What Core Business Functions Can Benefit From Hadoop?

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Hadoop can have a major impact on core business functions, leading to a better and more efficient business.

In recent years, it has become a ubiquitous fact that enterprises are struggling to find a way to deal with all the new data that is available at their disposal. Data is everywhere and it is being generated from all possible digital sources, including digital phones, sensors, social media and Internet of Things (IoT) devices.

To tap into this data efficiently, Apache Hadoop has emerged as a leader. Hadoop has become the go-to solution for storing, processing and analyzing the ever-increasing amounts of big data. It also provides a competitive advantage for organizations in various key industrial areas.

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Let’s explore these core functions and industries that are being affected by Hadoop solutions.

What is a Hadoop Solution?

Primarily, Hadoop is made up of these core components:

  • Hadoop Common — Contains the libraries and utilities that support other Hadoop modules
  • Hadoop Distributed File System (HDFS) — The file system used by Hadoop. It is based on Java and highly scalable, which permits storage of data across multiple machines without any prior organization.
  • MapReduce — A programming model that uses parallel processing for big data sets consisting of structured and unstructured data, known for reliability and has a high tolerance for variation and faults
  • YARN — A framework for resource management. It handles the scheduling of resource requests from many distributed applications that are part of a Hadoop implementation.

Hadoop provides these major advantages:

  • Scalable — Is a highly scalable storage platform as it can store and distribute large data sets across many servers running in parallel
  • Cost effective — Designed as scale-out architecture to efficiently store a company’s data for future use
  • Flexible — Enables businesses to generate data from various data sources, such as social media and email conversations
  • Fast — With the distributed file system, Hadoop is efficient in processing terabytes of data in minutes.
  • Fault tolerance — The major advantage is its resilience to failure. That means, in the event of any failure, the backup of the original data is made readily available and hence the data remains intact.

Big Impact on Industries — The Power of Hadoop

Before we delve into various business functions, let us take a look at the impact of Hadoop in various industries:



Plausible Use Case

Banks, Insurance Companies and Security Firms

Personal customer data

Insurance underwriting


Call records

Financial Services

Trading risk


Personalized connection with the customer


Supply chain and logistics


Patients’ vital signs


Drug trials

Oil and Gas

Data in real time


Government programs working together

Big Impact on Core Business Functions

Security & Risk Management

As you know, the biggest challenge for a corporation is to secure its assets. Enterprise data is always at risk of fraud or security breach; the only way forward is to either adopt the existing and ineffective traditional security solutions or take another look at a new and effective model to protect the data at large and hence solve the problem at the core.

By and large, the traditional security solutions have not been able to address the big data challenge at the core. So, we are left with a newer solution and Hadoop could possibly address this challenge holistically.

At the core, Hadoop can address these challenges in the risk management arena:

  • Real-time analysis of big data
  • Enhanced capability to assess risk and hence allow you to be prepared with a contingency plan

Social Media Platform and Predictive Analytics

With the rapid growth of social media as a communication channel amongst customers, partners and the entire community itself, the model is serving as a simple, intuitive and interactive channel to connect with customers. You can use and adopt Hadoop to integrate and analyze the data to build a personalized association with the customer. With the personalized data captured around a customer, it can also increase the revenue.

At the social media platform level, Hadoop can address:

  • Analytics of the data to make real sense of the data
  • Optimization of multimedia that includes graphics, audio and video advertising to increase revenue
  • Social media analysis to predict the end-user patterns
  • Holistic customer view to engage the interest level
  • Professional services for manufacturing clients to serve the end user

Harnessing the Internet of Things

By definition, the Internet of Things is machine-to-machine communication, which is built on cloud computing and huge networks of sensors. According to a report by Gartner, there will be 26 billion devices connected to the IoT within the next six years. The report further says that the IoT presents a unique opportunity for organizations to utilize a vast amount of freely existing information to gain business insights. “The IoT connects remote assets and provides a data stream between the asset and centralized management systems,” the report states. “Those assets can then be integrated into new and existing organizational processes to provide information on status, location, functionality, and so on. Real-time information enables more accurate understanding of status, and it enhances utilization and productivity through optimized usage and more accurate decision support.”

So, where does Hadoop fit into the whole scheme of things? As more devices connect to the IoT, a humongous amount of data is generated that can offer valuable pointers about the end users. With the integration of IoT with Hadoop, Hadoop offers a powerful platform for analyzing machine and sensor data. At the Internet of Things level, Hadoop and IoT in conjunction can address challenges such as these:

  • Weather forecasting
  • Timely warning of natural disasters
  • Predictive analysis
  • Ability to record and monitor patients’ vital signs

Proactive Maintenance

The core problem in the field of proactive maintenance is that it is a daunting task by itself. Let’s imagine the scenario of oil rigs in the oil and gas industry, in which a component has failed earlier than expected. This can be an expensive and time-consuming task for the business because the required tools or people may not be available to address the problem in real time. Also, at the same time it is equally difficult to maintain the inventory of all parts or tools, as it may result in unnecessary cost. Using Hadoop, you can predict equipment failure and take appropriate corrective action well ahead of time. So, this saves a lot of operational cost by allowing you to perform preventive maintenance than to incur the cost of an emergency repair. The solution must bring in these capabilities for a potential equipment failure:

  • Capture the real-time and historical sensor data
  • Analyze the generated data
  • Evaluate the patterns of normal and errant behavior

Hadoop can be the solution to these challenges:

  • Approach zero downtime
  • Monitor the health of equipment during runtime


As solutions are becoming monolithic and complex in nature, it may not be possible to stick with a single traditional approach. Instead, an open architecture is the need of the hour. With a choice between traditional technology and the adoption of next-generation technology, a proper balance must be found. The right blend of these technologies can result in an efficient solution.

In the end, whatever may be the decision in terms of adoption of the next-generation technology (Hadoop) or any other disruptive technology, the ultimate objective of providing value addition to the customer remains the priority.


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Kaushik Pal
Technology writer
Kaushik Pal
Technology writer

Kaushik is a technical architect and software consultant with over 23 years of experience in software analysis, development, architecture, design, testing and training. He has an interest in new technologies and areas of innovation. He focuses on web architecture, web technologies, Java/J2EE, open source software, WebRTC, big data and semantic technologies. He has demonstrated expertise in requirements analysis, architectural design and implementation, technical use cases and software development. His experience has covered various industries such as insurance, banking, airlines, shipping, document management and product development, etc. He has worked on a wide range of technologies ranging from large scale (IBM…