Data is used for almost every decision made in the business world today. It has become an indispensable resource, one that organizations cannot ignore. This is in part why many businesses have jumped into data science. In order to better utilize the data that is collected, however, organizations first need to transform it into a more usable form with the right tools. This transformation process is often referred to as data wrangling or data preparation.
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Understanding data preparation
Put simply, data preparation means changing your raw data into a form that you can more easily use. This aspect of data science essentially involves taking data you’ve collected, cleaning it up, and changing it into a different format, which can increase its value. This isn’t always easy to do, and recent history has shown that it can be a time-consuming process. After all, with more and more data available to organizations, data sets can quickly become complex and unwieldy. You’re dealing with an amount of data now that was almost incomprehensible only a few short years ago. Taking information, putting it through a data cleansing process, and transforming that raw data into a usable format for analysis is vital for businesses today and should not be overlooked. Thanks to Import.io Transform tools, it’s now faster and easier than ever to perform data preparation.
Simplifying the data preparation process
Whether you’re undertaking data preparation for machine learning purposes or would simply like clean data for future data visualization tools and analytics, the whole data preparation process has largely been a complex one. Data preparation has usually been defined by several steps. First is the discovery phase, where you get a better look at the data you’ve collected and determine how you would like it to be analyzed. Next comes structuring, which organizes and moves your data so analysis can be performed more easily. Data cleansing comes next, where you comb through the data and apply a standard format to everything while getting rid of any outliers or errors. The next step is enriching, where you take another look at the data and determine what further data you might need that will boost what you already have. You then need to validate the data, which includes basically means verifying that the data is consistent, accurate, and of a high enough quality. Finally, you get to publish the data, which prepares it to be used for other analysis purposes and other users in the future.
Obviously, a quick look at this process shows how it can take so much time and so many resources to perform. No wonder data professionals spend the vast majority of their time using data transformation tools with the hope of performing proper analysis. But Import.io simplifies this whole process, decreasing the time and amount of resources needed to run data transformation. With Import.io, data professionals will be able to devote more time discovering fascinating new insights that will help their organizations.
A new outlook with data preparation
With so much information now online, getting that data can often prove the difference between success and stagnation. Web data can be extremely valuable not only since it is accurate but also because it is kept up to date. With the right data in hand, you can analyze what you need to determine new insights and find exciting discoveries.