Big Data: What It Is and How It Can Be Applied to Business

Big data has an important role in this digital era where information or data is a vital asset in decision-making, especially for business activities.

Its application to businesses has great potential to develop products, maintain operational performance, optimize efficiency, and increase the user experience. That way, a company can have a bigger chance to win the competition and improve its performance.

So, how do you apply big data to increase business profits?

Before knowing the steps, first understand what big data is, its characteristics, functions, how it works, and its application to business in the following guide.

What is Big Data?

Big data is characterized by a large volume of data collection, a high speed of collection, and a variety of data formats. This data set is very important for companies because it can help them make better decisions to improve business performance.

It's the latest version of the previous database system. What makes it different from the previous database systems is the volume, speed, and various types of data.

Characteristics of Big Data

Big data has three main characteristics known as "3V", namely:

1. Volume

Large amounts of data are involved here. It means that this data set will process high-volume, low-density, unstructured data.

Data can come from various business line sources, ranging from social media, business transactions, and others. The data size can reach terabytes (TB), petabytes (PB), or even exabytes (EB).

2. Velocity

Velocity itself refers to how fast data can be generated, processed, and analyzed. Data must also have a reliable transfer speed so that it can be used directly to get timely and relevant insights.

3. Variety

Variety includes many different types of data. Usually, the data types consist of structured data, semi-structured data, and unstructured data. The various types of data require different approaches to management and analysis.

4. Veracity

The purpose of veracity is to determine the quality or accuracy of data and the level of trust in the information contained in it. The quality of the data can be seen from its accuracy, which can be seen from its arrangement and completeness.

5. Value

Value refers to the value provided by the data and is directly related to its arrangement. The value of the data obtained must be unique for a business to be considered quality.

Big Data Functions

Big data has a strategic function in a business. Here are some of them:

1. Determine the Cause of the Problem

One of its functions is the capability to perform in-depth analysis of large-scale data. The data analyzed comes from various business sources, ranging from customer data to operational data, market data, and others.

The results of the analysis include the identification and understanding of the root causes of business problems. From there, companies can take effective and appropriate actions to address business problems.

2. Basis for Decision-Making

The combination of the internet of things (IoT) and artificial intelligence (AI) with big data can be a powerful strategy to drive business growth.

The combination of these three elements is able to receive, provide, and provide the necessary data and information. This is useful for better decision-making.

3. Detect Anomalies in Business

Real-time data analysis can help companies identify unexpected changes or events that may affect the business, such as decreased sales or operational failures.

With precise and fast anomaly detection, companies can make action plans to reduce the negative impacts that may arise.

4. Save Costs

The three previous functions, namely determining the causes of problems, decision-making, and anomaly detection in business, if done properly, can have an effect on cost savings.

This is because operational costs are used effectively and preventive measures are in place to reduce the negative impact of unexpected events on the business.

How Big Data Works

The way it works involves several stages, namely collecting data, processing data, cleaning data, and analyzing data. Here is a more detailed explanation of each stage:

1. Collect Data

Data collection can be done from various sources, ranging from internal company systems to websites, social media platforms, IoT sensors, public data, and so on. Data is collected in a variety of formats, including text, numbers, images, sound, and video.

2. Processing Data

Processing activities involve transforming and manipulating data so that it can be directly used.

One way to process data is through batch processing. This processing uses large blocks of data over time. These blocks are used to view data sets and shorten the time between data collection and analysis.

3. Cleaning Data

Raw data often has defects, such as missing values, duplicates, typing errors, and so on. In order for the data to be processed, it needs to be cleaned and normalized.

These actions involve removing duplicate data, filling in missing values, correcting errors, and standardizing formats.

4. Analyzing Data

The data analysis uses algorithms and statistical techniques to identify patterns, trends, and correlations. This activity aims to gain an in-depth understanding of the data and reveal valuable information.

Here are some data analysis methods that are often used in the industry, namely:

1. Regression: This method identifies the relationship between two or more variables in a set of data.
2. Classification: Assigning items to multiple labeled categories in a dataset.
3. Clustering: Collecting objects from a group that are similar to one another.
4. Forecasting: Planning and controlling production to predict future demand.

How to Apply Big Data in Business

This type of data can help handle various business activities. Here are some of them:

1. Product Development

Several large companies build predictive models for new products and services. They analyze customer data, feedback, market trends, and other related data to gain in-depth insights into customer preferences, market needs, and industry trends.

That way, they can plan development, production, and launch new products that are more in line with customer needs and more competitive in the market.

2. Predictive Maintenance

Data sets can be used to perform predictive maintenance in industries that use complex equipment or machines, such as manufacturing or transportation.

Companies can predict the factors that contribute to mechanical failure or problems that may occur with equipment.

Later, the prediction results are used to carry out timely maintenance and avoid losses due to equipment damage.

3. User Experience

Today, a good user experience can help increase user satisfaction, improve user retention, and strengthen the relationship between companies and customers. A deep understanding of users can be achieved with big data.

This data set will analyze data on user behavior, preferences, and interactions with the platform. It can be used as a foundation to provide users with a more personal and relevant experience.

4. Fraud Prevention

Data sets can be used to identify indications of fraud and collect large volumes of information. The data used is in the form of suspicious patterns and trends in transaction data, user behavior, or other related data.

From there, the company can file a report and take appropriate countermeasures.

5. Decision Making

Data sets are a critical component in the development and training of machine learning models by providing large, diversified, and representative data volumes.

Companies can train machine learning models to make the best decisions based on the patterns and trends found in the data.

The result of the machine learning model is an increase in operational efficiency and the optimization of business processes.

6. Operational Efficiency

Companies can identify areas that need improvement or increase efficiency through big data. This is because these data sets can analyze operational data, production data, and other related data.

As a result, the company is able to reduce operational costs, optimize processes, and increase productivity.

7. Innovation Drivers

Having a large amount of data can prove to be beneficial as it is a source of information for innovation and development. The information commonly used is market data, consumer trends, and industry data.

Companies can identify new opportunities and emerging trends through this information. From there, companies can improve customer satisfaction and create new products and services.

So, that was the complete explanation of big data, including its characteristics, functions, ways of working, and application to improve your business performance.

Another way to improve business performance is to market it digitally and organically.

SEO services from cmlabs can help with digital and organic marketing. The right SEO strategy allows your business to grow organically without relying on paid advertising.