What Is Unpivot (And How Does It Affect Data Analytics)?

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Unpivot is real. When working in BI or with data analytics, many have heard of the concept of unpivoting data. But what exactly does unpivoting mean, and why is it useful for data analytics? In this guide, we’ll take a look at what unpivoting does, some examples and use cases, and why unpivoting as a concept is so valuable for data analytics development.

What is Pivot?

A pivot table is a data processing tool that appears as a statistical table that presents information about another table in a way that clearly identifies important and valuable statistics. The core premise is that information is presented in a relatively straightforward manner in a standard spreadsheet. Although simplicity improves clarity, it also makes it harder to understand the spreadsheet’s contents on a larger scale. The capacity of pivot tables to provide you with information about your data fills this need.

What is Unpivot and Why is It Useful for Data Analytics?

Most developers are familiar with pivot tables. With the use of sums or averages, for instance, a pivot table may rapidly simplify fundamental statistical data and present it in a more comprehensible way. Before you can begin pivoting your data, though, you might need to reorder it, or in other words, “unpivot” it.

The relational operations Pivot and Unpivot in SQL or Excel are used to change one table into another in order to create a table with a more straightforward perspective. Traditionally, we may say that the pivot operator transforms the table’s row data into its column data. The Unpivot operator performs the reverse operation, turning column-based data into rows.

Outside of specific SQL or Excel use cases, there are some pretty important reasons to unpivot your data when developing data analytics.

You might be thinking: Unpivoting is simply the process of converting data in columns into rows. Why is this concept so valuable for data analytics?

Simply said, when data has a tabular structure like a database, pivot tables or formulae make it easier to evaluate the data. Each row represents a transaction, and each object has its own column (i.e. a sale, a task, etc.). We are all aware that data is messy and occasionally needs some treatment to be used effectively when it comes to data analytics. One of these obstacles is the representation of categories or dates as columns rather than rows. This eliminates the need for many computed columns for filtering choices and other problems. Unpivoting data is one technique to deal with this issue.

If you keep the data in its current state, you frequently have few options for visual display and even fewer options for filtering. Unpivoting data gives you more options for data structure and makes your report more interactive without requiring the use of additional calculated columns. Essentially, unpivoting frees your data up and makes it easier to use and manage.

Examples of When to Use Unpivot

Let’s consider an example of when unpivot can be helpful. Think of a financial spreadsheet that any typical business would have, either exported from a financial tool or built manually.

Each month in this spreadsheet is represented by a column, such as January, February, March, April, etc. While it’s pretty simple to drag a range of fields and generate a chart, pulling something like this into a database for dynamic report building is a lot more difficult. That’s because each month is in a separate field or column in the database.

This is where unpivot comes into play. If you can grab the January through December columns and unpivot them, you can easily query them using SQL syntax. Essentially, you create one column named Month and another named Amount, and unpivot all those columns to fit into those unpivoted columns.

Basically, it would look like this:

So, where you had one row for 702-Uniforms, you can now expand it to 12, with one per month. The same for each additional record. With things unpivoted, you can easily calculate quarterly, calculate yearly, apply filters and where clauses, and do more analysis of the data.

Use Cases of Unpivot

Let’s consider a use case for unpivoting data. Let’s say you have a table of data that assigns a specific number of tasks to a group of users, such as a development team for an application. You like the row-column arrangement because it makes reading easier, but you find it simpler to perform calculations when working with data that is arranged in rows since there are fewer columns to filter.

Consider the difficulties of the data in its current state to have a better understanding of why unpivoting this data might be helpful. How long would it take to determine how many of the hundreds of engineers on a development team actually completed Tasks #3 or #6? How long would it take to look up the number of jobs that a certain developer completed?

Given that there are a limited amount of users and jobs that can be counted, it might not appear difficult right now to simply manually search for the specific data needed. Unpivoting enters the picture when there is an increase in the number of users or the variety of tasks to be completed, where manually searching for data becomes notably more difficult.

You may find the precise data you’re seeking if you used unpivot to transform the same table into a slightly different format. Your data table is altered such that your column of developer names becomes the attributed and all the jobs that have been checked off become the value after the columns of data that you wish to unpivot have been unpivoted. One of the numerous benefits of unpivoting data is that partially formatted and unformatted data may be examined with ease if brought to the condition where we initially observed the row-column arrangement.

How DashboardFox Can Help with Unpivot

Without a doubt, using unpivot is very important in order to execute functions that would totally help companies with their daily processes and operations. It is a very important tool that we need to use in order to have more effective presentations and data processing. In short, we need this for the company’s progress.

At the moment of this article, DashboardFox doesn’t have an unpivot feature (we have a pivot, but not a unpivot). Currently, we recommend leveraging a SQL view or unpivoting in Excel and then importing the data to DashboardFox.

But here’s the good news: we think it’s a valuable feature and we plan to add it. You can check the latest status on our roadmap here.

Our approach to features that we don’t have, we’re driven by our customers. So if DashboardFox seems like the perfect tool for you, but you need this one critical feature, let us know. It will move it up to the top of our roadmap and then we tend to knock it out in a matter of days/week(s) based on your feedback.

It’s a perk of working with a small business: you get your input factored in quickly, not like trying to get a change to a product made by some billion dollar Goliath.

Start the conversation by reaching out to us or better yet, seeing DashboardFox in action through a free live demo session. We will be waiting!

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