Big Data is one of the most widely and rapidly growing terms among learners. It is not just a term but an expansive domain dealing with today’s most important asset; data. In today’s digital age, devices and humans equally depend upon data to process information. From a simple Facebook profile to giant organisations with global networks, data combines them all. All traditional mediums of communication, transaction, business, and organizations are evolving to digital means to keep up with the times. The reliance on data to regulate many services is more than ever.
Data retrieval is a serious concern for industries trying to keep pace with changing customer behavior, but what about data collection?
Data collection is growing as a larger concern over retrieval following the colossal amount of data generated each day from multiple sources. To make better business decisions and extend better services, online platforms retrieve data but managing the same is a concern when the said data grows massively. Moreover, most of the data is not even structured but entirely raw, making it nearly impossible to reap value from. Big Data is what helps in dealing with the ever-growing data issues.
Let’s dive into the world of big data to know more about types of big data
What is Big Data?
Big Data refers to the enormous amount of data an organization holds, collected through diverse sources, which is exponentially growing. These sources can range from e-commerce, social media, search history, transactions, and all other digital activities accessed through digital devices. Big Data is a collection of structured and unstructured data, which is too complex to use, but the expansive domain is also well-equipped to deal with it. The extensive domain extends non-traditional ways to analyze huge volumes of data and extract value from its raw form to reap valuable insights for businesses and organizations.
Data collection is only valuable as long as companies know how to extract value from them. Today, retrieving customer data is just a survey form away, but what about using it to improve insufficient resources? Raw data becomes useless in the absence of insights generated from them, and big data extend various services to bring out pertinent data, helpful in improving lacking processes. The growth of digital accessibility has made it easier for businesses to target their customers online with personalized tokens and offers explicitly curated for them through AI, social media, or other internet applications. However, too much data can result in zero results if the application is inaccurate.
Big Data instrumentation uses multiple tools such as data analytics to extract relevant data that traditional management databases cannot acquire. These massive data sets can bring significant changes to any business. Hence, understanding the concept of big data can immensely help you take your endeavors a notch up.
Characteristics of Big Data
To better understand big data and its influence on various business endeavors, the characteristics of big data are divided into five categories, also known as the 5 V’s of big data. Let’s learn more about these 5 V’s to understand their effect!
The volume of big data directly refers to its size, composed of enormous amounts of data compiled through various sources. These sources may vary from social media, e-commerce, sensors, financial transactions and much more. The volume of data is crucial in determining if it comes under the category of big data. For example, data retrieved through hits on a local website is comparatively lesser than what an e-commerce website compiles in a day – both are significant for generating insights, but the size of data is greater on e-commerce platforms than on a local website.
The rate of data flow at which data is generated is one key component of big data. The continuous flow of data determines how fast and widely data is being processed and meeting customers’ needs. The velocity of data efficiently governs the continuity in the data flow to understand its amount. If the data is not continuous, it is not massive enough to be considered under big data. The most prominent sources of data are social media sites, sensor machines, and networks. Velocity is greater than volume as high-speed data flow is always preferred over lots of data at slow speed.
The third V of big data refers to variety, which regulates the variety of data being received. Before rapid digitization, data forms were limited, ranging from documents, pdf, etc., but now data forms are more diverse. Images, videos, and GIFS are a few frequently used data elements shared by millions of people. Data variety is also divided into three categories: structured, semi-structured, and unstructured data. The importance of variety is relevant to its serving organization. For instance, the customer service department must harness and analyze customer data and not sales data.
This category refers to the quality of data acquired. Veracity refers to the uncertainties and inconsistencies of accumulated data which often gets messy with the enormous amount and diverse sources. It is essential to have it filtered and structured according to the relevant domain to make the most out of a given dataset.
Relevant data is crucial for extracting meaningful insights. Analysts say poor data quality can do more harm than good, which is why collected data is processed through several parameters to extract valuable information. Data scientists and analysts analyze raw data, which is organized and cleaned to retrieve the most helpful information. This data is further analyzed and processed with pattern identification to determine if it is valuable or not.
Strengthen your Resume with PG Program
Big data is a rapidly growing industry that offers lucrative career opportunities to tech professionals globally. India, too, is experiencing a demand for big data experts, which is bound to grow in future. The best way to ensure you stay relevant in the exponentially increasing tech world is to keep up with the latest industry trends, and big data is the leading one now!
Learners looking for big data career opportunities can strengthen their resumes with upGrad courses.
If you are interested to know more about Big Data, check out our Advanced Certificate Programme in Big Data from IIIT Bangalore.
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Who came up with the 5 V's of big data?
Big data was initially characterized with “3 V’s of big data”, which later became “the 4 V’s of big data”. Finally, paraphrasing the 5 W’s of journalism, Oscar Herencia offered 5 V’s of big data, which became the most widely accepted keys of big data worldwide. These keys include big data’s velocity. Veracity, volume, variety, and value. The 5 V’s were introduced in a presentation by Oscar to emphasize the impact of these on big data.
What is an example of big data?
Big data examples include the most frequently used domains - the e-commerce industry. From analyzing consumer shopping habits to using the obtained information to serve relevant deals and advertising campaigns, big data compiles all the information in a structured way to help companies create data-driven business strategies.
Are big data jobs in demand?
Digitization and easier digital access in the Indian market has led to a boom of data on various platforms, growing businesses to step up their games and tech professionals to reboot their careers in big data. Big data is one of the leading jobs globally and in India. Analysts claim that big data is one of the top careers in India as vacancies for data scientists and analysts keep growing.