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How To Avoid Big Data Confusion, And Implement A BI Solution

How To Avoid Big Data Confusion, And Implement A BI Solution

How To Avoid Big Data Confusion, And Implement A BI Solution

Can doctors predict a disease before symptoms appear? Can businesses use real-time data to advertise more effectively? These are some of the questions posed by Join Viktor Mayer-Schönberger of the Oxford Internet Institute and Kenneth Cukier of The Economist in their 2013 book “Big Data: A Revolution That Will Transform How We Live, Work and Think.”

Big data” refers to society’s increasing ability to collect and compress near limitless storehouses of information, analyze it immediately, and draw important conclusions from it. Advances in data analysis allow everything from friendships to airplane tickets to be categorized in a searchable format through social media and search engines. Users can then comb through such information to find trends and patterns. Real-time data, social media analytics, dashboards, and more are all subsets of such analysis.

For businesses, big data allows them to revise their market strategies in near real time, based on incoming data and market patterns. Many advisors already believe that big data is as crucial to success in the business world as the Internet, because more data can lead to more accurate and specific forecasts.

However, many small businesses assume that big data is only for large companies with full-time IT staff and data warehouses. Rebecca Shockley, Global Research Leader for Business Analytics at the IBM Institute for Business Value has a different perspective. In her opinion, companies of all sizes can effectively utilize big data. “Big data is quite simply data that cannot be managed or analyzed by traditional technologies. ‘Big’ doesn’t have to be really that big; it’s just bigger than what you’re used to dealing with.”

Overcoming Confusion

One of the main problems for small companies is identifying which data sources matter, and which can be ignored. Sifting through data can seem like an overwhelming task for a small company with few resources. However, Shockley encourages companies to take things one-step at a time. First, decide what type of action you want to take. Do you want to acquire new customers? Or, do you want to earn more revenue? Once you know what your desired outcomes are, start by analyzing the internal data (such as sales logs, or manufacturing info) you already have before moving on to any outside data.

Besides your in-house data, you can likely gather pertinent information from sources such as social media, customer feedback, employee surveys, and marketplace data (think pricing indexes, or consumer confidence). Once you understand what information you have, and the various streams you’ll want to combine, you can consider implementing business intelligence software that will help analyze and assimilate such data.

Some of the benefits to business intelligence software include the ability to explore and analyze data through dashboards, and access to tools that visualize new information in real time. These types of services allow businesses to track both consumer trends and operations information in order to make more informed choices. It’s vital to choose software that will help you focus on the important details. Are you looking for a tool that allows you to explain complex numerical data through simple visual content? If so, it’s best to focus your search on visualization-specific programs. Are you looking for software that analyzes data and analytics to improve outcomes? In this case, you may need a more comprehensive platform. During every stage of the BI implementation process, it’s important to evaluate your needs, and make sure the tools you’ve selected are going to help solve defined problems.

Forbes contributor Greg Satell believes that business owners can determine what data matters through the Bayesian inference, which encourages individuals to make educated guesses and update their hypothesis as new information is acquired. He wrote, “In the past, we’ve mostly operated by testing hypotheses. The problem is that’s all incredibly expensive and time-consuming. With big data, we can simply look for patterns that correlate with real world phenomena.” After identifying a potentially useful model, business leaders can make the necessary changes as more data comes in.

Through knowing what your objectives are and which business intelligence programs to use, you can avoid confusion and use big data to your advantage.

keith-cawley

By Keith Cawley,

Keith is the media relations manager at TechnologyAdvice. He covers a variety of business technology topics, including gamification, business intelligence, and healthcare IT. Connect with him on Google+.

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