Data can be characterized as the facts or figures which can be stored in and processed by a PC. Now, what is Big Data?
Big Data is a large volume of data that floods a company or a business on a day to day basis. It can be in various formats, such as structured or unstructured data. Big Data is fast, large, and complex, it’s not possible to process it using traditional means. So, the question arises that how to process data that is traditionally impossible to process?
Above all, the new emerging technologies, like Hadoop, related to Big Data Analytics come in handy, to know more about Big Data Technologies, click here.
Since we now know what exactly is Big Data, we must learn how to characterize data as Big Data. For that, there are four Vs, which are as follows:
Volume
It is one of the most defining characteristics of Big Data. We know that what makes Big data “Big’ is it’s volume. Every second of every day, social media platforms, business processes, machines, networking, human interactions, etc. combine together to generate a huge amount of data from different sources. So, Data is stored in Data Warehouses; where the concerning business or industry can use it to provide customers with the products they want. Likewise, Governments may use the data for the advancement of their population.
Variety
The growth of Big Data can only be termed as exponential. The main reason behind its growth is that the various different sources generate data at the same time. In the past, a limited number of sources, such as databases and spreadsheets were used to collect data; however, today it comes in many different forms such as photos, videos, emails, PDFs, Posts, audio, etc. Moreover, defining what varieties the big data is an important characteristic of Big Data. All in all, there are many existing varieties of Big Data; they are as follows:
- Structured Data
In this, the data is in a structured schema or tabular format. An example of structured data is a database management system. For instance, employee tables in a company database which includes details such as employee details, salaries, job positions. - Unstructured Data
In this, data is not present in any particular format. Above all, it is complex and time-consuming to process and to conduct analyses. For instance, unstructured data is email. - Semi-Structured Data
Semi-Structured data is data that includes the characteristics of both structured and unstructured data. All in all, it cannot be particularly defined but it is structured.
Velocity
Velocity is the characteristics of Big Data; that defines how fast the data is collected. It plays a role in whether the data will be characterized as Big Data or not. Above all, in this digital age, all of us have access to mobile phones and computers and are continuously generating data without even realizing it. Examples of data generated by us every 60 seconds are:
100,000+ Tweets
695,000+ Status Updates
11,000,000+ Instant Messages
698,445+ Google Searches
168,000,000+ Emails
1,820 TB Data Created
217 New Mobile Users
Veracity
Veracity refers to the quality of the data, and whether it can be trusted. It has become very necessary to maintain the quality of the data. Because of the sheer volume of the data, that is the characteristic of big data, there can be unnecessary noise and inconsistencies that can hamper the processing of data. For instance, all Facebook posts, Instagram pictures, hashtags, spam emails, cannot be scanned for their content; if we want to produce quality results from the gathered data.
All you need to know about Big Data
| Introduction to Big Data | Career Options after Big Data |
| 4 V’s of Big Data | Big Data for Business Growth |
| Uses of Big Data | Benefits of Big Data |
| Demerits of Big Data | Salary after Big Data Courses |
Learn Big Data
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| Top 7 Online Big Data Programs | Top 7 Certification Courses of Big Data |
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