Big data is an area of artificial intelligence that deals with methods for examining, methodically extracting information from, or otherwise affecting data sets that are too large or complicated for conventional data-processing application software to manage. In other words, it is made up of a sizable volume of structured and unstructured data that organizations utilize to analyze data for insights and gather data for decision-making.
The term was coined by Roger Mougalas from O’Reilly Media in the year 2005, only after they created a word called Web2.0.
The 5V’s of Big Data
- Volume: Volume refers to the size of the data that the organization has gathered to be analyzed and processed. In todays, advanced technology data is much larger in size of bytes such as terabytes and petabytes. Therefore, volume is a specific attribute of Big Data. Volumes in data can reach up to any level. It’s estimated that around 2.5 quintillion bytes of data are created each day. It was found that nearly 40 zettabytes of data were created by the end of 2020.
- Velocity: Velocity refers to the speed at which data is being processed. Some of the data come in real-time and some of it comes in batches. Analyzing data quickly can alert businesses to resolve problems faster than it may become worst. Data velocity can speed up to process of making important business decisions to keep up with market changes.
- Variety: Variety refers to collecting unstructured and structured data from multiple sources to understand a problem and make well-informed decisions. This includes having clear, sophisticated access to a variety of data, this enables businesses to keep up with the latest innovations and improve efficiency.
- Veracity: Veracity refers to how accurately correct a data set may be, when it comes to the accuracy of big data, it’s not only the quality but also how credible is the source of data. It also relates to the nature of the data that is being analyzed.
- Value: The value refers to how useful the data gathered for business. It indicates how important and valuable is data for gathering insights and information about customer needs and enables businesses to make decisions that could lead to effective and efficient operations and build long-term customer relationships.
Why use Big Data?
- Substantial cost reduction
Big data helps you to cut down your costs most organizations have agreed that by using it, there has been an average of 10% reduction in costs. Many researchers reveal that businesses who rely on data-driven strategies have received accurate insights which have enabled them to make the right decisions, this has helped them to increase their revenues by 10%.
- Increases Business Efficiency
Big Data Analytics and tools help businesses to extract important information from a large variety of datasets and that can enable businesses to develop strategies and decisions that would align with the current market demands. It would enable them to innovate their products after considering customer feedback, improve their strategies in marketing and utilize customer service and human capital employed in the business.
- Increases Profitability
Big data consists of accurate information about which products of the company are profitable and which marketing activities are most profitable. Big data tools can be used by businesses to understand which products and activities to devote their time and investments more to and which are the least profitable products and activities to discard.
- Helps to increase Customer Satisfaction
Every websites you visit and actions performed by you on the website get recorded in big data. Ever noticed how you start receiving advertisements for the product you just added to your wish list on an Ecommerce website? All your activities get collected and recorded in big data. This way businesses understand what the demand for their products in the market is, it enables them to tailor products and services to match your needs and wants. This leads to customer loyalty.
- Set Competitive Prices
Big Data is constantly monitoring market conditions and of course competitors of the business. It enables companies to delve deeper into the activities of their competitors and understand the actions and strategies adopted by them. It enables businesses to understand their financial position, helps them to understand the most suitable pricing strategy to adopt for their products as per the type of customers they deal with, and helps to understand the impact of price changes.
Artificial Intelligence in Big Data
- Artificial Intelligence is used to gather Big Data and it is not only used in collecting data but also in analyzing and processing the data and recognizing the content of the dataset through natural learning. AI helps big data to generate valuable insights. AI makes the most use of Big Data. When AI is run through data, it can identify most of the data types, also find possible connections, and even create a link among the datasets and recognize knowledge by making use of language processing, that’s how data analytics work. It also helps to accelerate and automate data preparation tasks, and prepare modules and insights thereby making tasks of businesses easier. AI helps to create a competitive advantage in the industry with the help of Big Data.
Big Data Analytics
Big data is high volumes of unstructured, raw, complex data. The role of big data analytics it scrutinizes large amounts of data to discover various patterns, trends, statistics, correlations, and insights. With current technological advancements, it is easy to analyze data quickly and accurately. This has also enabled businesses to quicken and align their decision-making process and strategies.
When we talk about Big Data, we hear another word closely associated with it known as Hadoop.
What is Hadoop?
- It is an open-source software provided by Apache. Hadoop is a program that was designed to manage and organize raw, sophisticated, and complicated data. It is not only affordable but it is a faster and excellent storage platform and analytics tool. Hadoop enables companies to perform advanced analytics, deep learning, machine learning, data mining, etc. Hadoop was one of the earliest Big Data tools launched in 2006. However, there are faster and better alternatives to Hadoop such as Apache Spark a successor of Hadoop, it is more advanced, faster almost by 100times, flexible, and practical than Hadoop, and will soon become the top preference of most companies.
Other alternatives to Hadoop are Apache Storm, Google BigQuery, DataTorrent RTS, Hydra, etc. These will be explained in detail in our next article about Big Data Analytics.
Future of Big Data
Many big companies are adopting this technology to reap its benefits. As per researchers, the big data market is expected to grow by $103 billion by 2027, with rapid technological advancements we know that the software industry is a leading industry that consists of a 45% market share. Big Data and Big Data Analytics market will show an exponential rise from $169 billion in 2018 to $274 billion in 2022. The field of Big Data does have a lot of lucrative career options with attractive pay packages.
To Read: Cryptocurrency, Web Development, Web Application, Mobile App, Google Street View, Digital Agency, WooCommerce, Digital Marketing, Visual Identity, Google AdWords, Logo Design, Google Ads, Chatbot, Motion Design, Mobile Development, Leaflet, Internet, Graphic Design, WordPress, Web Design, Google Adsense, SEO, Blog, LinkedIn, Instagram, Facebook, Youtube