Introduction
Big data is a term that refers to any collection of data so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.
Big data is a term that refers to any collection of data so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.
Big data is a term that refers to any collection of data so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.
Big data can be generated from various sources like social media posts, mobile devices, sensors and even images. The term “big” refers to the size of this data in terms of volume (amount) and velocity (speed). For example: You might have 1 TB (terabyte) of images stored on your computer but those images won’t be considered big until you start sharing them with others over the internet!
What Is Big Data?
Big data is a term that refers to any collection of data so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. This can be due to the sheer volume of information involved, as in the case with genomic sequencing or Internet traffic logs; or it can be due to other factors, such as multiple types of data (structured vs unstructured) or highly varied formats (images vs text).
How Big Is Big?
Big Data is a term that refers to any collection of data so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. The term was originally used by computer scientists working with huge datasets generated by scientific instrumentation, such as the Large Hadron Collider at CERN in Switzerland or telescopes looking for signs of extraterrestrial life.
But today, we’re all generating big data–and sometimes without even realizing it! As our society becomes increasingly connected through mobile devices, social media networks like Facebook and Twitter (where everything you share becomes part of your personal “profile”), wearable fitness trackers like FitBit (which collect information about your health), smart cars (which collect information about driving habits), smart homes (which collect information about energy use), etc., more and more people are creating new sources of this type every day without even thinking much about what they mean beyond “I should probably delete this later.”
The Four V’s of Big Data
The Four V’s of Big Data
Volume: The amount of data and its variety are the most basic characteristics of big data. Velocity refers to how quickly information is being generated and processed, while veracity refers to whether or not the information can be trusted.
Big Data And Analytics, Applications
Big data applications can be classified into three categories:
- Analytics, which includes data visualization and predictive analytics.
- Artificial Intelligence (AI), which employs machine learning to train computers to learn from experience in order to make predictions or decisions.
- Internet of Things (IoT), where devices use sensors to collect real-time data about their environment and send it back for analysis by other systems that can take action based on that information
Conclusion
Big data is a term that refers to any collection of data so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.
