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Data Management and Databases Archives - Inciter
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Tools to Make Data Cleaning Easier

Cleaning, wrangling, munging, preparation, validation, ETL, transformation, ELT… these are all different names for “making data more useful.” Whether you’re doing one-off analysis, scheduled reports analytics, or integrating two different data systems or applications, when you work with data, data cleaning is an important part of almost all data processes. Data cleaning is taking data as-is and changing the content, structure or format to be more useful. Removing blank rows and deleting invalid addresses are examples of data cleaning. Data cleaning can be the most laborious part of a data analysis project. At Inciter, we use tools to streamline the process and save us hours of tedious work.There are a seemingly endless number of tools to assist in the process of data cleaning. Some of them can only be used...

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5 Mistakes That Kill Survey Data (and How to Avoid Them)

Whether you are getting feedback from program participants, members, donors or other stakeholders, an online survey can be the easiest and most efficient way to do it. Of course, online surveys are not a one size fits all solution for collecting data to answer your burning questions, but they can be a cost effective method to gather certain data for your organization. No matter your field or audience, you have to follow some best practices if you want to make use of your data.At Inciter, we develop surveys for a variety of reasons. And if you already have a survey but think you could be doing more with it, we can help you clean up your instrument and fine tune your questions, too. By asking good questions about what...

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Your Data Ducks Are Wandering All Over the Place. Get Them Lined Up To Maximize Your Technology Resources

You want data at your fingertips, when you need it, in the right format. Who doesn’t? But often when you go to get reports, the data is siloed and you can’t bring it together, or some of it’s missing, or it’s not accurate, or you don’t know what to make of it. Maybe you think technology is the answer. It’s understandable. Machine learning. Artificial intelligence. Big data. There is all this amazing technology out there that can make cleaning, analyzing and reporting on data so much easier. Data warehouses, data lakes, and pipelines make it easier to bring all those siloes together into one place without making everyone use a new data system. While these tools can do amazing things, if you don’t have your ducks in a row in terms...

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What is Sketchnoting and Why Should You Try It?

Tired and unfocused during long meetings? I’m going to help you with that.Last week, I had a seven hour Zoom conference call, with about 20 people in it. (I know. I know.) It was necessary, and all parties were actively engaged, and needed to be. This was an author’s retreat for a large research project, where Inciter is serving as the data visualization team. It was important that I stay engaged, not space out, and listen to the findings, the nuances, the decisions people were making. Because I knew I would be called on to do sketches later in the meeting and help them think through how to represent some of the findings.But it’s hard. I don’t think of myself as someone with a squirrel brain, but during meetings that...

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Data Cleaning in Excel 101, Part 8: Final Summary & Data Cleaning Guide

This is the eighth and final post in our Data Cleaning in Excel blog post series. As the series comes to a close, we’d like to take an opportunity to organize and recap material we’ve covered. We’ll review some of the useful Excel functions we’ve used, and provide some guidance for incorporating the techniques into your data cleaning routine.Every dataset has its own issues. Our posts in this series have been written to address ad-hoc common problems. We advise referencing this post as you go through your data with the understanding that not everything here will be applicable to your dataset. Also, keep in mind that you’ll always run into unique challenges, and this isn’t an exhaustive list of commands for squeaky-clean data.When you’re presented with a raw, messy sheet...

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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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