Data is the currency in today's world, and data translates to power and authority. So everyone is always competing with one another over data to gain the upper hand. Data is categorized based on two factors: its extraction source and the method used to extract it. Based on these factors, data can be categorized into two kinds: Hard Data and Soft Data. Today I shall give you an overall comparison between the two data types, i.e., Hard Data Vs. Soft Data.
What is Hard Data?
In simple terms, hard data is any data that is quantitative, meaning this data can be measured. Graphs, tables, and numbers can represent them. Hard data can be gathered from a long list of sources, including and not limited to computers, phones, smartphones, meters, sensors, etc.
Also known as factual data because this data is methodologically collected and can easily be traced. This ensures that the data collected is valid and obtained from reliable sources. Based on collection methods, Hard Data can be categorized into two types. Let us see what they are.
How Can You Collect Hard Data?
Hard data can be collected from various sources, for example,
- Polls and Surveys
- Votes
- Internet
- Sensors and meters
- Questionnaires
- Experimentation
What are The Types of Hard Data?
Based on the collection method, hard data is of two kinds:
Primary
Primary data collection is the accumulation of information through various mathematical and scientific procedures. These procedures include questionnaires, polls, statistics, etc. These are all forms of quantitative data collection and analysis. As these methods and procedures for data collection are all conducted following strict rules and scientific regulations, the resultant accumulated data is not only reliable but also accurate and free from any sort of contradiction and bias.
Secondary
In this method of data collection, all the information collected is from sources that are related to the subject matter. These sources include journals, newspapers, research documents, books, publications, etc. When choosing any of these sources, strict rules and requirements are set and followed. This ensures that the data collected is reliable, credible, and accurate.
For instance, these sources should come from trusted and renowned authors or individuals with proper credentials. This method of data collection is faster; however, it actually doesn't increase the amount of data as these data are not new and they already exist.
Based on sources, hard data is of two kinds:
Research Derived
Just like the name suggests, this data collection is from sources that contain information collected by scientific methodology and procedure. Usually, the data collected from research are well organized, structured, reliable, and, most importantly, trusted. This research is conducted by experts and professionals, and individuals who hold credibility and authority. For instance, controlled experiments, questionnaires, surveys from sample audiences, etc.
Technology Derived
Technology-derived data means any and all data and information collected from devices and machines. This includes everything starting from smartphones and computers to even temperature readers and meters. The data extracted from these sources are always reliable and valid, given that the devices are calibrated and functioning properly.
What is The Importance of Hard Data?
Hard Data is an important resource for a lot of reasons, which include:
- Research and analysis.
- Statistics
- Forecasting and prediction
- Study
- Trend analysis
- Behavioral patterns
- Optimization
What is Soft Data?
Soft data is any information that does not adhere to the standard research procedures and methodology. Soft data is, at its core, qualitative data. For instance: it includes information gathered from opinions, personal interpretation, hypothetical scenarios, etc. To put it another way, soft data is based on things that are commonly attributed to humans. It is extremely difficult to measure or estimate in exact numbers due to the nature of the phenomenon. As a result of this, soft data has earned the reputation of being less reliable than other types of data.
However, despite the absence of scientific proof, soft data are frequently utilized as a supplement to hard data in order to provide a more comprehensive picture. The fact that soft data is collected on an individual basis enables organizations to develop a more in-depth comprehension of the behaviors, motives, requirements, and reactions of their customers. This, in turn, leads to the development of an effective plan to communicate with customers and fulfill the requirements they have set forth. Because of this, when coupled with hard data, it performs an extremely important part in the process of strategic planning.
What are The Types Of Soft Data?
Soft Data is of two types:
Study and Interview. Derived
Soft data, collected by methods like interviews and focus group discussions (FGD), is theoretically analogous to the hard data acquired, which is obtained through rigorous analysis. However, the information being gathered is very different from what is typically acquired. In order to understand more, the technique uses free-form questions rather than definitive answers. Knowledge of opinions, ideas, attitudes, assessments, experiences and other types of subjective information is acquired in this process.
