Big Data Introduction

Big data refers to extraordinarily big datasets which cannot be processed and analysed with conventional data processing tools and procedures because they are either too massive or complex. The “3Vs” of volume, velocity, and variety, which stand for vast size, rapid rate of data collection, and diversified nature of the data, respectively, are frequently used to describe big data.

Big data is generated by a wide range of sources, including social media, online transactions, sensor data, and internet of things (IoT) devices. It has the potential to be used to drive innovation and improve decision making in a wide range of industries that include healthcare, finance, retail, and manufacturing.

To effectively analyse and use big data, organisations typically need to use specialised tools and technologies, such as Hadoop and Spark, which are designed to process, understand and analyse large datasets in a distributed manner. These tools enable organisations to store, process, and analyse big data at scale, and they are an important part of the modern data landscape.

Overall, big data is a rapidly growing field with many exciting opportunities for professionals with the right skills and expertise. It is a key enabler of innovation and improved decision making in a wide range of industries, and it is likely to continue to play a significant role in the complete development of data-driven technologies.

Big data refers to extraordinarily big datasets that cannot be processed and analyzed with conventional data processing tools and procedures because they are either too massive or complex. The “3Vs” of volume, velocity, and variety, which stand for vast size, rapid rate of data collection, and diversified nature of the data, respectively, are frequently used to describe big data.