What Is Data?
Data in simple terms is nothing but a collection of facts that can be stored and analyzed for various purposes.
Let's visualize it:
Imagine you have building blocks of different colors, they are fundamentally so small and so bright in color and yet they may or may not mean anything to you but when combined with other similar pieces they form structures. Big colorful beautiful structures where each piece contributes in a way that can be neglected when looked at the whole structure but when it is analyzed on an atomic level each piece plays a significant role in aiding the formation of the structure.
Data is just like building blocks, a fact alone may or may not mean anything much but when combined with other collections or facts it sheds light on the bigger picture in the study.
When talking about data one can simply ask, how is data created?
Throughout our everyday lives, we often unknowingly leave behind clues that can provide deep insights into our personalities and mental well-being. By closely examining these traces, others can gain a better understanding of who we are as individuals. This data, if properly utilized, can reveal aspects of ourselves that we may not even be aware of.
Example:
The objects we own and interact with daily can reveal a lot about our lifestyle, interests, and values.
Digitally we are no different, the amount of data we produce has exceeded our capabilities. Unlike our physical world data, digital data can be collected and analyzed on a much deeper level. With society's increasing reliance on technology, more and more of our tasks are being shifted to computers, leading to a continuous influx of data being generated every day.
This is where there came a new field into the picture that combines the mathematical prowess of primitive powers with the computational speed and accuracy of computers, known as data science.
Big Data
Due to the shift of our lives towards a digital age, the amount of data we generate online has increased significantly. This is where a new term related to data comes into play, Big Data.
Big Data refers to large data sets that are generated at a rapid pace from different sources. Example: Assets we upload on social media sites like images, and textual data.
Big Data is described by 5 characteristics also known as the 5 V's of Big Data:
- Volume
- Variety
- Velocity
- Veracity
- Value
Volume
Volume refers to the size and amount of big data companies manage.
Example:
On Instagram, 95 million photographs are shared every day on average.
Variety
Variety refers to different kinds of data that are generated by us.
Example:
In today's age data comes in different forms such as PDFs, photos, videos, audio, and so much more.
Velocity
Velocity refers to the speed with which data is generated.
Example:
Data that is generated with high velocity would be Twitter messages or Facebook posts
Veracity
Veracity refers to the accuracy, quality, and reliability of the collected data.
Value
Value refers to the benefits that big data provides
Being able to pull value from big data is a requirement, as the value of big data increases.
Emergence of Data Science
Data science is a field that uses mathematics, statistics, scientific methods, and algorithms along with a unique blend of computer science to extract insights from data.
Although still known as a new and emerging field, data science finds its roots back in the 1960s and 1970s when computer scientists started to find ways to combine mathematics along with the speed of computers to analyze and process large amounts of data and they weren't wrong in doing so, in 2000s data science gained widespread recognition due to the growth of the internet and emergence of social media sites that completely altered the way we live and interact.
Business Analytics: A Subset of Data Science
Business analytics and data science are two closely related fields that are integral to the success of modern businesses. While the two disciplines have distinct focuses and methodologies, they often complement each other.
Business analytics is just a subset of data science or more specifically business analytics is a clear application of how data science can be used by businesses to improve business operations, increase revenue, and drive growth.
Data science is a broader field that encompasses a range of techniques and tools for analyzing and interpreting complex data sets. While business analytics focuses on improving decision-making based on concrete proof that lies in the collected data hidden and waiting to be discovered.
Example:
Big Data provides a vast amount of data coming at high speed, but simply gathering the data is not enough in any manner. This is where data science comes into play. Data science not only helps in collecting and refining the data but also offers a chance to analyze and uncover valuable insights. These insights from the data from the data can be used to enhance company strategies to increase revenue and improve customer satisfaction.
Where Are We Heading?
One cannot deny that data science is revolutionizing the way we approach and solve problems across a multitude of industries. The vast amounts of data being generated daily provide immense opportunities for innovation and growth. However, one cannot forget that every tool we create lays two sides of a coin, challenges such as data privacy, bias, and ethical considerations must be carefully navigated to ensure the responsible use of this powerful tool.
As we continue to advance in the field of data science, we must harness its full potential for the betterment of society. With a thoughtful approach, data science has the potential to propel us toward a more informed, efficient, and equitable future.
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