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Inciter | Data Management and Databases
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Data Cleaning in Excel 101, Part 7: Managing Blank Cells

In this part of our data cleaning series, we’ll be focusing on managing blank cells. There isn’t a singular approach to handling blank cells in your dataset. Because there are numerous reasons why a cell might be blank, context is key when determining how to fill them. Sometimes, you’ll need to fill every blank cell in your data with the same constant. Other times, you’ll pick up clues as to what should be there from the surrounding data.This is Part 7 in our Data Cleaning in Excel 101 series. Part 1 showed methods of removing blank rows from your data. Part 2 focuses on splitting data from one cell to multiple cells. Part 3 covers the opposite: combining data from multiple columns into one column. In Part 4, we discussed...

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Data Cleaning in Excel 101, Part 6: Removing Duplicates

In this part of our data cleaning series, we’ll be reviewing how to find and remove duplicate entries in your dataset. Repeats are a very common data entry mistake or error from a data pull. Duplicates in your data can create a variety of unfortunate consequences in administrative duties and analysis. Worst of all, they lead to a real misrepresentation of your results.This is Part 6 in our Data Cleaning in Excel 101 series. Part 1 showed methods of removing blank rows from your data. Part 2 focuses on splitting data from one cell to multiple cells. Part 3 covers the opposite: combining data from multiple columns into one column. In Part 4, we discussed some incredibly useful and time-saving tricks with Excel’s “Flash Fill” function. Part 5 covers solutions...

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Data Cleaning in Excel 101, Part 5: Numbers That Don’t Act Like Numbers and Leading Zeros

Ever try to do a calculation with numbers in Excel and get an error or the numbers don't seem to be adding up? Ever fight with ZIP code formatting? Below you can find some methods of dealing with numbers that just aren't acting like numbers. We’ll also review some instances in which you’ll actually want Excel to store numbers as text, and how to convert them.This is Part 5 in our Data Cleaning in Excel 101 series. Part 1 showed methods of removing blank rows from your data. Part 2 focuses on splitting data from one cell to multiple cells. Part 3 covers the opposite: combining data from multiple columns into one column. In Part 4, we discussed some incredibly useful and time-saving tricks with Excel’s “Flash Fill” function.Numbers that...

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Data Cleaning in Excel 101, Part 4: More Uses for Flash Fill

Having the right data in the right columns to meet specific requirements for your analysis plays a major role in the data cleaning process. In Parts 2, 3, and 4 of our Data Cleaning in Excel series, we’ll show you how to solve common issues by utilizing both standard and Excel’s powerful “Flash Fill” shortcut.Part 2 focuses on splitting data from one cell to multiple cells. Part 3 covers the opposite: combining data from multiple columns into one column. Here, in Part 4, we’ll showcase some incredibly useful and time-saving tricks with the mystical powers of Excel’s “Flash Fill” function.Flash Fill is the mind-reading short-cut us data folks have been waiting for. It works by analyzing your data entries, detecting a pattern, and then filling in the rest for you.Here,...

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Data Cleaning in Excel 101, Part 3: Combining Data from Multiple Columns

Having the right data in the right columns to meet specific requirements for your analysis plays a major role in the data cleaning process. In Parts 2, 3, and 4 of our Data Cleaning in Excel series, we’ll show you how to solve common issues by utilizing both standard and Excel’s powerful “Flash Fill” shortcut.Part 2 focuses on splitting data from one cell to multiple cells. Here, in Part 3, we’ll cover the opposite: combining data from multiple columns into one column. Coming up in Part 4, we’ll showcase some incredibly useful and time-saving tricks with the mystical powers of Excel’s “Flash Fill” function.Combining Data from Multiple ColumnsIn our last blog post, we went over how to break apart data that has been exported into just one cell. What about...

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Data Cleaning in Excel 101, Part 2: Splitting Up Cell Contents Into Multiple Columns

Having the right data in the right columns to meet specific requirements for your analysis plays a major role in the data cleaning process. Over the next 3 parts in our Data Cleaning in Excel series, we’ll show you how to solve common issues by utilizing both standard and Excel’s powerful “Flash Fill” shortcut. Part 2 focuses on splitting data from one cell to multiple cells. Part 3 covers the opposite: combining data from multiple columns into one column. Part 4 showcases some incredibly useful and time-saving things you can do with the mystical powers of Excel’s “Flash Fill” function.Classic Methods and an Introduction to Excel’s Magical Mind-Reading Shortcut “Flash Fill”While straightening up datasets, you may encounter cells containing text strings of data that need to be organized into multiple...

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Data Cleaning in Excel 101, Part 1: Three methods for removing blank rows (without deleting anything important!)

At Inciter, we use many tools to clean data. Google Sheets and Excel are widely available and powerful tools for basic data cleaning of small to medium data sets. In this series, we will describe different methods for cleaning data that have common problems such as blank rows, duplicates, multiple values in one column, data split into too many columns, leading zeroes, numbers that don’t act like numbers, basic data recoding, and comparing two versions of a spreadsheet. Method #1: Sort them out.Excel’s column sort function won’t order blank cells. If it makes sense to organize your data by a certain column, (i.e. date from newest to oldest), you can sort the entire sheet and watch the completely blank rows fall off. Just be sure all of your data is...

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Data Maturity Part II: How Grown Up Are You?

Data Maturity StagesIn Part I of this blog series, I introduced the concept of data maturity, its importance to organizations, and steps for becoming data mature. Today, we’ll tackle the ways in which organizations can be thought of as existing in different stages of data maturity and how you may move through them. Particularly relative to reporting, knowing where you are on the data maturity scale will help you identify the right approach and the right tools to move forward. Early Phases: Piloting and Building Phase I: Piloting (Infancy)Your data is new and cute, but you can’t really leave it alone when you go out for dinner. You may be collecting some basic data, but you haven’t created a data strategy and made clear decisions about what you are collecting and why....

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Data Maturity Part I

I was introduced to the term “data maturity” by Karen Graham, Maddie Grant, and Jenn Taylor at their 2019 GoodTech Fest presentation. (If you don’t know about GoodTech Fest, check out my blog post on it here and consider going in 2020! It’s a great, reality-based conference about measuring what matters in the nonprofit sector.)I’ve been thinking a lot about this idea of data maturity, and how we can help organizations build capacity to provide data for themselves and to funders. I think about this all the time, of course, but data maturity provides another, very useful concept to hang some ideas on. It got me thinking about why some of our clients seem able to collect and use data better than others, and also about what it takes for...

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