Because of the specifics and individuality of each inquiry, their results cannot be generalized or considered representative.
Internet Derived
Soft data can be easily extracted and obtained using the internet. This includes product reviews, comments, social media posts, interactions, etc. A lot of information can be extracted from the internet that can be used to determine market trends, customer behavior, product pricing, etc.
How Can You Collect Soft Data?
Soft data can be collected by different means. Some of the most common ones are:
Through FGDs
An FGD or focus group discussion is one in which a control population of people is broken up into smaller groups and guided through the process by a moderator. The goal of taking such an approach is to learn more about a particular subject. Most people who take part in focus groups have something in common.
Conducting Interviews
This method is also used to collect data that can be used to make decisions. The questions asked of the respondent are what set the two types of tests apart. Soft data is gathered through interviews that are more conversational and relaxed.
The questions that arise from a conversation usually take on whatever shape the talk takes. Typically, this method involves asking a wide variety of free-form questions. The reason for this is the emphasis placed on one on one interactions.
Conducting Case Studies
This method of information extraction is done by digging into past events, situations, or processes to gather information on the subject matter or related information. This method can be used for any sort of information extraction.
Through Incognito Research
In most studies, the researcher is required to live in the same conditions as the participants. Researchers are usually able to conduct interviews with participants who are unaware that they are participating in a study because the researchers remain incognito.
What is The Importance of Soft Data?
Soft data is necessary because of a wide array of reasons, such as:
- It serves as a foundation for in-depth research
- It provides information for analysis
- It demonstrates customer intent
- It provides insight into marketing and advertisement.
- It gives a different perspective
- It works well in conjunction with hard data.
Hard Data Vs. Soft Data
| Hard Data | Soft Data |
|---|---|
| Quantitative data. | Qualitative data. |
| Factual data. | Hypothetical data. |
| Collected using technology. | SCollected using observation |
| Provides measurable data | Provides reasoning behind data |
| Sources: research, scientific methodology, etc. | Sources: interviews, observations, social media, etc. |
| Uses forecasting, statistics, analysis, optimization, etc. | Uses market research, product, and service analysis, etc. |
| Data that is measurable tracked, traced, and credible | Data that is contradictory, opinionated, hypothetical, and suggestive |
| Technology derived and quantifiable | Derived from human interactions and observations |
The main difference between Hard Data and Soft Data exists because of two main factors:
- The sources from which they have been extracted.
- The method by which they have been extracted.
However, differentiating Hard Data and Soft Data is becoming more challenging each day. The reason for that is automated data extraction methods. These automated techniques of data collection provide comprehensive data collection, with little differentiation made between the many types of data that are collected. Web Scraping is the most common means of data extraction these days.
Role of Web Scraping
Web scraping is a method of data extraction that involves the use of scrapers to collect information and data automatically from websites. There are both hands-on and hands-off approaches to performing this task. On the other hand, the automated method is the one that is used more frequently because it is both significantly quicker and more accurate.
Data scrapers are computer programs that can automatically extract and organize data based on the requirements set forth by the user.
In spite of the fact that it is such a quick and dependable method of data extraction, it is sensitive, and the question of whether or not it is legal is the subject of much debate. Because of the close relationship between data and information and privacy, it is frequently simple to violate rules and laws in this area if one is not careful.
The Verdict
Now that you have a better understanding of the comparison between Hard Data and Soft Data, you can easily see that it all comes down to a few basic things: sources and extraction methods. But with the increasing use of the internet globally, the sources have become lesser and more common, and due to the vast amount of data, the extraction methods also became automated. This is all a result of automated data extractors called scrapers.
If you wish to learn more about scraping, then please check out this link.
Happy data mining, and don't forget to share this article with your colleagues 📧