What Is Data Wrangling?

Data wrangling is the process of cleaning and unifying messy and complex data sets for easy access and analysis.

The Key Steps to Data Wrangling:

Data Acquisition

Identify and obtain access to the data within your sources.

Joining data

Combine the edited data for further use and analysis.

Data cleansing

Redesign the data into a usable and functional format and correct/remove any bad data.

Goals of Data Wrangling

With the amount of data and data sources rapidly growing and expanding, it is getting increasingly essential for large amounts of available data to be organized for analysis. This process typically includes manually converting and mapping data from one raw form into another format to allow for more convenient consumption and organization of the data.

Goals of data wrangling

  • Reveal a “deeper intelligence” by gathering data from multiple sources
  • Provide accurate, actionable data in the hands of business analysts in a timely matter
  • Reduce the time spent collecting and organizing unruly data before it can be utilized
  • Enable data scientists and analysts to focus on the analysis of data, rather than the wrangling
  • Drive better decision-making skills by senior leaders in an organization

Altair Monarch is the industry’s leading solution for self-service data wrangling.

Built for business users not rocket scientists Automatically extract from reports & web pages Combine, clean and use with your favorite tools

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