The main purpose of big data is making meaningful use of the high volume of data that the organizations receive on a daily basis. But there is a lot more to it than this. Since it was coined, many organizations and even individuals have misinterpreted its concept, and this has led to the birth of many myths.
Those who are just adopting the concept at the moment should be careful not to be misled as well. Busting the top myths is important for everyone and this is very informative.
Machine Learning and AI Are the Same
No, they are not. Machine learning is all about algorithms that recognize patterns and relate images and videos to a set of instructions. Machine learning is also frequently used to analyze big data in companies. On the other hand, AI is a technology that makes logical conclusions after looking at the various analyses. Although both work together in many ways, they should be treated as different approaches to big data.
Big Data Means “A Lot of Data”
You are wrong to think that big data is all about receiving a humongous amount of data. It encompasses a lot more than this, as we mentioned earlier. However, the data is pretty unstructured and diverse, which means that the systems that receive it should be highly sophisticated. It is quickly sorted and sent to different databases to await further analysis. It is possible to fill out one form, but the data will go to different data lakes.
Human Need is Getting Replaced by Algorithms
Many people believe that algorithms that work behind computers and machines will make human needs obsolete. But according to data experts at ActiveWizards, the need to have professionals on top of things is even more crucial now that the data volumes are getting bigger and bigger. There is a lot that they can do alongside the algorithms including controlling what analysis technology should do.
Big Data Use is Costly
Truth be told, there is a cost implication when implementing big data concepts in your organization, but it is not as expensive as people put it to discourage others. Those who have bought into the myth have lost a lot more revenue because big data save costs in a company and also adds revenue. Thus, the cost is low in relation to what you will get in return. The most prudent approach is to research well on the value that big data will add to a company before the concept is adopted.
Managers and Employees are Adopting Big Data Very Well
While many have accepted the use of big data in their organizations, not everyone is ready for it. After ten years in use, there are still many organizations that do not have the resources and manpower to handle big data. Others are skeptical about its applicability and still prefer to use spreadsheets and other simple computer operations.
These and more myths have misled many people in relation to big data. Now that you know the most common myths and the truth behind them, it is time to make the right decisions.
