When people say data is the new gold, what they are really trying to capture in four words is how much data impacts our lives on every level. Across every sector of development and innovation, data serves as a precursor to sound decision making, finding solutions to our problems, and strategic implementation.
However, many people shy away from handling data because of the sensitivity of it and the technicality of data handling. This article will explore all you need to know about data handling that will help you secure and protect the integrity of data.
What is data handling?
Data handling is an essential concept in statistics that relates to securing data and protecting the integrity of data, regardless of the forms in which it is stored or presented. It is the safe and secure storage and disposal of data during and after the conclusion of a research project. In simpler terms, data handling is the process of securing the storage and disposal of data.
Data handling is an important process in ensuring the integrity of data. Unfortunately, the skills shortage in the data industry has been a huge obstacle to data handling and management. Hence, more people, especially those who already work with data, may benefit from more training and certifications, which can be gained through courses such as a Master’s in Applied Statistics. This would ensure that data handling systems, policies, and procedures are well-developed, safe, and secure.
Types of data handling
There are two major types of data handling based on the type of data:
- Qualitative data handling
Qualitative data handling has to do with the storage and disposal of descriptive information. Qualitative data is usually assessed through interviews, questionnaires, and observations, and appears in a narrative form.
- Quantitative data handling
Quantitative data handling, on the other hand, involves the storage and disposal of numerical information, which can either be discrete or continuous.
Steps in data handling
The process of data handling can be broken down into a few key steps:
- To either identify the problem you want to solve with data, or the purpose of such data.
- Collect the data from relevant sources.
- Present the data in a form that can be easily understood to aid analysis. Data is generally presented in the following formats: pictographs, bar graphs, pie charts, histograms, line graphs, scatter plots, etc.
- Visual representation of data collected.
- Analysis of data to extract useful information for further utilization.
- Arriving at a conclusion or providing a solution to the identified problem.
Things to consider when handling data
Whenever you are handling data, it is important to keep a few things in mind:
- The type of data, the medium of storage, the capacity of storage, and retrieval effectiveness.
- The type of data collected and its impact on the environment.
- The safety of data collected and stored.
- The confidentiality of the process of data collection.
- The data handling procedures, personnel involved, and their responsibilities in the process.
- The integrity of data, either in electronic or non-electronic forms.