CAT / #Data Interpretation

April 04, 2017 @ 01:15 PM

April 04, 2017 @ 01:15 PM

Interpretation of data is a process

Interpretation of data is a process | MBA Rendezvous

Published : Tuesday, 20 September, 2016 10:45 AM

Interpretation of data is a process

The amount of data circulating around in the world is mind numbing. Everything seems to create data or be dependent on data,a country depends on data for calculating GDP and taking decisions accordingly, a business uses data to take various decisions regarding investments, clients, employees and other areas, a person uses data to make day- to- day decisions regarding household budgets, shopping, future events and so on. With all kinds of data floating around, analysis becomes a crucial aspect, on which the conclusions depend. 

Managing data is a difficult task, as also, interpreting the data to derive the relevant conclusions. As interpretation of data involves some subjectivity, it is possible to streamline the process and make it effective.


1. Aim

Before beginning with data interpretation, it is essential to be clear about the aim of the exercise. The things that you want to accomplish through the data under consideration, what is it that you have collected the data for and so on. Without a proper aim, all the data you collect will be meaningless and seem to be collected at random. Having a clear aim and purpose precedes data collection.

2. Study the data

The next step after listing the aim and collecting data is to study the data thoroughly. Data might involve numbers, statistics, graphs, percentages, opinions and so on. Often, this information will be quite dense and would require carefully reading.


3. Interpret the data

Once you study the data thoroughly, the next step is to begin interpreting the data. This step is where you begin to make sense of the data and add meaning to it. This is a specialised job, as wrong interpretation of data can cause a lot of damage to the company or the individual. Data interpretation should be done using all the relevant resources, mathematical tools at hand. The objective is to extract out of the data all the possible and relevant information, for instance, governments base important decisions such as subsidies, disinvestments, interest rates on data and its interpretation.

4. Draw analogies

Meaning can be added to the data and the data can itself be simplified when appropriate analogies are drawn to make sense of the data and to adapt data to the real world more strongly. Analogies also help to enrich the data and understand it better.

5. Implement

The last step in this process after the analysis of data is to use the analysis to alter, persevere, modify the current practices so that you are able to shape your future positively. All the analysis will mean nothing if you do not implement the conclusions you draw from the process. The process was started to take stock of things and use the results to improve the present and the future and even rectify errors.

Data is everywhere around us. The use of all the data depends on how we interpret and gather the relevant meanings from it and how we use it to make decisions and choices that affect not only the present but will also affect the future.

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