How Data Manipulation Is Done


The skill and knowledge of playing with data is a critical skill in analysis. This technique is used in various situations such as searching for trends or patterns or as a preparatory stage for further analysis. Sorting data in chronological, alphabetic, numerical or complexity is all forms of data manipulation.

Manipulating data is a process of rearranging, resorting and otherwise, moving your research data without changing it fundamentally. This is both used as preparatory technique like as a precursor to other activities or as a way to explore the data as analytic tool in its own right. Among the key aspects of manipulation technique than related techniques such as transformation is that, the underlying data stays unchanged.

Reorganizing data helps in identifying patterns that might otherwise not be apparent. Truth is, it's nearly certain that many patterns will not be visible right at first glance.

Literally, resorting is a technique that's aimed in changing the order of data. Most of the time, resorting is performed on quantitative or numerical data but, it can be applied easily to text content. There are some common kinds of sorting like alphabetical, chronological, numerical as well as others that are less common. To give you an example, a list of responses to survey question asking for rating of a product or service can be sorted based on the tone and severity of the review.

Sorting the data can help in isolating important individual values, the lowest or highest, least or most frequent, last or first and can be a way to highlight the shape of data. Rearranging is a kind of activity that normally involves digital or physical repositioning of data element so by that, it sits in close proximity to each other. This can be to organized photo in narrative or juxtaposing contrasting ideas.

Most of the rearranging that's done is exploratory however there are instances that it'll be more directed. In such cases, professionals in data manipulation may try to present new configuration for the data similar to rearranging furniture to better support activities. Some manipulation is more purposeful. Professionals may seek to categorized collection of photos by means of grouping them into the same pile or drawing out common themes in user interviews.

Despite of the simplicity of data manipulation as a technique, it is delivering the heart of very powerful methods in analytics. For instance, affinity diagramming demands more than manipulation in order to produce real insights.