Growth Of Data

Khalid Nawaz

7 March 2025 





 

Growth Of Data

The growth of big data has been exponential in recent years, driven by the rapid advancement of digital technologies and the widespread use of connected devices. Every day, massive amounts of data are generated from various sources such as social media, mobile devices, sensors, and online transactions. This has resulted in an unprecedented surge in data volume, expected to exceed 180 zettabytes globally by 2025. Alongside the volume, the speed at which data is produced—referred to as velocity—has increased due to real-time applications like video streaming, financial services, and Internet of Things (IoT) systems.

Moreover, the variety of data types has expanded, encompassing structured data in databases, semi-structured formats like JSON, and unstructured content such as videos, emails, and social media posts. This diversity adds complexity to data management but also offers valuable insights when analysed effectively. The growing demand for data analytics, artificial intelligence, and machine learning has further accelerated the importance of big data. However, this growth also presents challenges related to data security, privacy, and quality. As big data continues to evolve, businesses and governments are investing heavily in infrastructure, cloud computing, and data governance to harness its full potential and drive informed decision-making.       



Comments

Post a Comment

Popular posts from this blog

Application of big data techniques to a problem 4

Image
  Application of Big Data Techniques A high dropout rate — 28 percent of freshmen in one program — is a major obstacle in online STEM education. Teachers collected a huge amount of data to attempt to tackle this, including assignments submitted, posts made in forums, marks on quizzes, views of video lessons and actions in LMS logins. After detecting stress and disengagement indices from chat contributions via natural language processing (NLP), regression models were used to predict who among the students would be at risk of performance dropout. Cohort dropout risk heatmaps, weekly teacher trend reports, and individual student engagement dashboards were applied to visualize this data. These findings enabled more targeted interventions: teachers were automatically alerted to reach out individually to students showing early warning signs, those at risk received specific prompts (e.g., offers of tutoring, inspirational messages, or resources); and teachers were given individual feedbac...
Read more

Application of big data techniques to a problem 1

Image
  Explaining Big Data Concepts Massive amounts of data are coming out of educational platforms because of the rapid growth of online learning, everything from discussion forum activity and video watch time to the frequency of login and assignments submission available. The titanic volume of data, often called “big data,” is being utilized by institutions for the purpose of the improvement of learning results and for the thorough understanding of student behaviour. Edutrack is one such example, where the amount of data annually went up from 1TB to over 10TB, making it necessary to use smarter data strategies instead of manual ones. This comprises, among others, the situation when manual progress tracking was the main method of monitoring, and the end-of-semester survey was the instrument that gave the teachers clues about the best topics for the next semester. The effective scope of the latter was not only limited by its low response rates but also by the time taken to supply an inp...
Read more

Value of Data

Image
Khalid Nawaz 10 March 2025    Value of Data (Including Future Value)  In today’s digital era, big data has become one of the most valuable assets for organizations across industries. It allows businesses to gain deep insights into customer behaviour, preferences, and trends, enabling more informed decision-making. By analysing large volumes of data, companies can optimize marketing strategies, improve product offerings, and enhance customer service. For example, retailers can use purchasing data to forecast demand, personalize recommendations, and manage inventory efficiently. In the healthcare sector, big data supports early disease detection, patient monitoring, and more effective treatment plans by analysing patient records and medical histories.  Governments use it to improve public services, monitor traffic patterns, and respond to emergencies. In agriculture, data from sensors and satellites helps farmers monitor crop health and manage resources more sustainabl...
Read more