The idea and concept of “Big Data” has been around for a while now, however it seems there are many people who still believe it is shrouded in mystery. Therefore, in the following post we are going to debunk some of the top big data misconceptions.
Every business has access to data, from transactional, mobile, financial and behavioural data, to customer research data and social media data. What’s more, as technology evolves and buying trends change more and more data is becoming available. However, it is the ability to transform all this data into actionable insights that is invaluable and is the definition of “Big Data”.
Analysing big data enables businesses to monitor trends and adjust their strategies accordingly. It aids the creation of new products and services in relation to increasing customer demands. It also provides detailed insights to help you cut unnecessary costs and invest cash where it has the potential to increase your ROI.
Yet, businesses continue to doubt it.
Here are some of the top misconceptions debunked:
It’s all hype. Big data is much more than just a fad, it’s very much here to stay. The value in which it can provide a business is astounding and it’s been reported that in the next two years, 73% of marketers plan to implement a big data analytics solution within their business. Why? Because, analysing and reporting on accurate data helps you create roadmaps, projections and forecasts that enable decision makers to set budgets, targets, identify trends and ways of making improvements.
To remain up to date and ahead of the competition in the ever changing world of business, it is more important than ever to get on board with big data.
It’s the IT department’s responsibility. Ensuring there’s an intelligent solution in place; capable of analysing your data may partially be the responsibility of the IT department in terms of implementing the solution. However, it is the responsibility of everyone within an organisation to use the systems in place accordingly, to input all relevant data and to highlight any anomalies. This includes the finance, sales, and customer service teams, along with the marketing department, since according to an article on Teredata.com, 45% of big data deployments are for marketing purposes.
You need a lot of data. Big data can be defined as extremely large data sets that can be analysed to reveal trends, yet there is a distinction between having lots of data and having good quality data. Huge data sets may have numerous errors, duplications, be out of date or irrelevant. Therefore, your data must be clean and of good quality to ensure the results you get are not skewed in any way.
Less is more when it comes to data. If you have good quality data from a wide variety of relevant sources, you’ll be able to yield better results. As Gary King from Harvard’s Institute of Quantitative Social Science explains, “The definition of what is considered “data” has changed. That is, most people think of data as rows and columns of numbers, such as Excel spreadsheets, however, Big Data is predominantly about semi-structured data or unstructured data.” He goes on to say, “…when people begin grasping the variety and velocity of data, they begin to find more innovative ways to use it.”
Don’t just collect a vast amount of data. Clearly define what it is you want to know in order to identify the data that is essential to creating actionable insights and to improve your business’ performance.
Big data is hard to come by. As Dave Stewart, Founder and CTO of Cake explains, “There is a big misconception about the technological complexity involved with processing big data, while in fact, new developments continue to simplify and streamline the task.” There are a variety of solutions available that help businesses interpret their data.
There are tools that pull information from your accounting software, customer relationship management system (CRM), email, website analytics and much more. Many of these tools will allow you to export your data into Excel for easy manipulation so you can create custom reports and present it in an easy to understand format – It doesn’t have to be difficult or expensive.
It’s the solution to all your problems. The ability to monitor, maintain, measure and analyse data will enable you to manage and improve your entire operation, but if you don’t have the correct processes in place, or set out clear goals you will struggle to leverage insights.
Some opinions expressed in this article may be those of a guest author and not necessarily Analytikus. Staff authors are listed in https://www.datasciencecentral.com/profiles/blogs/big-data-misconceptions
