What is Big Data

Big data is characterized as more massive, more complex information sets, especially from new information sources. These information sets are so voluminous that conventional applications for information processing can not accommodate them. But these large volumes of information can be used to solve business issues you couldn’t handle before.

Big Data characteristics (4 V of Big Data);

  1. Volume

Big data is always full of information . It is due to building up an amount of information from unstructured sources such as contact with social media, posting or exchanging comments on the web page, cell phones, and many more.

The traffic creates if a user visits the website using desktops, laptops, smartphones, pdas, etc. They also produce unstructured data by uploading music and videos from various platforms. Using the analytics tool, this information can be filtered and important metrics extracted that are useful to the business.

  1. Velocity

Velocity refers to the frequency at which the information arrives and how easily it is processed and used by the organizations. Using analytics tools, data processing can generate answers to queries via reports, dashboards, etc.

With these findings, a company can make effective decisions that improve productivity and accomplish customer-related goals such as developing applications that meet needs.

  1. Variety

Different sources, such as social media, CRM systems, call center logins, emails, audio, and video types, produce varied information . Managing such complex data poses a significant obstacle for businesses. However, analytics tools are used to distinguish groups based on sources and generated information to handle this big data.

It will avoid data mixing in the database. Separating new and old data from different sources is crucial and must be able to make the changes according to consumer behavior.

  1. Veracity

Veracity refers to the complexity of the available information , which makes it more difficult for businesses to react quickly and find suitable solutions. Precision is a big problem in such a big data setting. Organizing the information by category, importance, and significance will allow you to have a better strategy for using the information .

Avoid mixing with similar and unrelated information , as the mixed analysis is reduced. The information have to be safe, accurate, and integrated to make the right decisions.

Big Data types?

The two broad categories can be grouped: structured and unstructured.

  1. Structured Data
  2. Created

Data generated is just that; information companies are producing intentionally, usually for market research. These may include consumer surveys or focus groups.

It also involves more modern research approaches, such as creating a loyalty program that gathers consumer information or demands that consumers create an account and log in when shopping online.

  1. Provoked

Forbes Article described provoked information as “Allowing people to express their views.” Each time a customer rates a restaurant, an employee, a shopping experience, or a product, they create provoked information . Review sites, like Yelp, produce this kind of information as well.

  1. Transacted

Comparison, transactional information is reasonably self-explanatory. Organizations collect information on each completed sale, whether the purchase is made through an online shopping cart or at the cash register in-store. Businesses also gather information about the steps leading to an online purchase. A consumer, for example, can click on a banner ad that leads them to the product pages that then prompt a purchase. As the Forbes article states, “Transacted information is a valuable way of understanding precisely what was purchased, where it was purchased, and when. Matching information of this kind with other details, It can provide even more information, like the weather.

  1. Compiled

Data is a vast database gathered on each U.S. household. Firms like Acxiom collect information about things like credit scores, location, demographics, transactions, and registered cars that can then be used by marketing companies for additional consumer information .

  1. Experimental

Data is created when companies are experimenting with different marketing pieces and messages to see which ones are more effective for customers. As a mixture of produced and transactional information , you can also look at experimental data.

  1. Captured

Data is passively generated through the actions of an individual. Each time someone enters on Google, a search term which is information that can be collected for future benefit. Another example of passive information that can be managed using big information technology is the GPS info on our smartphones.

  1. User-generated

Data is composed of all the information that individuals placed on the Internet every day. Through tweets, to Facebook posts, to news article reviews, to videos uploaded to youtube, individuals generate a massive amount of information that companies can use to better target customers and get feedback on goods.

Advantages of Big Data Processing

Big Data processing capability provides multiple benefits, such as-

  1. Businesses can use outside information when making decisions. Accessing social information from search engines and websites such as Twitter; twitter helps companies to customize their business strategies.
  2. Enhanced customer experience new, Big Data technology systems are replacing conventional customer feedback systems. Big data and natural language processing techniques are used in these new systems for interpreting and analyzing user responses.
  3. Early product/service risk recognition, if any
  4. Improved operational performance Big Data tools may be used to establish a staging area or landing area for new information before determining which information should be transferred to the data warehouse. Therefore, the incorporation of Big Data technology and information warehouse assists an enterprise in offloading seldom accessed information .

Ways to use Big Data

  1. By making information transparent, the Big Data will unlock significant value. There is already a considerable amount of details that are not yet digitally collected, e.g., information that is on paper or that is not easily accessible and searchable across networks. In some technical workgroups, we found that up to 25 percent of the effort consisted of looking for information and then moving it to another (sometimes virtual) location. The aim is a significant source of inefficiency.
  2. When companies produce and store more digital transaction information , they can capture more accurate and detailed performance information on everything from inventory inventories to sick days, thereby revealing uncertainty and improving results. Also, some leading companies use their ability to gather and analyze big data to perform controlled experiments to make better management decisions.
  3. Big Data allows for ever-finer consumer segmentation and thus much more specifically targeted products or services.
  4. Sophisticated analytics can significantly improve decision making, minimize risks, and uncover useful insights that would otherwise remain hidden.
  5. Big Data can be used to build the next generation of services and products. For example, manufacturers use information collected from sensors embedded in goods to create original after-sales service packages such as proactive maintenance to prevent faults in new products.

5 Ways it’s used in your daily lives

  1. Mobile maps and GPS
  2. Online Shopping
  3. Urban Planning
  4. Energy Consumption
  5. Wearables

Examples Of Big Data

  1. The New York Stock Exchange creates about a terabyte of new daily trading data.
  1. Social media the statistics show that every day, 500 + terabytes of new data are absorbed into social media website Facebook databases. Such information is generated mainly in terms of uploading photos and videos, exchanging messages, placing comments, etc.
  2. A single Jet motor can generate 10+ terabytes of information less than 30 minutes of flight time. For several thousands of flights, a day, information processing approaches as much as Petabytes.

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