What Makes A Good Data Preparation?
Data preparation is one of the key parts of data science. It involves cleaning up messy data sets before analyzing them. It’s essential to get the right information out of raw data so you can draw valid conclusions from it.
The best data preparation software will allow you to cleanse your data set and prepare it for analysis. Cleaning data means removing junk information, fixing typos, standardizing formats, and aggregating data into a common form. Preparing data means organizing it into the proper structure so you can easily analyze it and understand its meaning. The best data preparation software will combine these two processes into one seamless experience.
Cleaning data: One of the biggest challenges with data preparation is finding ways to remove unwanted elements from your data set. There are tons of free online services available that can cleanse your data. These services are perfect for small projects or quick analyses.
Fixing typos: Typos are often overlooked until it’s too late and you realize you’ve lost valuable data. Fixing typos early on can prevent costly mistakes down the road. Some of the best data preparation software includes spellcheckers, auto correctors, and grammar checkers built in.
Standardizing formats: No matter how well prepared your data is, there’s always going to be some variation in the information stored within each column. Standardizing your data removes this variation and ensures your data stays consistent across columns. Sometimes this process entails changing the format of data to match a specific pattern. Other times, you might want to change the order of the data or convert values like dollars into percentages.
Aggregating data: Aggregation is another critical step in preparing your data. After you’ve cleaned your data and standardized it, you need to aggregate it into a single, coherent view. For example, if you’re analyzing customer satisfaction, you might want to group customers into categories based on their spending habits.
Processing speed: Processing speed is important because you don’t want to spend hours waiting for your data to be processed. When using data preparation software, processing speed depends on several factors including the size of your data set, the number of users accessing the system at once, and the hardware running the software.
What Is Data Preparation Software Data preparation software helps business analysts cleanse, organise, and analyse large amounts of data. It then provides the information needed to answer questions like “What is the best product for this customer?”