Through 2015, 85% of Fortune 500 organizations will be unable to utilize big data for competitive advantage. That’s what a recent study from Gartner says. The world of data is a complex ecosystem and it’s not organized the way we want it to be.
Here, we’ll try to simplify things. Smart decisions require the right data and right information. Managing and implementing a solid infrastructure towards this requires the right resources–time, people, tools, and processes.
Identify Business Objectives
The purpose of data is to provide you with the information you need to make good business decisions. Are your business decisions leading to positive outcomes or negative outcomes? Then, figuring out how to adjust moving forward.
Data initiatives must begin with business objectives. Why does the business unit exist? This might involve discussion(s) with senior management. Once business objectives are identified, you can define the problem and issues that you’re solving.
Define the Problem and Scope
Figure out what you want from your data. What value can you extract? Here are some questions to ask:
- Context. What are you trying to achieve? How does this fit into your business objectives? Who are the stakeholders invested in the outcomes of the project?
- Need. What issues can be addressed with the outcomes of the project? Are you trying to bridge gaps? Will this project empower or expand initiatives?
- Results. How will stakeholders use the results? What’s the definition of project success?
Defining the problem and scope should provide clarity, providing specifics on what needs to be accomplished. This should cover all aspects of the objective. The scope allows you to determine what data to use, how to analyze the data, and how to apply insight that you gain.
Use the Right Resources
Big data won’t solve all business problems by itself. You need the right tools. If you’re building a house, you can’t build a house without the proper materials. To ensure that the materials fit into a house, you need the right equipment and tools. The equipment and tools still requires the manpower to operate them.
According to InformationWeek’s 2015 Analytics & Business Intelligence Survey, 48% of analytics and BI decision makers and influencers identify “ease-of-use challenges with complex software or less technically savvy employees” as a barrier to success. For the third consecutive year, it’s a close second to “data quality problems.” The right tools and the right talent will make the job efficient and more accurate. The talent and tools are required to clean the data, analyze it to identify relevant relationships and trends, and to present findings in a useful manner.
The first step to exploring data is to clean and prepare it. That means ensuring columns and rows are correct, that there are no blank entries, that the data is in the correct format, etc. Raw, unclean data may skew results or lead to inaccurate findings.
Once you validate your data, perform analysis. Filter and segment the data so you can focus on areas and groups of interest, and identify strong relationships between variables. Compare time ranges to find events that might trigger certain outcomes. As you discover relationships, you can begin to piece together a story.
Tell the Story
Data visualizations can convey information in a clear, easy manner. They focus on trends and highlight unexpected findings. They engage viewers and even allow them to interact with it. They accelerate understanding and allow viewers to take a deeper dive without losing focus of context.
A good data visualization is able to stand on its own and tell your story. Visualizations should be aesthetically appealing as we are drawn to beautiful exhibitions. However, that’s not the main goal. The goal is to present knowledge, wisdom and value. Ask yourself, is this visualization actionable? Are stakeholders able to use this to postiviely affect outcomes?
This process will help you to extract true and meaningful insight from the sea of data. After all, the value in big data is in our ability to understand it. We can move on from capturing big data to empowering business decisions and outcomes. This will help us realize the big data promises of changing the way we do business.