big data, what is big data


Big Data: What It Is and Why It Matters

Described simply, big data is voluminous data that originates from multiple sources and keeps on growing in size over time. Big datasets are so complex that no conventional data management software can process them efficiently. Nevertheless, big data matters primarily because it helps enterprises realize more in-depth business solutions that facilitate business growth. Successful companies that leverage big data to streamline business strategies and customer experience include Netflix and Tesla. 


Defining Key Big Data Terminologies

To appreciate the role of big data in the business community, let’s define a few terms that it encompasses, starting with the famous 5Vs. 

  1. Big Data Volume

Volume relates directly to the size of big data in the subject. The volume aspect of any data determines if the data in the subject can actually be referenced as big data. This makes volume the most definitive characteristic of big data. 


  1. Big Data Velocity

Velocity relates to how fast or slow big data accumulates from its sources, including social media platforms, business machines, and even mobile phones. The velocity plays a significant role in determining the usefulness and potential of data because the faster data accumulate, the faster businesses can acquire sophisticated insights. 


  1. Big Data Variety

Data can vary in type, mainly depending on the industry and source in the subject. As data changes in an organization, so does its usefulness. A company that deals with security cannot receive the same type of data as a company dealing with social media marketing. Experts classify big data as either structured, semi-structured, or unstructured. Structured data has definitive properties such as length and format and can be processed using relational databases. On the other hand, semi-structured data does not follow all formal understandings of data but is not entirely disorganized. Finally, unstructured data is entirely unorganized and can’t be stored or processed using relational databases. 


  1. Big Data Veracity

Big data is not easy to control or handle. In this regard, veracity describes the discrepancies, inconsistencies, and uncertainties that come with data collection. Businesses have to deal with this inconsistency on a daily basis. The quality and quantity of data determine whether it can reliably be used to produce useful insights. Big data can facilitate confusion, while lesser data can produce half-baked insights. As such, business data analysts have to find the balance between these two angles to deliberate insights. 


  1. Big Data Value

It all comes down to the actual value that big data presents to businesses. Without transforming big data accumulation into business, big data would be as good as dead. A good example is how a movie company can leverage big data to analyze what type of movie they should produce next, depending on how previous movies did. By using big data, the company would potentially save millions in production losses. Such projections are the leading voice of big data. However, modern data processing methodologies enables businesses to achieve more than projections. An online shop can analyze big data and tell the difference between customers, including demographics, thereby changing their way of business to foster more satisfaction among different types of consumers.


  1. Big Data Visualization

Just as it sounds, visualization involves presentations made in an attempt to acquire the meaning of data and to put things into perspective. 


  1. Datasets

A dataset is basically the name assigned to the resulting cluster when data that shares the same properties are grouped together. 


  1. Data Analysis

The analysis involves detailed data inspection to discover patterns and trends that could amount to or lead to valuable conclusions that facilitate the decision-making process. 


The Importance of Big Data

Modern technology in the name of IoT, machine learning, and cloud computing have largely facilitated the growth of big data and shaped how businesses understand and use it for development. The benefits of big data reveal themselves when a company takes the initiative to analyze their collected data and incorporate the findings into business. Here are the potential benefits of big data:


  • • It helps businesses understand the market

With big data, companies can learn consumer behavior and have a visible idea of the products that sell most in a certain region or demographic. By capitalizing on these findings, they stand a better chance of inspiring more business and sidelining competitors. 


  • • Big data helps in acquiring and retaining new clients

By learning about consumer patterns, businesses can have an idea of where to get more customers for a particular product, and how to appeal to the new prospects. Similarly, this information can help discover practical ways to meet the expectations of these customers, thereby keeping them loyal. 


  • • Big data triggers result-oriented marketing

Insights from big data analysis streamline marketing campaigns, and here’s how. The directions help companies discover what amounts to general advertisements that yield limited results. In line with the discovery, they get to understand their target better, thereby staging precise marketing campaigns. 


  • • Big data drives innovation

In the business space, a high level of competition demands that businesses stay on top of their game in many areas, including product development. Prudent companies can use information from big data analysis to discover weaknesses in their product mainstream. They can go further to define ways of making their products more superior than the competitors’.


  • • Big data saves operational costs and time

Big data tools, especially cloud-based mechanisms, store large volumes of data which saves operational costs. Similarly, these tools collect and process data from different sources quickly, facilitating better business operating speed. 


  • Big data enables companies to establish competitive pricing

Competitor analysis was a hard thing to accomplish in the old days, but this is no longer the case. Big data presents an opportunity to analyze competitor strategies in a bid to establish the dos and don’ts when crafting your company’s strategies. Further, you can discover the influence of price fluctuations and determine how to position your prices to stay safe. Finally, you have a better chance of setting more reasonable prices relative to purchasing behavior and industry patterns.


  • Big data helps companies to discover new revenue streams

Analytics on both competitors and consumers could lead to the discovery of new opportunities that you can invest in. data processing could also bring to light highly valuable information that you can sell to other companies within your industry.


  • • Big data is a tool for risk analysis

Running a successful business is not as easy as making big sales. It involves finding a balance between several factors, including social, economic factors among other external influences. Big data analytics can help you achieve this balance through leveraging predictive insights and maintaining pace with industry-specific trends.


Examples of Companies That Use Big Data to Foster Success

Global business powerhouses actively lead the way by using big data to remain on top of their respective industries. Here are a few success stories: 



Google manages billions of searches per day, not to mention the amount of data coming from its other ventures such as Gmail, Google Docs, YouTube, and Google translator. The amount of data Google handles is beyond imagination, yet the company never disappoints its consumers. How so? The company uses data flowing in from the various streams and processes it using state-of-the-art technology. That way, it discovers critical information such as the most searched keywords, the more visited resources, and the type of videos each viewer likes to watch. Google then injects back this information into the mainstream of their services to ensure that users remain satisfied. 



Netflix enjoys a huge viewership across the world, thanks to the diversity of taste, user-friendliness, and streamlined experience. The company successfully serves different demographics and societies without hiccups. Probably its most notable usage of big data is in its recommendation algorithm. Netflix gathers enormous data volumes, captures taste from what different viewers have watched before, and uses this information to recommend watching material. For example, you’ll find titles that read ‘because you watched prison break’ and a host of related shows below it. Besides using machine learning to recommend shows, the company also uses analytics to determine the types of movies they should produce or buy. 



Tesla has risen to become one of the most talked-about electric car production companies globally. Big data handling has a significant impact on this success. Autonomous vehicles use machine learning capabilities and predictions based on vast volumes of data. Further, the cars follow incredibly detailed maps that include even the most minor street features to enable the vehicles to drive seamlessly. The vehicles can even determine what road is better to follow based on criteria such as traffic and the condition of the roads. Tesla uses big data analysis to sophisticate their autonomous systems, among other operations such as marketing and pricing. The company even knows which time of the year is ideal for making big, trendy announcements that yield better results. 


Big data, geared by modern technological advancements, has become an invaluable resource for businesses as it houses endless possibilities and benefits. It can bring to light the underlying causes for slow business and help discover better strategies. The most competitive companies in the world use information from data analytics to maintain their competitive edge. Whether large or small, every business should borrow from these leaders to foster growth and satisfy clients.