Online education portals like Udacity and Coursera are really changing the world of remote learning in significant ways. By making free and high quality education accessible to a global audience, these platforms are opening up undreamt of possibilities for communities around the world to improve, grow, and prosper in the digital economy of the 21st century. Education at top tier colleges and universities has traditionally been a social and economic privilege, but now anyone can join in the learning revolution by sitting in virtual classrooms with the world’s best and brightest educators. Whether this involves learning how to code and build smart phone apps, or starting up a new business, or learning about public health literacy, the sky is the limit of what’s now possible.

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Big Data – Getting the most out of predictive analytics

The Big Data revolution continues to transform all levels of business and society in ways almost unimaginable just a few short years ago. Indeed, the best word that comes to mind in describing this phenomenon is “epic.” Gartner best summarizes the latest trends as follows: “Big data creates a new layer in the economy which is all about information, turning information, or data, into revenue. This will accelerate growth in the global economy and create jobs.”




Closely aligned and integrally related to Big Data is the field of Predictive Analytics, or PA. As one article declares, predictive analytics is “Big Data’s Greatest Power.” The article goes on to describe PA as the science of taking the vast store of historical data – the ginormous amount of structured and unstructured data stored “out there” – and using data mining and statistics to make accurate models and predictions of future customer behavior and business scenarios in near real-time. PA is critical for providing a complete view of customer behaviors and trends. And businesses that learn to capture these insights will increase revenue, cut costs, and stay ahead of the competition.

Predictive analytics is complex and multi-faceted and it’s impossible to give a thorough overview in the confines of this article. But we want to pull together the highlights to capture the process and get you thinking about specific steps that will comprise your predictive analytics strategy going forward.




Identify your business problem: What is the primary question you wish to solve? Look across all lines of your business to see where the painpoints are. What are your highest expenditures? What steps need to be taken to improve the bottom line? For instance, you may decide: “We want to identify the top 10,000 customers who are most likely to respond to our mailers.”

Understand your data: Start by asking some basic questions: where does the data reside, who owns it, how far back, and in what format? There are also growing numbers of companies on the market that specialize in helping businesses to analyze their existing data, or else to generate new data, in order to derive a 360 degree view of their customer interactions and behavior.




Clean your data: Disparate sets of data often contain duplicate, wrong and missing values, and other inconsistencies. Your data sets will need to be validated or “cleansed” to ensure optimal outcomes. Leverage available software tools to make this process less painstaking. Fortunately, there are many tools on the market that help automate the data preparation and cleansing process using graphical ETL (Extract, transform, and load) capabilities.

Build & evaluate your predictive model: This is a multi-faceted process that involves identifying the time frame of your study, choosing the dependent/independent variables, selecting the right methodology, and then building and testing the model. As a small business leader, who may be new to the world of predictive analytics and modeling, one of the most important points is to not get overwhelmed. The best advice especially for the novice is to make ready use of the growing numbers of predictive analytics tools on the market today.

Deploy the predictive model: The journey has been a long one, but don’t stop short of rolling out the predictive outcomes to the rest of the organization. Deploying your model means sending live data to your predictive model and then feeding the results to your favorite data visualization tool. The results will be worth it!




To keep competitive in today’s environment business leaders and stakeholders need to develop a clear predictive analytics strategy. And while it’s easy to assume that Big Data and PA are only for big businesses with well established budgets, nothing can be further from the truth. The path is wide open and resources are readily available for small business leaders to jumpstart their PA strategy today. The oft-quoted phrase, “A journey of a thousand miles begins with a single step,” is appropriate here because getting aligned with Big Data can seem daunting for some. But with clear planning and deliberate strategizing, predictive analytics can be a big win for your small business in the year ahead.

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About Jeffrey Walker

Jeff is a business development consultant who specializes in helping businesses grow through technology innovations and solutions. He holds multiple master’s degrees from institutions such as Andrews University and Columbia University, and leverages this background towards empowering people in today’s digital world. He currently works as a research specialist for a Fortune 100 firm in Boston. When not writing on the latest technology trends, Jeff runs a robotics startup called, along with oversight and leadership of - an emerging market assistance company that helps businesses grow through innovation.