy PivotTables using options from the "Analyze" tab.
Learn how easy it is to refresh and update PivotTables as your source data changes, and understand the difference between changes made within or outside of your source data range.
Learn how to use tables or column-only source references to deal with data that consistently grows over time.
For those looking to dig a bit deeper, this lecture demonstrates how PivotTable values are actually calculated and displayed based on given field settings.
In this lecture, we'll discuss a few different ways to customize number formats in PivotTables (dates, currency, percentages, etc)
Learn how to adjust PivotTable settings to apply a default value to blank cells.
There are several options when it comes to PivotTable report layouts, and a number of ways to customize the look and feel. In this lecture, we'll review these options and discuss the pros and cons of each.
PivotTables can be an incredibly useful tool for creating brand new tables from existing source data, whether you want to aggregate your data at a different level of granularity, eliminate certain fields, or add new calculated metrics. This lecture demonstrates how this can be done using specific table layouts and design tools.
In this lecture, we'll learn how to change and customize labels and headers in Excel pivots.
In this lecture, we'll demonstrate how to use conditional formatting like color scales and icon sets to visualize patterns in your data and draw attention to notable trends.
In this lecture I'll show you how to hide text to prevent it from overlapping with data bars, using a custom formatting rule.
In this lecture, we'll review basic PivotTable sorting options, including manual, alphabetical and value-based sorting.
In this lecture, we'll explore cases where sorting may give unexpected results due to Excel's "custom lists".
Label filters allow you to include or exclude items using text-based criteria (i.e. begins with, ends with, contains, does not contain, etc). This lecture demonstrates several ways to use these label filters in your PivotTable views.
Wildcards allow you to create more complex and flexible label filters. In this lecture we'll practice using two variations of these wilcards: the asterisk (*) and question mark (?).
Value filters allow you to include or exclude items using numerical or value-based criteria (i.e. greater than, less than, equal to, etc). This lecture demonstrates several ways to use these value filters in your PivotTable views.
Learn how to adjust PivotTable settings to allow you to apply multiple filters to the same field.
Grouping options allow you to combine or aggregate data however you choose. In this lecture we'll walk through some of the most common automatic and manual grouping techniques.
In this demonstration we'll show how daily data can be automatically grouped to summarize data by month, quarter, year, etc.
In this lecture, we'll practice using slicers and timelines to add visual filtering tools to a PivotTable.
If you need to generate multiple copies of a PivotTable view with different filter settings (i.e. a view of product sales for each region or country), the "Report Filter Pages" option is a lifesaver. In this lecture, we'll see how this tool can be used to instantly break out multiple views.
In this lecture, we'll explore different ways to summarize values within PivotTables, including Sum, Count, Average, Max, Min and more.
In this demo, we'll talk about the difference between "Sum Of" and "Count of", and why PivotTables sometimes default to counting values instead of summing them.
One of the most powerful PivotTable features is the ability to display values in multiple ways. This lecture introduces some of the most common and powerful options, including % of Column, % of Parent, Difference From, Running Total, and more.
In this lecture, we'll practice using "% of Column" and "% of Row" value calculations in our Pivot.
In this lecture, we'll practice using "% of Parent" value calculations in our Pivot.
In this lecture, we'll practice using "Difference From" and "% Difference From" value calculations in our Pivot.
In this lecture, we'll practice using "Running Total" and "% Running Total" value calculations in our Pivot.
In this lecture, we'll practice using "Rank" value calculations in our Pivot.
In this demo, we'll transform values into index numbers and explain how the approach can be used as an analytical tool.
Calculated fields are one of the most powerful PivotTable tools. In this lecture we'll explore some common ways to create new values and calculations based on existing fields.
In this demo, we'll see why you should always create calculated "rate" metrics in your Pivot, as opposed to your raw data range.
In this lecture we'll demonstrate how adding a simple "Counting Column" in your raw data can enable powerful PivotTable calculations and analysis tools.
In this lecture we'll explore a second example of using a "Counting Column" in the raw data to enable more complicated calculated fields.
Calculated items are essentially the text equivalent of calculated fields. In this lecture we'll explore why (and why NOT) to use calculated items in PivotTables.
In this lecture, we'll demonstrate how to customize the solve order for fields that are part of multiple calculations.
In this lecture, we'll introduce some of the pros and cons of using PivotCharts for data analysis.
In this lecture, we'll practice creating a PivotChart in the form of a Clustered Column chart.
In this lecture, we'll practice creating a PivotChart in the form of a Pie or Donut chart.
In this lecture, we'll practice creating a PivotChart in the form of a Clustered Bar chart.
In this lecture, I'll explain how to prevent charts from resizing and distorting when the underlying rows or columns are changed.
Changing PivotChart types is incredibly easy. In this lecture, we'll practice modifying our charts using the PivotChart Design tools.
In this lecture, we'll practice creating a PivotChart in the form of a Stacked Area chart.
In this lecture we'll practice customizes the look and feel of a PivotChart using layout and style options.
In this lecture I'll demonstrate the pros and cons of moving a PivotChart to its own separate worksheet.
In this lecture, we'll practice inserting slicers and timelines and applying them to multiple PivotTables and PivotCharts.
In this demo, we'll build a dynamic dashboard using PivotCharts, slicers and timelines.
In this lecture, I'll introduce the Case Study section of the course and lay out some expectations before we dive in.
In this case study we'll explore U.S. Census Bureau data from the 2012 presidential election, including population and registered voter counts broken down by state and age group.
In this case study we'll review salary information for government employees in San Francisco, including employee names and titles as well as base and overtime pay from 2011-2013.
In this case study we'll explore recorded shark attack records from 1900-2016. Dimensions include the date and location of the attack, victim demographics and activity, shark species, and whether or not the attack was provoked.
In this case study we'll explore a 3-month sample of US stock market data, including Open, High, Low and Close prices as well as trading volume for 500 individual stocks.
In this case study we'll take a look at Major League Baseball team statistics from 1995-2015, including games played, wins, losses and post-season results, along with hitting and pitching statistics (R, HR, RBI, ERA, etc).
In this case study we'll explore customer-submitted burrito ratings from a number of Mexican restaurants in San Diego. Data includes the burrito and restaurant name as well as 0-5 ratings based on tortilla quality, temperature, meat volume, uniformity, synergy, and more.
In this case study we'll analyze daily weather conditions for Jan-Dec 2016, including max, min, and mean temperature, wind speed, total precipitation and weather conditions.
In this case study we'll analyze actual post-level Facebook data from Spartan Race. Data includes the date and time of the post, post type and copy, and number of engagements (likes, comments, shares, etc).
In this lecture I'll leave you with some additional resources to dive into, including the other two courses in this series: Advanced Excel Formulas & Functions and Excel Charts & Graphs.
Chris Dutton is a certified Microsoft Excel Expert, analytics consultant, and best-selling Udemy instructor with more than a decade of experience specializing in business intelligence, marketing analytics and data visualization.
He founded Excel Maven in 2014 to provide high-quality, applied analytics training and consulting to clients around the world, and now mentors 10,000+ students in more than 130 countries. He has developed award-winning data analytics and visualization tools, which have been featured by Microsoft, the New York Times, and the Society of American Baseball Research.
Current Udemy courses include Advanced Excel Formulas & Functions, Data Visualization with Excel Charts & Graphs, and Data Analysis with Excel Pivot Tables.