Data is the new gold- goes the phrase around the IT industry as of now. However, people are often cynical of the phrase because they are never sure about how to use data so that it becomes a profit-generating device. More importantly, even if people have the data as well as the tools, the lack of management results in a lot of data going astray or the company ends up working with redundant, unnecessary data. That can have a really problematic impact on your business.
As an investor in data, you should invest in technologies that cover multiple concerns and there is an integration of the infrastructure across the various sectors of the business. In fact, if the units don’t keep track of each other, they can seriously harm your business goal as some units will work faster than others and end up in complete disruption.
Finding the right screw for the right nut
In business, it is always about the screw fitting into the nut. So, you need to ensure two specific things. One, you need to ensure that your business objectives are well defined. You have certain data sets in your hand which, when operated upon by analytical tools, will reveal certain insights that can be applied to business decisions thereafter. The flow of this process depends on the parameters on which data is built. So, first organize your questions around these parameters since they will dictate the outcome and the potential profit.
Secondly, you need to select the perfect algorithm for your specific problem. There are multiple methods that analytics adapts and that too varies with the type of analytics you are practicing. Certain technological exodus can have really bad impacts on the business if you follow them blindly. For example, the sudden hue and cry regarding AI and machine learning has pushed quite a few companies to try them out. However, you will be surprised to know that such technology is hardly necessary unless the use cases are extremely complex. For other scenarios, the simple tools are more than enough.
Being economical
Unless you are doing fraud detection or such advanced analytical procedures, you may probably never need AI as such. However, investing in AI requires a lot of money. So, if you invest in it just because you need some simple business trend analysis, you will be running low in budget. Moreover, if your fraud detection serves no business purpose or is of little help, then also it will result in a loss.
So, big data is more about elaborate planning, weighing the benefit of individual technologies as well as its extent of usage and then setting the goals to achieve them. Big data teaches you about risk taking and enables you in deciding upon dicey scenarios. With more and more tech giants turning towards it, it is probably the incoming of a humongous big data wave that has been brewing in the various sectors. However, to sail through it, you need to be prescient, decisive as well as look-before-you-leap kind of person.
