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What is big data?



Kirjoittanut: Sille Sinor - tiimistä SYNTRE.

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Esseen arvioitu lukuaika on 5 minuuttia.

What is big data? What it is used for? Why do companies want it and what do they do with it?

What is big data?

Big data is a commonly used term that may confuse you if you are not familiar with it or do not work with data or in IT. It is used to refer a large and complex data sets, that are produced and gathered through the internet. It is gathered data that is too large or complex to process by traditional data-processing application software within a tolerable elapsed time. The more official definition for big data is that it is data that contains greater variety, arriving in increasing volumes and with more velocity. The Vs listed before are characteristics that big data holds. The characteristics help to understand the size, value, and complexity of the data.

What do the Vs tell us about big data?

The volume of the data refers to the amount of generated and stored data. When talking about big data this amount or quantity is usually larger than terabytes and petabytes. To understand the size better, to store one terabyte would mean that the data would need to be in 16 phones with a memory of 64 GB. Usually, with big data, you need to process high volumes of low-density, unstructured data. The value of the data can be determined better after it is processed.

The velocity means how fast an organization or software can react, generate and process the data given to it. So it is the speed that which data is received and acted. Usually, with big data, there are two kinds of velocity, the frequency of generation of data and the frequency of handling, recording, and publishing it. Big data is often handled more daily based because it is often available in real-time. For example, Amazon can capture every click of the mouse while shoppers are browsing its website. Gathering the data is made quickly.

The variety refers to the types and nature of available data. Data can be in many different forms. It can be structured like it used to be traditional before pictures and videos were able on the internet. Or it can be semi-structured or unstructured, which means data types like text, audio, and video that need additional preprocessing to derive meaning and support metadata. The variety can make processing the data even longer if it is unstructured. The source of the data determines its type and nature of it.

These three Vs are the most relevant characteristics of big data, that you should know about. Because according to them you can see how big data are we talking about, the time it takes to be processed, and its structure of it. Big data haves other characteristics also that are used from time to time like veracity (refers to the quality and value of the data), value (how valuable the big data is after processing it), and variability (structure and source of the data). They are also used but more likely you bump into volume, velocity, and variety when describing big data.

Why and where can you use big data?

Now that we have an understanding of what big data is we can think about why and where we need it. Big data is this big ball of information that with the right tools and hands can be valuable for different institutions, companies, and study fields. Companies that can manage to use their data smartly will most likely increase their productivity by 8 %.
We can use big data to analyze and study customer patterns and trends. Companies can increase their sales with this information. Also, you can see the shopping trends and invest more time and money in them. Staying on top of the trends has become important to companies and reacting to the demand at the right time helps the companies to provide the service to their customers.

In artificial intelligence, big data is used to teach machines. The more data they can process and work with, the “smarter” they can come. As a result, AI could be used even more efficiently to help in different fields like the health industry for example to find patterns in disease. With advanced AI and effective machine learning, we can make the humans’ everyday life easier and find patterns in things that would take us years even faster. It is fascinating to see how much are we able to succeed in this field and how it will affect us in the coming years.

How can a big company advance from big data?

For bigger companies, big data and working with it has become a crucially needed element in their businesses. Because the amount of data that is available and its usage of it has become so natural in everyday life companies would be stupid not to advance from the data and use it. Companies can automate time-consuming processes like gathering information and analyzing it. Big data holds information about trends and insights that businesses can use for increasing their productivity or sales. Combining big data with machine learning or just analyzing it you are able to make decisions based on the data and the information. Such as how many orders should be made for holidays. With the information from last year, the machine can analyze and predict how many orders should be done for the next year. This way of using the data can also be used for finding cost reduction. As listed there are many ways big companies can use big data and where companies can profit.

Future of big data?

In the future, big data will keep increasing in size. It will most likely bring some problems because storing it all will need a lot of space. It will bring in the question is it needed enough to store all of it and where are we able to put it all. It is predicted that by the end of the year 2025 seventy percent of the population will be able to access the internet and interact with the online data.
AI and machine learning are going to come more common in our everyday life and change the landscape.
In the working field, the demand for data scientists and Chief Data Officers will increase. The need for these positions is already big but it will increase even more because of growing data. To be wanted in the market for this you need to have deep knowledge of data platforms and tools, programming languages, machine learning algorithms, and data manipulation techniques, such as building data pipelines, managing ETL processes, and prepping data for analysis.

Conclusion

Big data means it is a large and complex data sets, that are produced and gathered through the internet. The data contains greater variety, arriving in increasing volumes and with more velocity. You need to process this data and because today’s data is mostly unstructured processing it takes more time. AI and businesses benefit from this data and can develop because of it. It is used in businesses for example to improve the customer experience and cut costs. In the future, the need for professional data readers and proceeded is going to grow as will the amount of big data too. Big data is useful and it is used in many fields knowing what big data I and how we can benefit from it is important when running a company or needing data to improve or learn.


Sources:

Khvoynitskaya S. 2020. The future of big data: 5 predictions from experts for 2020-2025. Itransition.

 https://www.itransition.com/blog/the-future-of-big-data  

How much is 1 TB of storage? Dropbox.

https://experience.dropbox.com/resources/how-much-is-1tb  

Griffith University. What Does Big Data Mean? FutureLearn, website.

https://www.futurelearn.com/info/courses/applied-big-data-analytics/0/steps/52404  

Ibedrola. Big data: main uses and applications.

https://www.iberdrola.com/innovation/what-is-big-data-what-is-it-used-for  

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Comments
  • Hassan Chakir

    Interesting topic with good perspective, keep up the good work Sille.

    28.4.2022
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