Khalid Nawaz

Khalid Nawaz 14 March 2025    Limitations of Traditional Data Analysis Former techniques for data analysis used to work, but now, they are unable to process data with such a high volume, variety, and velocity as it is today. Most traditional methods are usually related to structured data like in relational databases, so they are not able to adapt to the large and complex data sets in the digital world. The old-fashioned systems also have to rely on more manual data entry and predetermined queries, which are slow and not adaptable to real-time updates and other non-structured information like, for instance, multimedia files and social interaction with customers. Consequently, the observation through these means can be postponed, be partial or be much previously due to the long duration they require, which obstructs prompt decision-making in rapid environments. Finally, traditional data analysis systems are unable to handle increasing requirements. As data level grows with the c...

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...

Khalid Nawaz 9 March 2025     Reasons for the Growth of Data The growth in data is driven by several causes. The digital revolution in sectors has triggered the widespread adoption of digital platforms in commerce, education, healthcare, and entertainment, significantly boosting data creation. The spread of the internet and social media platforms like Facebook, Twitter, and Instagram has led to humongous quantities of end-user-generated content. IoT sensors, smart appliances, wearables, and other gadgets are constantly streaming and collecting data. Online commerce and web commerce generate vast amounts of transactional data, and scientific research in genomics, astronomy, and climatology generates massive data sets. Further, the availability of scalable cloud storage has made storing and managing such massive amounts of data easier, which has, in turn, fuelled data growth. Another major contributor to data growth is the advancement of digital technology in business and m...

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 d...

Khalid Nawaz 5 March 2025                                                             Big Data Introduction  Big data, which includes the collection, storing, analysing, and visualising of vast amounts of structured and unstructured data from various sources, is the term used in computer science to describe extremely large data sets that are too big, too complex, or too fast to process using conventional data processing software or methodologies. Example In today's digital age,  information  is being generated  on  an unprecedented  level . From  Facebook   posts to  Internet   of Things  devices, the  amount   of  information  we  generate   on a  daily  basis  is  overwhelming .  All  this  data  explosion...