Data Wrangling as a Business Driver

How data wrangling enhances your business value?

Webster dictionary describes a wrangler as person who takes part in a dispute, or a fighter, debater or an arguer. When we add the word ‘Data’ with ‘Wrangler’ what it means is someone who can churn the data around to define the right meaning out of it, and making data fit for use to decide the business outcomes(or alteast argue about it with data evidence).

So, how can we use this person and his/her techniques to drive business value and make optimal decisions at the right time? Let us look at how data wrangling gets done-

  1. Gather & Extract data – As a first step, we need to gather the right data to start our analysis, based on which we want to form decisions. It could be an Organizational data, like sales for last 10 years or Shared data like Weather reports for last seasons. This data can be small or huge and should be stored ideally so that it is easy to extract, For example – MongoDB for storing huge number of files or images for analysis. Automated tools can be used to scrape the right pieces of information from huge files, if required.
  2. Clean & Enhance the dataset – With the data extracted, we want to make it fit for use in making decisions, and therefore we run programs to eliminate bad data, enhance existing data and format data to universally applicable formats. Some examples where we need cleansing is to find Missing data values or typo errors, find correct address information or format date and currency values.
  3. Integrate & Fuse to find the Right answers – Once we have the data we can rely on, we use programming languages like R, Python etc. to detect patterns or discover new findings out of our dataset. On the weather data, we may find a pattern of temperature range in Summers to predict a Heat wave far in advance, or the sales data can be used to find demand splurge based on a pattern of income changes.

It is interesting to see how the application of Data wrangling can be used in Big data analysis, since this combination of techniques fulfills what Business wants and what Data can deliver.

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