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CP053: Excel Data Validation for Dummies

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In the 53rd session of Chandoo.org podcast, let’s talk about data validation.

What is in this session?

In this podcast,

What is data validation
How Excel DV compares with database & software DV?
Types of data validation rules
List & custom rules explained
Input & error messages
Alternatives to data validation
Enhancing data validation
Removing data validation rules
Homework problem for you
Resources & show notes

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March 10, 2016

Unpivot and then pivot for clarity (case study)

Or more appropriately titled, the one where Power Query solves the problem in less time than it takes you to say Get & Transform Data.

Recently, one of my students Mr. K, sent me a pivot table problem.

Today my boss asked me “how much we paid to staff since the inception of our business with their respective date of joining?” He wanted to know, level wise summary of the last 16 years (on Quarterly / Year wise basis).

The records appended from the database month wise. Have a look to the file and give your ideas.

Mr. K’s data looked like above.

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March 8, 2016

“How Trump happened” in Excel [visualizations]

During last week, an alert reader of our blog, Jørgen emailed me a link to “How Trump happened“. It is an interactive visualization by Wall Street Journal. Jørgen asked me if we could replicate the visualization in Excel. My response: “Making a new chart in Excel? Hell yeah!”

Read on for awesome visualizations and full explanation.

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March 2, 2016

Autosum many ranges quickly with Multi-select & ALT= [quick tip]

Let’s say you have data in a worksheet in various ranges, and you want sum up each range at the bottom.

Something like this:

How to do all this one shot?

Simple. We use multi-select & ALT=

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February 26, 2016

Analyzing half a million complaints – Customer Satisfaction Scorecard [Part 3 of 3]

This is the final part of our series on how to analyze half a million customer complaints. Click below links to read part 1 & 2.

Complaint reason analysis – Part 1
Regional trends & analysis – Part 2

Customer satisfaction scorecard

In the previous parts of this case study, we understood what kind of complaints were made and where they came from (states). For the customer satisfaction scorecard, let’s focus on individual companies.

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February 23, 2016

Analyzing half a million customer complaints – Regional Trends [Part 2 of 3]

This is part two of our three part series on how to analyze half a million customer complaints. Read part 1 here.

Analyzing Regional Trends

As introduced in part 1, our complaints dataset has geographical information too. We know the state & zip code for each complaint. Please note that zip codes are partial or missing for a 10% of the data.

In this article, let’s explore three ways to analyze regional trends.

Regional trends by state, product & issue
Complaints per million by state
Complaints by zip code

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February 18, 2016

Analyzing half a million consumer complaints [Part 1 of 3]

How would you analyze data when you have lots of it? That is the inspiration for this series.

Let’s meet our data – Finance Industry Consumer Complaints

As part of open data initiatives, US government & Consumer Financial Protection Bureau maintain a list of all consumer complaints made against financial institutions (banks, credit unions etc.) You can download this data from the catalog page here. I have obtained the data on 1st of February, 2016. The download has 513,824 records. Each row contains one complaint.

In this and next two parts of the series, we are going to analyze these half a million complaints to find insights.

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February 16, 2016