In the interconnected and online world, today there is no place where Big Data does not exist. Before analyzing what Big Data is, there is some data that shows the growth in this area and, therefore, it can be understood why many companies and organizations are increasingly interested in data analysis. According to Forbes, in every minute of the day, users around the world watch 4.15 million videos on YouTube, send 456,000 tweets and post almost 50,000 photos on Instagram.
Imagine the large amount of data that is produced with these activities. This constant creation of data , interactions, tastes, affinities through social networks, commercial applications, telecommunications and other various domains is leading to the formation and growth of Big Data.
DEFINITION OF BIG DATA
To understand Big Data well, we should briefly know its history. A simple definition is that Big Data is data of great quantity and variety that arrives in greater volumes . Although it seems that Big Data is a new topic that was born with the digitization of many sectors in recent years, it actually began in the 60s, when the first data warehouses began to appear.
Fifty years later, and with advances in tools and services available to help us interpret data, companies can now make decisions about business, strategy and marketing campaigns, among other things.
And the development of those services that interpret the data is key in the definition of Big Data. They are increasingly large and complex data sets that are received through different data sources. With so much complexity to the traditional software programs that were used to process the data it was not easy to manage it and new tools were created.
Source : E-skillsbusinesstoolbox
As can be understood from its name, structured data has a fixed format and in most cases it is numeric. The information comes through databases or spreadsheets stored in SQL databases or data lakes. Today, this data is managed by machines and not humans.
Unstructured data is disorganized information and does not come from a source with a predetermined format. A good example of unstructured data is data that comes from social media sources.
Finally, semi-structured data has characteristics of the two ways already mentioned. Some of the data is already organized and some is not. Information that comes through web server logs or sensor data are examples of semi-structured data.
BIG DATA FEATURES
Before seeing how Big Data is used in real cases, it is also important to understand the characteristics. Professionals who work in the Big Data area talk about the big Vs of Big Data:
- Volume : We refer to large volumes of data.
- Speed : How fast data is received and processed
- Variety : Refers to the types of data that are available
- Veracity : Refers to how accurate the data in the data set is
- Value : It is important to establish a way to value the data because not all have the same value.
- Variability : It refers to the way of using very different data and formatting it in different ways
EXAMPLES OF BIG DATA APPLICATIONS BY SECTORS
Big Data has enormous potential. With a good data analysis and with as much information as possible, it is easier to be able to make decisions of any kind to reach the customer, offer them a more personalized experience, reduce costs, and improve all processes.
Some examples of how Big Data is being used in different sectors are:
- Streaming Services: Netflix and Amazon use it to make recommendations for shows and movies to their users.
- Insurance : Insurance companies use Big Data to predict illnesses, accidents and set the price of their products.
- Education : Big Data-driven technology as a learning tool instead of traditional methods has improved the experience for students and helped teachers better track their performance.
- Government : A very interesting use case in this sector is to use Big Data to be able to analyze patterns and influence electoral results. Equally the most famous case was Cambridge Analytica, a company that used data to change the behavior of the audience in the Brexit vote in 2016.
A SECTOR THAT WILL CONTINUE TO GROW
If you are thinking about a professional career in Big Data, it may be time to study a Master in Big Data Analytics or Course in Big Data Online .
According to IBM, 59% of all labor demand for Data Science and Analytics (DSA) is in Finance and Insurance, Professional Services and ICT, but every year there is more demand in different sectors. The graph above shows the Big Data market revenue growth in the US between 2011 and 2027.
Companies also pay a salary bonus to attract the best profiles in the Big Data area. According to data from the Spanish market, a professional specialized in Big Data can charge from 30,000 euros to over 80,000 euros. All this depends on the position, experience of the candidate and the company.