The Big Data Revolution: Is Data Mining the Future of Business Success?

0
191

Big data doesn’t just help big businesses. If you thought it can only help the WalMarts and IBMs of the world, you have an exciting opportunity to leverage big data and data mining to further your company. From startups to solopreneurs, the information and visualizations provided through automated data gathering and analysis can lead to better decision making. Entrepreneurs need an overview of the big data revolution and how it’s affecting businesses. Herein you’ll find a primer on big data basics, a discussion of the pros and cons of using big data and how software developers are coming out with new software to support analytics in business.

Big Data Basics

Like anything else in business, planning provides the key to a successful big data implementation. You need to start with data mining objectives. What would you like to improve? If you have one product moving significantly slower off the shelves than others, data mining can tell you why it’s selling poorly and what to change about it. Analyze your current situation to pick one actionable thing you’d like to change in your business. Use it as the case study for your new data mining and analysis program.

Big data is just what it sounds like: a massive dataset providing key information to answer a prescribed set of questions. While relatively new to business, science has used big data for decades, essentially since computers were invented. One common example of its use (the modeling of weather data) produces a result with which we’re all familiar, weather forecasts.

While the National Weather Service uses massive sets of temperature, precipitation levels, wind speeds, etc., your data set more than likely comes from your sales figures or retail data by product code. More advanced data miners like Fabletics, use customer surveys to collect data and build on it with real-time sales data.

While the output differs, business has learned a lot from science about successfully implementing a big data program. The lessons learned and steps to follow work for any size or type of organization.

  • Create a genuine team project. You may have had an end-user step forward with a need. Include this user, but also realize you’ll need involvement from others, including your information technology department. You may need other departments to work together, such as marketing and sales. Identify members of each department interested in or knowledgeable about big data. They don’t have to be experts in it, simply actively interested and somewhat conversant.
  • Choose the team members based on the goal and objective. The second key to the right team members is choosing people who will use the data in implementing the changes. So, if you want to increase the sales movement of a product already on the shelves, you’ll need someone from sales, marketing, distribution, etc.
  • Always include the marketing department. The marketing industry was an early adopter. While not as early as science, you probably don’t have a NASA or NOAA department, but you probably have a marketing team.
  • Educate your employees as to when and why you’re implementing the big data program. Prepare them with the idea that change is coming.
  • Set your strategy. Plan how to mine the data and how it can help company performance. Formalize the objective and goals by putting them on paper. Set Key Performance Indicators (KPIs).
  • Create an inventory of your existing data. Data already in your warehouse, so to speak is a ready set for analysis. This lets you identify what you’re missing, identify its potential source and who maintains it.
  • Carefully choose your software and hardware with your end goal in mind. Choose tech that fits your company’s needs.

Pros and Cons

Big data can provide useful information, but it only shows its true value when a permanent program gets created and maintained. Like every business decision, there are pros and cons to weigh.

The pros include:

  • Uses available information sources like departmental data and retail sales data.
  • Provides information that can lead to an increase in sales or profitability.
  • Provides information that can lead to an increase in customer satisfaction.

The cons include:

  • Requires that the results can influence or improve the workflow requiring 100 percent buy-in.
  • Needs full integration into the existing business process.
  • Requires elimination of duplicate data.
  • Requires elimination of unnecessary data.

A properly designed data mining program can provide helpful data that can positively alter your bottom line. You must identify and obtain relevant data sources, honing the data set to include only the original sources. While you want a big set of data, you also want the “minimally appropriate” set of data, so it remains manageable. Your software choices help you with this.

Data and Analytics Software

While planning your team, plan your hardware and software team, too. Your IT department should guide your choices in hardware and software, but inquire with marketing if it already uses a data quality software program.

Data analysis is becoming an important part of business operations. In fact, more and more developers are coming out with software that’s engineered to process and analyze user data and figures. Business owners can use this information to make informed decisions. With this reliance on big data, it’s also important for businesses to focus on the quality of the data they’re using. Data quality software such as FirstLogic helps determine the relevancy and strength of the data piece or set. For example, eliminating duplicate news articles from a data set about a drought event.

In some cases, you can purchase an existing data set from a warehouse. This ensures a pre-vetted data set. You’ll be able to fluidly merge this into your own data set. This won’t provide a real-time feed such as those you can tap into by combining Internet of Things devices with your data collection. For example, you can draw instant, constant data from an automatic coupon dispenser set up on the in-store shelf with your product. Its IoT dispenser records each human that passes by it, how many take a coupon and at what time.

Merged with the retail checkout data of the retail outlet, you’ll find out which coupons got used. This tells you much more than how many units you sold. You know when couponers shop, the percentage of those who pass your product that stop and retrieve it. You may think you’re selling like hot cakes, but what if only ten percent of those passing your product buy it? Your data analysis software program will help you get to this data. Combined with your choice of data quality software, the analysis software you choose is your most vital choice you make.

Your data analysis software should make it easy to design and run reports. In most cases, a good program has ready-made report templates that put crunched data into familiar formats like sales reports. Your sales report will simply house enhanced information like how many of your potential buying audience purchased.

The benefits to implementing a big data program in any size business are many. Take the time to plan it fully. Invest in the appropriate hardware and software. Build an integrated team that involves both experienced parties and departments related to the objective and goals. Data mining can provide valuable insights, but you need to mine in a targeted, well-honed manner to create success.