Big Data: What Is It?
Big Data describes enormous amounts of data that are generated every day. These data volumes are so large that they are measured in zettabytes. They are generated by computers, smartphones, and electronic sensors. Companies can use this data to make better decisions, improve processes, and develop customer-oriented products and services.
Why “big”?
Big Data is not only “big” because of its volume. It is also “big” because it is very diverse and complex. This diversity and complexity make it difficult to capture, manage, and process with traditional databases.
The data can come from various sources. Three important sources are:
- Social data: This data is generated through comments, posts, images, and videos on social media.
- Machine data: Machines and devices in the Internet of Things (IoT) are equipped with sensors. These sensors capture and send data.
- Transaction data: This includes all data generated during purchases, banking transactions, and other transactions.
The 5 Vs
Data must meet five characteristics (in English, the 5 Vs) to be considered Big Data:
- Volume: The amount of data must be enormous.
- Velocity: The data is generated very quickly and must be processed rapidly.
- Variety: Structured, unstructured, and semi-structured data.
- Veracity: The data must be accurate and reliable.
- Value: The data must have value for businesses.
Benefits
By analyzing Big Data, companies can gain valuable insights. These insights can help them:
- Improve products and services,
- Reduce maintenance costs,
- Enhance customer experience,
- Better manage risks,
- Save costs and work more efficiently,
- Become more competitive.
Artificial Intelligence and Big Data
Analyzing these large amounts of data is hardly possible without artificial intelligence (AI). AI systems need large amounts of data to learn and improve their performance. Conversely, the data cannot be meaningfully analyzed without AI.
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