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Everything You Need To Know About Data Manipulation In Data Science

Most Widely Used Tools In Hadoop Ecosystem For Crunching Big Data

Data Manipulation is an advanced concept in the predictive modeling. A robust predictive model can’t just be built using machine learning algorithms. If organizations are really intended to understand their business problems, the underlying data, performing required data manipulations and then extracting business insights is very important.

What Exactly Is Data Manipulation?

Data manipulation can be interpreted as the process of changing data in order to make it easier to read or be more organized. For an instance, the information in the data becomes easier to locate by arranging its log of data in alphabetical order thereby by presenting individual entries for each of it. Also Data manipulation applications are also used in the websites to help the owners view their most popular pages.

Still confused about Data manipulation? Let’s explain it to you in simpler terminology. Data Manipulation is a loosely used term with ‘Data Exploration’. It indicates the process of ‘manipulating’ data using available set of variables. This process helps in enhancing the accuracy and precision associated with data.

Different Ways To Manipulate Data:

There is no specific way for indicating whether the particular procedure for data manipulation is correct or wrong. As Data manipulation is everything about understanding the data, so whichever procedure you follow to achieve this doesn’t matter much. Here below are a few techniques that are followed by most of the people for data manipulation.

Using In-Built R Functions

For the beginners most of them usually find comfort in performing Data Manipulation applications using inbuilt R functions. This is a good way to begin with but however it is more repetitive and time consuming process.

Use Of Packages For Data Manipulation

Tree based boosting algorithms are extensively used for handling missing data & outliers. This process is definitely less time consuming. ML algorithms for data manipulation are better for understanding the data.

Here below is the list of packages in ‘R’ that make the life easier during the data manipulation stage.

  • dplyr
  • data.table
  • ggplot2
  • reshape2
  • readr
  • tidyr
  • lubridate

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