Big Data

  Big data means Big data refers to large and complex sets of information that are difficult to manage and analyze using traditional data processing methods. It encompasses vast amounts of data gathered from various sources, including sensors, social media, and business transactions.  The defining characteristics of big data are often referred to as the :  volume velocity variety.  Volume represents the sheer amount of data generated, velocity refers to the speed at which data is collected and processed, and variety indicates the different types and sources of data.  Big data analysis aims to uncover valuable insights, trends, and patterns hidden within these massive datasets to inform decision-making and drive innovation across industries.

The growth of data in today's world is increasing rapidly and unlike anything we have seen before. This is mainly due to the increasing use of technology like the Internet of Thing and artificial intelligence, which has led to a massive amount of data being generated.  We can measure this growth in different ways, such as volume, velocity, and variety. Volume is about the sheer amount of data being produced, with estimates suggesting that 2.5 quintillion bytes of data are created every day. Velocity refers to the speed at which data is generated, and variety covers the different types of data, from structured like databases to unstructured data like social media posts and videos. Managing and utilizing this huge amount of data poses challenges and opportunities for people and organizations alike. Big data  

Historical development of big data (technologies and techniques) : Big data has come a long way since the 1990s when companies began collecting and storing large amounts of data. In the early 2000s, technologies like Hadoop, MapReduce, and NoSQL databases changed how big data was processed and analyzed. These advancements allowed for the storage and processing of huge amounts of data in a distributed computing environment. As big data grew in importance, machine learning and artificial intelligence techniques were used to extract valuable insights from the vast data. Today, big data technologies are rapidly evolving, with cloud computing, real-time analytics, and edge computing shaping the future of big data analytics.