What Is Data? The Role of Data in Business

Data is a term that has been around for a long time and is very common in the Industry 4.0 technology era. Thanks to data, information on computers is stored and transmitted quickly. So What is Data? What role does Data play for businesses today? The article below from Mona Media will answer these questions for you.

What does the term Data mean?

Definition of the term Data

Data is simply figures, bits of information, but it is not information itself. When data is processed, interpreted, structured or presented to make it meaningful and more useful, it is called information.

“Data” and “information” always go hand in hand. Whether they can be used interchangeably depends partly on how “data” is used, that is, its context.

Examples of the concepts of data and information:

• Recorded temperature figures are called data. If this data is organized and analyzed to show that global temperatures are rising, that is information.
• The number of visitors to a website from each country is an example of data. If the numbers are analyzed and show that traffic from the US is increasing while traffic from Australia is decreasing, that is called information.

Basic types of Data

Today data exists everywhere and in almost every field. Whether you are a data scientist, a marketer, a business owner, a data analyst or work in any other profession, you need raw data or structured data. This data is very important to us, so processing and storing it correctly without any errors becomes essential. When working with this data, you need to understand it well. There are two main types of data:

Qualitative data: also known as categorical data, can be measured or counted in numerical form. These types of data are arranged by category, not by number. That is why it is also called categorical data. This data includes sound, images, symbols or text. A person's gender, i.e. male or female, is qualitative data.

Example: The language you use, colors, hobbies,…

Qualitative data tells us about people's perceptions and helps market researchers understand customer tastes and then come up with suitable ideas and strategies. It is divided into two further types of data:

• Nominal Data: Nominal data is used to label variables to distinguish them from each other. Hair color can be considered nominal data, since one color can be compared with another. For example: hair color (black, brown, red,…), nationality (Vietnam, Laos, Thailand,…), marital status (single, married, divorced),…
• Ordinal Data: Ordinal data is qualitative data whose values have a relative position. These types of data can be considered to sit between qualitative and quantitative data. Ordinal data only shows sequences and cannot be used for statistical analysis. For example: when companies ask for feedback, experience or satisfaction on a scale of 1 to 10; letter grades in exams (a, b, c, d…); the ranking of teams in a competition (first, second, third, etc.); economic status (high, middle and low); education level (postgraduate, secondary, primary).

Quantitative data: Quantitative data can be expressed as numerical values, meaning it can be counted and used in statistical data analysis. This type of data is also called numerical data.

Example: The price of a phone, a person's height or weight… are quantitative data.

Quantitative data can be used for statistical manipulation and can be represented with many charts such as bar charts, line charts, pie charts,… and it is divided into two further types of data:

• Discrete Data: Discrete data contains values that are integers or whole counts. This data can be divided into decimal or fractional values. For example: the total number of students present in a class; the cost of a mobile phone; the number of employees in a company; the total number of participants in a competition; the days in a week,…
• Continuous Data: Continuous data represents information that can be divided into smaller levels. A continuous variable can take any value within a range. For example: a person's height; the speed of a car; Wi-Fi frequency; market share price,…

The meaning of Data

The computing concept of data came from the research of Claude Shannon, an American mathematician known as the father of information theory. He laid the foundation for the concept of binary digital technology based on applying the two Boolean logic values to electronic circuits. Thanks to this concept, experts used binary digital technology as the foundation for the CPU, semiconductor memory and disk drives, as well as many other devices common in computers today. at first they only applied it to control devices and data in the form of punched cards, later extending to magnetic tape and hard disks.

Early on, the importance of data in business computing became clear from the popularity of the terms “data processing” and “electronic data processing”, which people commonly know as information technology. In the management of enterprise computer software, specialization emerged and the development of corporate data advanced further.

Terms related to Data

Data is a common term in the information technology field. If you want an in-depth understanding of this field and of Data, you can learn the related terms experts often use, such as:

• Data Acquisition: Data collection is the process of capturing measurement signals and converting the resulting samples into numeric values.
• Database: A database is a collection of related data that is stored and accessed from a computer system.
• Data Block: A data block is the smallest logical unit of storage in Oracle Database.

Why Data matters to businesses

Guiding business decisions

Businesses regularly collect user data such as personal information, habits and traffic to build a consumer database. All of that data has real potential to grow your business if you know how to use it.

Small and medium-sized businesses can gain the same advantages as large companies when they use data properly. Businesses can mine data to make decisions about:

• Finding new customers.
• Improving customer retention.
• Improving customer service.
• Managing marketing campaigns better.
• Tracking social media engagement.
• Forecasting sales trends.
• In short, data helps businesses make smarter decisions for their company.

See also:

• Methods for collecting customer data
• How to collect leads' email addresses effectively

Update regularly

Data is the fuel for the marketing strategy of every company. It helps you understand how customers interact with your brand, how users behave on social media, which content they like most and which channel brings the best return on investment (ROI).

If you have a database full of customer information, you can use it for relevant, specific targeted ad campaigns based on their interests and location. Data helps you make sure every campaign is running at its best and keeps delivering results.

Improving internal operations

With the right data, tracking the company's performance against the goals it has set becomes easier. Data can help optimise areas that are not well managed, such as supply chain management or logistics planning, which directly affect your profitability.

It can also help you streamline your own operations and cut the time you spend on work that brings little benefit. It can help reduce human error when problems happen, such as a production issue that leads to lost sales or damages your reputation.

Improving financial management

Besides helping you grow revenue, data lets companies improve financial management. You will also get a clearer view of the business's spending habits. As a result, you can see how the company budget is being allocated and whether the expenses are reasonable. Tracking and evaluating your revenue also becomes easier when you know which factors affect it, such as which region, product or service generates the most revenue and where the revenue comes from. Your data will show you the areas with room to grow in the future and let you allocate resources more effectively.

Important types of Data for businesses

Every business has challenges that data can help solve. However, different industries work with different types of data because of their own characteristics. Below are some examples of how different businesses use certain types of data:

• E-commerce businesses: They use customer analytics, media analytics, website analytics, digital marketing analytics, sales and online marketing figures, and other information related to their business.
• Healthcare companies: They regularly update data on medical records, lab reports, hospital information systems (HIS) and research and development (R&D).
• Government agencies: Government bodies use various types of data related to their services, such as crime statistics, employment trends, economic indicators, census information and environmental status reports.
• Educational institutions: They focus mainly on collecting metrics for educational assessment, enrolment management or campus safety.

Today, data has become one of the basic factors in growing and running a business. If your business does not know how to handle data, it is at real risk of being left behind.

With the growth of digital technology, processing data is no longer as hard and complicated as it used to be. There are now many tools a business can use to analyse company data and get more value from it. In this article, we have shared the basics of data along with some types of data businesses commonly use in each field.

See more: What is Data Driven? Applying Data Driven in business