Handling Data Data

6 Steps for Handling Data Without Missing Any Data

Data analytics is one of the hot professions today. If you have the right expertise, you can find online jobs and kickstart your career. Not only is it a great career for people who have done excel courses, but it also offers you to learn more and strengthen your position as a data analyst.

While it may be a fun learning activity, data handling requires you to be very attentive. Otherwise, you could miss a valuable piece of data, which may lead to wrong results. And nobody wants that.

But how can you avoid losing any data? Well, keep on scrolling to find out the steps for handling Data.

What is Data Handling?

Data handling is the process of collecting a particular set of data and presenting it in a different form. Data can be referred to as a collection of information gathered through observations, research, or analysis.

Image source: Pixabay

Data can be in any form. It may consist of words, numbers, facts or observations, and even a general description of things. Making it useable is what we call data handling. It involves: gathering the data, recording it, and presenting it in a way that makes it easy to analyze.

Considerations in Data Handling 

There are a few considerations while collecting data for data handling:

  • The data should be relevant to the problem or purpose.
  • The incorrect prediction may result due to inaccurate or missing data. These can be null values in columns and relative or missing images from the source, etc.
  • Inconsistency in data can also cause issues in data handling.
  • Data collected should be from authentic sources.
  • Data should not be difficult to comprehend to not be able to be read by a computer.

Steps for Handling Data Without Missing Any Data

Data handling cannot just be done haphazardly and randomly. The data has to go through a certain process for it to be analyzed, studied, and researched. Here are a few steps that you can follow for data handling:

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Problem Identification

The first and foremost thing is to identify and define the problem statement. This is because then it will narrow down our research for collecting data. If our problem statement is all over the place it will be easy to get lost in the abundance of research material available at your disposal.

The problem needs to be explained and described in a way that is easy to comprehend. It should also help you define your research parameter so that you only gather data that is useful for handling data.

Data Collection

In the next step, we will collect information and data that will help us gather the data related to this problem in one place. The data relevant to the problem statement is will collected. Data collection is about targeted variables that are defined as data requirements. Emphasis is placed on ensuring accurate and honest data collection. 

The data set ensures that the collected data is accurate so that relevant decisions can be made. It is the basis for measurement and improves the goal. If the amount of data is huge, and you have to find it, the traditional way of searching for it is not convenient to use. 

You can make data collection and data handling easy by using some tools like Microsoft Excel. Its functions, particularly VLOOKUP and IF-ELSE, help you find a particular kind of information corresponding to a variable from a large sheet with ease.

In addition, VLOOKUP is not just meant for collection. You can use it while analyzing the data as well. Then there are other tools listed in the analysis stage. 

Data Presentation

At this stage, the focus is on presenting data. The collected data should be presented meaningfully and in a way that it can be easily understood. This can be done by sorting the data collected in table symbols, table forms, and so on.

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Data presentation is important as it allows people to understand the kind of information that is being conveyed. If the data is presented in a way that makes it incomprehensive then the process of data collection and researching all becomes futile.

Graphical Representation

One of the most important steps is to visualize the data. This is so that we can have a graphical representation of it. The visual or graphical display of data facilitates analysis and understanding. 

Handle Data, Data

Image source: Pixabay

Therefore, the data presented can be plotted in graphs or charts such as bar charts, pie charts, and so on.

Data Analysis

It is a process in which the person or system analyzes the information entered. Data analysis techniques are available to understand and draw conclusions according to requirements.

The data should undergo data analysis so that you can derive necessary information from it. This helps in taking further decisions in regards to proceeding with data handling. 

Furthermore, data visualization helps in analyzing the data with a naked eye. Graphical formats and tables make it easier for the analyst to draw conclusions.

Data analysis is a vital concept in business management. Many jobs are data-based. This means that they need to continuously provide accurate and valid data. For this purpose, you have many different software tools, but Excel is more popular than any other tool.

Microsoft Excel provides several methods for analyzing and interpreting data. How?

Data comes from different sources, and Excel offers multiple ways to format it. Moreover, you can analyze it using Excel commands, functions, and tools. These tools include:

  • Conditional formatting
  • Data validation
  • Data sorting
  • Query tools (such as the Audit Formula) 
  • Functions (such as Data, Time, Financial, Preamble distribution, and more)
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With Microsoft Excel, data analysis will be accurate, and you won’t miss any value. 

Output

At this stage, the researcher makes judgments about the information presented. Therefore, it is vitally important not to miss any data to get a complete picture. This helps researchers and analysts to deduce the results as accurately as possible.

You need to study the results of the data analysis. This allows for direct interpretation of the data. 

The processed results help you in predicting and forecasting, which will help top management take the right decision. It will help you to be ready for new developments and changes in the future.

Final Words on Steps for Handling Data Without Missing Any Data

Data handling is an important task as it involves comprehending information that comes into contact with us daily. Data is part of our daily lives as it is everywhere. 

So, it is important to make sense of so much information that is available to us so frequently. This amount of data needs to be carefully managed and handled.

Data handling can become a bit tedious especially when it involves collecting large quantities of data. It can be in any shape or form and can be represented in several ways.  

There are a few techniques that can be used to make data handling convenient and without any hassle. You can get help from certain software and applications in managing and handling data.

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