What is Data Prep?

Data prep – or data preparation – is the process of gathering, combining, cleansing, structuring, and organizing data so that it can be analyzed as part of data visualization, analytics, and machine learning applications. Before it became common and now, a necessary tool, data prep used to be a tedious task that only a select few in IT departments could perform. With limited resources and high demands, there were extreme wait times for results. 

So, when self-serve data sets were first released to the business departments in a company, everyone jumped on the opportunity to leverage the new resource. However, without proper training, there were numerous mistakes and inconsistencies that lead to widespread mistrust of data’s sources and accuracy. As a result, data prep emerged to mitigate the risk of this happening again.

Challenges, Strategies and Use Cases in Data Prep and Analytics

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Why is Data Prep Important?

Data prep is the key to efficiency and success for today’s data-driven businesses. Rather than spending hours assessing the quality of data and searching for missing fields, visual data prep automates this process by detecting schemas, data types, and anomalies then combining data sources to go straight to the exploration and analysis of the data.

Data is an invaluable business asset, but if it isn’t accurate and trustworthy, then it can be detrimental. Businesses rely on data to make strategic business decisions and without accurate analytics, these mistakes can be costly. But when data is prepared properly, new strategies around increasing business value can be discovered by transforming, relating, and mapping that data.

Taking it one step further, visual data prep allows users to explore and understand data at every step before moving it into analysis. Today’s self-serve visual data prep is both technologically advanced and user-friendly, making it accessible to business users outside of the IT department who are looking for information at an expedited rate. Data prep enables users to easily manipulate data and blend it from several different sources to create custom analytics that yield highly accurate results. 

Steps to Visual Data Prep:

  • Grouping and filtering
  • Combining data sources
  • Data cleansing
  • Splitting and parsing

How Precisely Can Help?

Precisely offers Data360 Analyze a product to empower users to discover and share insights faster with self-service data prep and analytics.