The explosion of software, applications and overall technology designed to help with the management and usage of big data have had businesses of all types and sizes getting in the game. Big data isn’t exclusively reserved for big business, and it’s becoming the leading way organizations are better targeting their desired audiences, tailoring their marketing, and improving their efficiency.
While the above-mentioned software and technology do simplify how businesses of all sizes are able to collect and analyze data, this doesn’t mean it’s an obstacle-free experience for all of them. If you’re considering adding or growing big data into your overall business strategy, below are some common mistakes to avoid.
Going Too Big
Yes, the phrase “big data” implies something that’s large, but a lot of companies try to go too big, too fast with their data and analytics. They can dive into data projects head-first, without thinking about feasibility or budget, and these projects rarely bring the results the business initially wanted. Big data, in any sense, is about achieving results through insights, and rather than trying to go too big with initiatives, it’s best to make sure you’re tailoring them to your needs and your resources, in a realistic way. Data projects can get expensive very quickly otherwise.
Not Working With the Right People
If your business can afford it, investing in some type of big data certification or training can be valuable. If you don’t have the ability to have at least one dedicated member of your staff trained in this area, consider hiring a consultant or freelancer. Otherwise, you may find that you’re running in a lot of different directions, without a lot of results.
Not Knowing The Questions You Want Answered
Big data isn’t just something that sounds useful in a business environment—it is useful, but only if you know why you’re using it. Too often there’s a sense of enthusiasm surrounding big data, but there isn’t a clear understanding of why a business is using it, or what they want to answer as a result. Big data needs to be accompanied by strategy, and it also needs to be guided by measurable metrics and a set of goals.
The Correlation-Causation Conundrum
With all data, whether it’s used in business or not, there’s a big problem, and that’s the confounding of correlation and causation. When companies start working with data, there is a tendency to make the assumption correlation indicates causation. When you’re looking at data and immediately creating a cause and effect relationship, the insights may end up being incorrect. It’s important for a business to be able to differentiate between correlation and cause, to maximize how they analyze and use data.
To sum up, big data is undoubtedly invaluable for businesses at all levels, but even the biggest corporations can make common mistakes with their handling of it. The above are some strong ways to avoid the potential pitfalls of big data in business.