7 Essential Examples of Big Data in Real Life
There are many examples of big data in real life that we have used so much. On its own, big data can be defined as a large set of data that is incapable of being processed by traditional data processing software. Without us even noticing, we have used big data more than we thought before.
Through this article, you can learn about every characteristic of big data as well as examples of big data in real life that we often encounter. Let’s see the full explanation below!
Characteristics of Big Data
When we talk about big data, not all large amounts of data can actually be classified as big data. The following are characteristics that can classify certain data as big data.
The volume referred to here is the amount of data generated and stored. The size of the data will determine its value and potential insights, and whether the data can be considered big data or not. The size of big data usually has to be larger than terabytes and petabytes. The volume of big data will usually continue to grow all the time because more and more devices are connected to the internet and sending data.
For example, every time someone uses the internet, they will send and receive data which can be in the form of text, images, audio, or video. All of this data will then be collected and processed by the big data system to be used by companies or organizations.
Variety refers to the type and nature of the data. Usually, those belonging to big data will have various types of data collected from various sources, be it in the form of text, images, audio, or video. The properties of the data can also be structured, semi-structured, and unstructured.
Big data sources also vary, such as data generated by devices connected to the internet, transaction data from companies, log data from systems, and so on. This variation causes big data to become something complex and requires certain techniques and tools so that big data can be processed and understood.
Velocity refers to the speed at which companies receive, store and manage data. Big data has a high speed when it is collecting data, so the collected data must be processed in real time so that it can be utilized effectively.
For example, an e-commerce company with a high number of transactions and sales every day needs to process transaction data in real-time to manage stock and improve customer service. If it is not immediately processed in real time, the data will accumulate without a clear purpose.
Veracity refers to the quality and value of data, specifically the level of accuracy and reliability of the data. Big data not only has to be large but also has to be reliable to achieve the desired value in its analysis. The quality of the collected data is often unstructured and inaccurate, so it needs to be processed carefully to avoid errors in interpretation.
Veracity is a very important characteristic because inaccurate big data can produce wrong values and even harm a company or organization. Therefore, there needs to be an effective mechanism to ensure that the big data used is accurate and trustworthy.
To increase the veracity of big data, certain techniques are needed, such as data cleansing, data scrubbing, and data validation. These techniques can help eliminate inaccurate or duplicate data so that the remaining big data will be more accurate and reliable.
Value refers to the information value that can be achieved by processing and analyzing big data sets. Big data has high value for companies and organizations because it can be used to help make strategic decisions and improve business efficiency.
Examples of using big data to increase profitable value for companies include:
- Analyzing customer data to find out their needs and preferences so that they can offer products or services that suit those needs.
- Using transaction data to determine sales trends and adjust stock according to demand.
- Utilizing system log data to identify existing problems and seek appropriate solutions.
- Using data from social media to deduce customer sentiment towards the products or services offered by the company.
By using big data, companies can make more informed decisions and improve business efficiency. The data value of the company as a whole can also increase its worth from both an economic and social point of view.
The Usage of Big Data in Our Daily Life
In our daily life, a lot of big data is collected and processed. The following are some examples of big data in real life.
1. Customer Transaction Data in E-Commerce Companies
E-commerce companies such as Amazon and Tokopedia collect data about their customers’ transactions, including products purchased, purchase amounts, and payment methods. This big data is useful for knowing customer preferences and suggesting products that these customers might buy.
2. Supervision System Data in Manufacturer Companies
Manufacturing companies collect data from sensors installed on their production machines to monitor machine performance and identify problems before any downtime occurs. Big data is useful for increasing the efficiency of the production process, preventing problems from occurring, and reducing machine maintenance costs.
3. Social Media Data
Social media such as Facebook, Twitter, and Instagram collect data about the activity of their users, including uploads and posts, comments and replies, and interactions with content. Big data is useful for understanding trends and behavior patterns of social media users and presenting advertisements that are relevant to user interests.
4. Weather Forecast Data
Weather stations collect data about the weather around the world, including temperature, humidity, and precipitation. This big data is useful for predicting the weather in the coming days and taking preventive steps to avoid natural disasters.
5. Traffic Monitoring Data
Apps like Waze and Google Maps collect data about traffic currently happening on the roads. This big data is useful for providing up-to-date information to its users regarding the shortest or fastest routes to certain locations so that users can reduce traffic jams and increase travel efficiency.
6. Genomic Data
Genomic data is data that describes a person’s entire genome (genetic code). Big data is useful for identifying genetic patterns that might cause disease or predisposition to certain diseases.
7. Health Monitoring Data
Apps like Fitbit, Apple Health, and Google Fit collect data about their users’ physical activity and health conditions, such as the number of steps taken and heart rate. This big data is useful to help users maintain their health condition and suggest actions to maximize their body condition.
After knowing the examples of big data in real life above, now you definitely understand how important big data is. To help process big data in your company, you can use EKYC from AdIns which can help track prospect profiles more easily. Want to give it a try? Contact us here to conduct a service trial from AdIns or if you want to find other AdIns services that your company needs!