Big Data Concept. By Robinson A.

 What is Big Data ? Big data can be defined as a large amount of data collection made up of  Structured, Unstructured and semi structured that keeps growing over time, these data are too large for a regular hard drive to hold. The more technology grows more data sure as connectivity, Mobility, the internet of things (IoT) and the artificial intelligence(AI)  are been collected and the data keeps growing. More Big Data tools are created help companies collect and process all these data at a required speed and size. The 3Vs of Big Data. Big data can also be describe using the 3Vs Volume, Velocity, and Variety these were the first definition by Gartner in 2021. Volume . this is the high Volume of Data available to be collected and process from sources and devices on a daily bases. Velocity: This is the speed at which data's are been generated, most of these big data are been process in real time  so it requires a high speed generate these dates Variety : Big data ...

The Value of data. The value of data encompasses its current and future potential to drive insights, innovation, efficiency, and competitive advantage for organizations across various sectors, Let's explore some significant of value of data, including its future implications: What is the Value of Data. 1. The Immediate Value of Data: Data holds an immediate value for businesses, organizations, and individuals. It informs decision-making, enhances efficiency, and drives innovation. For companies, data aids in understanding customer preferences, optimizing supply chains, and predicting market trends. Individuals benefit from personalized recommendations, targeted advertising, and seamless online experiences. 2. Monetization of Data: Organizations can monetize data by selling insights, licensing data sets, or creating data-driven products. The future value lies in the potential revenue generated from data-driven strategies. Organizations can sell access to their data, offer data-dri...

Growth of data  The growth of data, often referred to as data proliferation or data explosion, is a phenomenon driven by various factors such as technological advancements, digitalisation of processes, increased connectivity, and the widespread adoption of Internet-connected devices. This growth is characterized by an exponential increase in the volume, velocity, variety, and veracity of data. these measures of data growth presents both opportunities and challenges for organizations seeking to harness the power of data for insights, innovation, and competitive advantage. Effective management, processing, and analysis of big data require a combination of technology, expertise, and organizational capabilities. The world of data growth and its impact: Global Data Creation The total amount of data created, captured, copied, and consumed globally has been on a rapid rise, ln 2020, the world witnessed 64.2 zettabytes of data and over the next five years (up to 2025), global data creation...

The Characteristics of big data analysis (including visualisations)  Big data analysis is characterized by several key features that distinguish it from traditional data analytics, These characteristics reflect the challenges and opportunities posed by the vast volumes, variety, velocity, and complexity of big data. Here are some key characteristics: The Characteristics of big data analysis  1, Volume:   The sheer amount of data generated and stored, deals with extremely large volumes of data, often ranging from terabytes to petabytes and beyond. Traditional data analysis techniques may struggle to handle such massive datasets efficiently. 2. Variety:  Big data comes in diverse formats and types, including structured data (e.g., databases), semi-structured data (e.g., JSON, XML), and unstructured data (e.g., text, images, videos). Big data analysis must be able to handle this variety and extract insights from multiple data sources. 3. Velocity:   Big data i...