Big Data describes enormous volumes of data generated every day. These 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-centric products and services.
Big Data is not only “big” because of its volume. It is also “big” because it is highly diverse and complex. This diversity and complexity makes 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 transmit data.
Transaction data: This includes all data generated during purchases, banking, and other transactions.
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 quickly.
Variety: Structured, unstructured, and semi-structured data.
Veracity: The data must be accurate and reliable.
Value: The data must provide value for companies.
By analyzing Big Data, companies can gain valuable insights. These insights can help them:
Improve products and services,
Reduce maintenance costs,
Improve the customer experience,
Manage risks more effectively,
Save costs and work more efficiently,
Become more competitive.
