Big Data is a very popular term of the 21st century. It’s a revolutionary new technology that resolves consumer-centric and point-of-sale questions needed by the industries. It provides the answers to issues and duties that data owners had never considered before. This is high time to learn Big Data. The average Big Data engineer salary is $116,591 per year in the U.S. Due to its increasing popularity and high salary trends, many students want to build their careers in Big Data. They generally ask what big data is, its types, and importance. In this blog, we will provide detailed answers to these questions.
What Big Data is?
Big data refers to data that comes from various sources, arrives in higher amounts, and at high velocity. The three V’s is another name for it. In simple words, big data is more extensive, more complicated, and derived from new data sources. These data sets are enormous, and conventional data processing software is unable to handle them. However, these vast amounts of data can be utilized to solve business challenges that cannot be solved previously. Here are the three V’s of big data which will help you to better understand what big data is-
Three V’s of Big Data
The amount of data being collected is rapidly increasing. Data floods into businesses at an extraordinary speed as the Internet of Things grows, and we must handle it quickly. We need to cope with data sets being driven by CCTV cameras, sensors, RFID tags, and smart meters. Every two years, the volume of data is expected to double.
Data is no longer kept in rows and columns. From organized, quantitative data in traditional databases to unstructured text documents, videos, emails, log files, audios, CCTV footage, and financial transactions, data comes in various formats.
The amount of data we deal with is massive, measuring in petabytes. Data is gathered from various sources that include Internet of Things (IoT) devices, commercial transactions, industrial equipment, social media, movies, and more. Previously, it was a huge challenge to store this data, but the decreased cost of storage platforms like Hadoop and data lakes makes the process cheaper.
History of Big Data
People started to notice how much data users created through YouTube, Facebook, and other Internet services around 2005. Hadoop (an open-source platform for storing and analyzing extensive data sets) was founded that same year. During this time, NoSQL began to gain popularity. The growth of big data was aided by the advent of open-source frameworks such as Hadoop (and, more recently, Spark), making massive data easier to deal with and store. The volume of big data has exploded in the years since then. Users are still generating massive volumes of data, but it isn’t just humans.
More products and devices are connected to the internet due to the Internet of Things (IoT), allowing companies to collect data on client usage patterns and performance of the product. The rise of machine learning has resulted in even more data. While big data has gone a long way, its utility is barely beginning. Cloud computing has opened up even more opportunities for big data. Developers may easily spin up ad hoc clusters to test a fraction of data in the cloud, which provides genuinely elastic scalability. With its ability to present vast volumes of data that makes analytics rapid and comprehensive, graph databases are becoming more important.
What are the Types of Big Data
The following are the three types of data that big data incorporates-
Structured data is any data that can be stored, accessed, and processed in a fixed format. Over time, computer science expertise has become more successful in inventing strategies for working with such data(when the format is fully understood in advance) and extracting value from it. However, we are now anticipating problems when the bulk of such data expands to enormous proportions, with typical sizes in the zettabyte. An employee table in a database is an example of structured data.
Unstructured data is any data that has an unknown structure or form. In addition to its huge size, it has several processing challenges to extract value from it. A heterogeneous data source is an excellent example of unstructured data that includes a mix of simple text files, photos, videos, etc. Companies have a vast amount of data available, but they don’t know how to extract value from it because the data is in an unstructured format. An output returned by the google search engine is an example of unstructured data.
Structured and Unstructured both types of data can be found in semi-structured data. Semi-structured data appears to be structured in appearance, but it is not defined in the same way that a table is established in a relational database management system. Personal data stored in an XML file is an example of semi-structured data.
Importance of Big Data
The importance of big data is determined by how a company uses the data it collects, not by how much data it has. Every business uses data in its unique way. The more effectively a business uses its data, the more growth potential it has. Data can be gathered from any source and analyzed by the company.
- Find out the reason for problems, failures, and flaws.
- Coupons are generated based on the customer’s purchasing patterns.
- Recalculating risk portfolios within a short time.
- Detecting fraudulent behavior and saving the company from its negative impact.
- Increase the number of new customers you get
- Recognize market conditions.
This blog has provided every piece of information about what big data is, its history, types, and importance. Social applications are widely used in the current scenario. As a result, the amount of data is increasing rapidly. Every day, billions of users connect on social media platforms, sharing information, photographs, videos, and much more. However, the growing data is no longer a burden. It is being used by businesses to expand and beat their competition. Hopefully, now you understand what big data is and why it is the hottest topic these days. Moreover, if you still have any difficulty in Big Data project help or need Big Data Assignment Help, you can discuss it with our experts.