Big Data is an emerging field, and nowadays, it is catching the eyes of everyone in the information age. We all know about the average Data that we usually store in our computers or smartphone in the form of multimedia, contacts, documents, and other files in general. All these things represent normal Data. But, when it comes to Big Data, many of us often are mislead by complicated jargon and some odd use-cases.
In this segment, we have covered the meaning of Big Data, its main characteristics, and some use-cases that makes it so valuable. Applications of Big Data probably surround you everywhere. How may you ask? Let us find out.
What is Big Data?
Big Data, in simpler terms, refers to a cluster of data that is produced very rapidly and in a non-uniform manner. It doesn’t end here. Data keeps growing exponentially. It widens so quickly to a point where standard database systems such as SQL cannot maintain it. Nor your computers can keep track of it. Now there are some characteristics of the Big Data.
Characteristics of Big Data (3’Vs of Big Data)
Now that you know what Big Data is, let’s dive into some basic fundamentals. Here we have tried to clear some fog on what makes Big Data stand apart from the standard Data. Later we also try to explain it with some examples; for now, let’s have a look at the characteristics of Big Data. It is famously defined as the 3’Vs of Big Data that includes Volume, Velocity, and Variety.
Volume
In simple terms, it is the amount of data that is generated by anything. Here, for something to be qualified as a Big Data, it needs to generate a lot of data. For example, we can relate it to social media such as Facebook, where it has more than a billion active users who interact with each other, upload images, videos, share posts, like, and connect with others via messages. So its a lot of data that they generate altogether.
Velocity
Going more deep into Big Data, it is evident that it hosts a lot of data. But, even Data Warehouses has a lot of data. So for something to qualify as Big Data, it needs to fulfil another property that is Velocity. It is the rate at which the Data is gathered, accumulated, or generated. Relating back to the Facebook example, every second, a lot of Data is made by its users.
Variety
Now, In Big Data, the Data that it stores is of different types. It can be multimedia data as images, videos, audios, and other documents and text as well. There is no pre-defined structure to this Data, which is generated. Hence, it goes into the category of unstructured data. Let’s see some examples of Big Data.
Examples of Big Data
Social Media is one prime example. Here, as we previously explained, there are millions of users who generate a huge volume of data. Sharing of posts, videos, images, and exchange of messages take place every minute. Thus this satisfies our three characteristics of Volume, Variety, and Velocity.
Search Engine data, as in Google, Yahoo, and other search engines. It consists of millions of indexed links in their database and has all types of it, such as blogs, websites, images, videos, etc. Even here, the Data that is collected every minute via web crawlers are quite gigantic.
Use-cases and Applications of Big Data
Now that we know what can be qualified as a Big Data let’s try to dive a bit into its application and use-cases.
Big Data Analytics
We did collect a lot of data, too much that it qualified as a Big Data. Now, it’s time to perform some actions on the data. Remember how you cannot perform the normal database queries that worked for SQL and other small scale databases?
So to gain more information out of the Data, we go for Big Data Analytics or Analysis. It is a technique to identify existing patterns, correlations, trends from different sets of data to predict and derive actionable insights. It is one of the applications of Big Data and using this, and there are many applications to it in all the sectors such as telecom, media, healthcare, etc.
Competitor Analysis
After gaining a lot of data through surveys, gathering social media data, and other consumer-related data sets, you can identify competition in different actors. Generally, experts do the analysis and give results in the form of new areas to generate revenue, sectors where a company can invest at any point in time, and other insights that dictate an organization’s growth towards profits and revenue.
Healthcare
Big Data is playing a significant role in healthcare nowadays in identifying trends from various sources. Different data sets are collected from hospitals and other medical facilities that contain patient data and medical history.
There’s also a surge in wearable healthcare equipment that monitors blood pressure, heart rate, and other such things are collected and analyzed for further research and development of medicines.
It also helps in identifying the scenario of all the hospitals at any given time, which further helps in making significant decisions related to management and overall governing of the healthcare sector in any particular area.
Conclusion:
Big Data is essential. It can derive new growth opportunities by identifying neglected sectors. Furthermore, it is becoming easier to deal with massive datasets with the help of Big Data. Currently, the majority of works done under behavioural analysis and productive analytics. It has given an edge over standard methods, and it can be more reliable with current technological advancements.