Sep 24, 2015

Overcoming Challenges to Make Big Data Profitable

By Kelly LeBoeuf

This article first appeared in Pipeline Magazine.

The Big Data train has left the station and is moving full steam ahead. By the time you read the opening of this article, look at what will happen:


It's crazy what happens on the Internet in just 60 seconds, and its growing leaps and bounds every day. In fact, industry analysts predict that global data traffic will be 100 trillion GB by 2025.

What does this mean for organizations today?

Well, one thing is for sure: we need to be prepared on all fronts. There's a lot to consider and there is no "one size fits all" answer.

The ecosystem of Big Data is no longer structured data, or data for traditional communication purposes, such as emailing and phone calls. Big Data now includes:

  • Machine 2 Machine (M2M)
  • Internet of Things (IoT)
  • Mobile
  • Cloud
  • Data storage and networks

It's no longer just information; it's also the analysis of the information that we collect. Because Big Data is so vast and complex to understand in its full capacity, we can break it down into five V's:

Excelacom Five-Vs-Big-Data
Big Data: Five V's

Let's take a dive into each of the five Vs:

  • Variety describes the different types of data, which is expanding every day. Structured data that has been commonly stored in databases is now joining unstructured data, including social media information, wearable data, and video streaming.
  • Volume is the scale of data, how it's acquired and stored. The volume of data is expected to increase from 2.3 trillion gigabytes of transfer today, to over 43 trillion by 2020.
  • Velocity is the speed of data processing and Veracity is the uncertainty vs. the reliability of data. IBM reports that poor data quality costs the US economy over $3 trillion dollars a year. ·
  • Value is how to make data profitable by using analyzed data to increase revenue and decrease cost.

The variety and volume of data that is being passed through the networks is staggering which effects the velocity, or how quickly technology and organizations can break down and analyze the entire overload of information that's collected. We need to use efficient network connections, monitors and sensors to map out behavioral patterns and applications to shape these patterns. And, the bottom line with all of these V's is: Value: monetizing on Big Data.

There is no ownership over the Big Data ecosystem. It's constantly changing and legacy systems are having a hard time playing catch up. And it's no longer just data. It's also the analysis of the data which is critical as well. Long gone are the days when the most effective strategies that emerged from the operators' IT departments loaded up on new platforms, systems and "critical" functionality that were often underutilized, or even worst yet, not fully deployed. Operators must now focus on making their infrastructures "lean and mean" and be ready for innovative technologies on the horizon.

With the Big Data forecast for 2025, we need to respond, sooner rather than later, with systems and processes that make this data manageable and able to be monetized. Within every industry, everyone is asking the same question: how can we make Big Data profitable? As with any new technological paradigm, there are hurdles. The biggest challenges to monetizing Big Data can be divided into three silos: business, technology and regulatory.

BIGGEST CHALLENGES: Business, Technology & Regulatory

Business Challenges

On the business side, we need to focus on analytics, accurate forecasting, adopting new tools and technologies, and getting real-time insights. We need to determine how we can gain profit from something that costs time, money and resources to keep up with.

  • 1. Business analytics: We need to use analytics to increase our operational intelligence and measure whether it's working and who it's working for.
  • 2. Accurate forecasting: Using these analytics to make reliable inferences about the future of the market. We know what we did, so how can we do it better? What's next for our demographic? What can we infer that our demographic will respond to?

Real-time insights are the key to making sure that the analytics and forecasting are worth it.

Time is essential. Companies want to know what's going on immediately so they can figure out how to respond accordingly. Big Data can do this.

Technology Challenges

Technology challenges include our workforce, infrastructure and tools. Each are equally important.


We need to make an effort to train the workforce that's already in place and hire top talent to fill the gaps. It's a booming market for Big Data professionals. According to Forbes, IBM advertised 2,307 new positions in Big Data in the last 12 months. Those professionals with VMWare expertise, application development, open source technology experience, data warehousing and solid programming skills will be the ones to hire.


Simplify, simplify, simplify! Agile IT is the business and simplification is essential. From an architectural point of view, the fewer systems you have, the more agile you will be.

Using this approach, we need to be smart and build an ecosystem for the future:

  • Combine legacy systems with modern systems to reduce cost. Leverage the existing architecture and use an evolutionary approach to build the smart ecosystem of the future. Don't start from scratch; it will cost valuable time and resources.
  • Prepare the infrastructure for business-critical production applications.
    • The customer experience depends on high availability.
    • Make sure to plan for hardware, network and data management applications.
    • Data storage must have the capacity to hold and update data at a low cost.
    • The network must be able to efficiently transfer data to/from frameworks and architectures, while providing for future growth.
    • Data management applications must be flexible for processing, organizing and utilizing massive amounts of data in real time.
  • Analyze data for predictive analytics and targeted marketing campaigns.


To be successful managing Big Data, it's important to invest in proven BI tools and apps. The right tools provide the ability to leverage the vast amounts of data that's collected as well as gain invaluable insight. The best tools are the ones that are easy-to-use and provide interactive interfaces that help us gain control and make informed decisions with Big Data.

Regulatory Challenges

We need to be aware of existing and new regulations that restrict the use, storage and collection of certain types of data. Obtaining and analyzing data to improve business practices will help to increase revenue and decrease cost, but with new laws, regulations and governance over data here in the US and in other countries, it's important to make sure the methods in which data is obtained and used to generate new streams of revenue are in line with rules and regulations.

The Keys to Success

Despite all the challenges, there are many opportunities to monetize on Big Data and gain an advantage over the competition.

  • Increase revenue with
    • Tailored advertising, products and services
    • Predictive analytics to gain real-time insights into customer behavior
  • Decrease costs through
    • Fraud Prevention
    • Network Optimization
  • Improve the Customer Experience with
    • Instant customer feedback
    • Targeted and predictive marketing
    • Tailored products and services

Across the three silos, there must be collaboration to overcome these challenges. For example, the business and technology silos need to work together to find synergies and automate IT and business processes for the most efficient and effective operation across the enterprise. Work together as a team and be smart.

Big Data is skyrocketing. With an evolutionary, innovative approach, businesses can use this opportunity to take the lead over the competition. If you would like to find out more information on how Excelacom can help your company overcome the challenges of making Big Data profitable, please contact us at:

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