In this digital age, data continues to grow exponentially. The growth is so immense that the International Data Corporation (IDC) projects that by 2020, the capacity of the digital universe will have hit 44 zettabytes. This is the equivalent of 44 billion terabytes. Such a huge amount of data, when analyzed properly, is capable of providing insights on virtually every aspect of human lives and all factors that influence decision making. Organizations are fast appreciating such proven benefits, and big data and analytics is at the heart of it all. Today, organizations rely on big data analytics to solve a myriad of business challenges, improve and streamline operations, boost sales, manage human capital, and much more.


In retail, for instance, big data enables optimized pricing and accurate forecasts for product demands. In health care, big data has enabled many institutions, both public and private, to analyze tones of medical records with the goal of reducing costs and improving patient outcomes. The field of agriculture also relies on analytics for yield maximization, while insurers have made significant strides in achieving accurate risk quantifications, even in naturally challenging dimensions such as the weather and environment, through predictive analytics. There are many other industries that benefit form big data. Read further for a detailed overview of the 5 major applications of big data analytics for organizations.

  1. Improving Business Operations’ Efficiency

Many businesses struggling with severed links in their value chain appreciate the value of big data analytics because it helps them optimize the operating efficiencies of their different investments. Through big data, feedback loops can be created by data generated offsite. For instance, commercial airplanes are able to generate up to 20 terabytes of data per hour. Onboard sensors in automobiles produce data that can be transmitted live to dealers’ service systems. Equipping crates and other forms of packaging with RFID chips has made collection of transit data much easier.

Combining such data repositories with machine-to-machine interactions forms a strong base for predictive analytics, which when fed back to such systems, produce incredible outcomes. For instance, the analytics can direct airplane systems to determine their own maintenance schedule and even go a step further to initiate advance communications with supply chains for preparation and delivery of the required parts at the right time. In other business transaction, powerful customer relationship management systems (CRMs) are able to analyze real-time data from multiple systems, and even suggest offers that are most suitable for a given customers at any point in time.

  • Expanding Customer Intelligence

Every customer wishes to be recognized and valued. Unfortunately, for businesses with millions of customers, this has been a major challenge in the past, but big data is changing the trend. With big data analytics, companies are now capable of identifying their most valuable customers currently, and in future. Better still, they can do so without disregarding or “punishing” other non-frequent customers. Big data achieves this mainly through examination of data from multiple sources in multiple fields. The data obtained may be structured, such as purchase histories, data from industry partners and CRM data, or unstructured data from social media, blogs, videos, and many more sources.

Ultimately, many businesses gain invaluable insight on how to treat their customers with recognition and uniqueness. For instance, an airline that has partnered with credit card companies and travel agencies can use big data to improve the travel experiences of many customers who have unique needs by creating packages that are tailor-made for them. Big data will continue to expand customer intelligence for many companies that capitalize on analytics.

  • Enhanced Mobility

Data analytics makes sense if it can yield actionable insight for the end-users. Adding mobility to insights from analytics helps accelerate the impact of big data on both operational efficiency and customer intelligence because the results of analytics become instantly actionable. When organizations push the intelligence and decision-making capabilities of analytics to mobile devices, they are able to create new business processes that are in essence, revolutionizing how business in conducted.

Businesses are realizing the benefits of equipping employees with real-time insights at the time and place they are needed. It is especially more beneficial when such insights are derived from blending both dynamic information (from data in motion), with static data. Mobile analytics ensure that real-time data can be collected from the field as much as it is being sent out from within the organization. This ensures that external data can support insights in other parts of the organization system.

  • Accessibility of Big Data and Analytics “As a Service”

Not many companies are able to acquire data analytics tools and infrastructure: vast storage facilities, arrays of servers, and an arsenal of data scientists. In fact, for other companies with the means to execute their own in-house big data collection and corresponding analytics, such activities would deviate so much from their core business, risking the productivity of other business processes.

Therefore, as the complexity of data increases, especially due to the unstructured data obtained from social media and other sources, many companies prefer to acquire data analytics as a service from software development firms that specialize in the trade, and who are better equipped to handle such complexities. It is now possible for small, medium, and large companies to leverage on the power of big data without venturing out of their core business or incurring outrageous costs because the insight and expertise they require has been provided to them as a service.

Development of New Products and Services

Many organizations are hopping onto the ambitious route of using big data and analytics in creating new products and services. As is expected, many of the organizations that adopt this approach are online companies whose core operations (services and products) are data-driven. Service providers are using analytics to bring people together in groups based on similar interests, similar likes, people they may know, or people who view others’ profiles, and many other knowledge areas that are seeing such firms attract millions of new customers within a short period.


Such successes are being recorded in industries across the board: manufacturing, telecommunications, electronics, entertainment, and many more. While there is always the risk that some products may never see the light of day, as businesses begin to realize the potential of big data and equip themselves with the necessary tools and personnel to leverage on this potential, then probabilities of success are bound to increase.

As seen from the discussion, big data is changing businesses in terms of operations, processes, revenue, and customer engagement. Although we cannot overlook the fact that data is complex and requires equally sophisticated systems to conduct meaningful analytics that can provide actionable insight, it is also clear that organizations not capable of constructing such powerful systems can also reap the full benefits of analytics by acquiring it “as a service”. Gradually, many organizations will be in a position to boost operational efficiency, expand their customer intelligence, create new products and see them all the way to market, as well as develop new business processes that support their core operations.