In this day and age when every person creates an extensive digital trail on a daily and even hourly basis, it should be clear to everyone that any business that aspires to stay relevant and rise above the competition needs to find a way to harness these vast pools of information. But, just how much data does your business need for efficient analytics?
The truth is – not that much. As a matter of fact, gathering incomprehensible amounts of redundant and irrelevant information can only put a strain on your business’s infrastructure. In this case, you should prioritize quality and efficiency over quantity.
So, let us take a look at five hints that should help you gather the best quality data that can truly perpetuate your business.
Try starting with small data
As we already touched upon, the problem most businesses obsessed with big data have is that the information they need to gather doesn’t need to be extensive but relevant. That brings us to the datasets we like to call “small data”. Unlike big data that consists of large structured or unstructured information sets that are very hard to organize and analyze, small data can be usually accumulated in regular Excel files.
If you have a problem developing the necessary infrastructure for collection and analysis of big data, it is highly advised to start your accumulation methods with smaller sets of information that are absolutely necessary for your decision-making and then scale up as your skills, infrastructure and needs grow.
Collect only the things that are relevant to your current needs
This way you will drastically reduce the volume of the information sets you will need to gather and store while getting the opportunity to improve their depth and quality. For instance, if you are branching out to the Australia and Oceania region and you want to know how your company is perceived by local media, there is no need to take a deep dive into the regional data pools. You can simply contact the experts experienced in local social media monitoring and get all the relevant info you need regarding this topic.
Casting too wide of a net while looking for information can only produce a lot of redundancies and put an additional strain on your data warehouses.
Establish efficient collection workflow
The benefits behind this decision are numerous. First, you are taking the randomness out of your data collection process and making it more streamlined. Second, by setting the clear goals and manageable steps that lead to that goal, you are allowing the data collection to be performed repetitively, seamlessly and efficiently by anyone you task with the said duty. This way, you are not only making the process more comprehensible for your own employees, but also increasing the potential for outsourcing.
It is important to remember, though, that while you are setting up your workflows, you should make your data structures easy to revise, update, and expand if the opportunity arises.
Outsource the collection activities
Being able to efficiently collect, process, store and analyze the big pools of data requires a well-developed infrastructure and a highly trained staff. Developing these two important resources can put a strain even on the budget of some bigger companies, let alone small and medium businesses that are still struggling with basic operational necessities.
If you have a problem with developing an efficient collection infrastructure, one of the options you can resort to in order to solve this problem is to hire the experts who can help you create workflows and develop an appropriate database system. The very process of collection can be outsourced as well.
Build your infrastructure with integration and validation in mind
One of the biggest problems regarding contemporary data harvesting is the fact that relevant bits of information originate from a wide variety of different sources. Enterprise applications, emails systems, social media streams and other channels we use to learn more about our customers don’t always produce compatible sets of information. This is the reason why your company should address this burning issue from the get-go and invest in some of the popular data integration tools.
Finally, there is the problem of validation, or in other words, reconciling conflicting information about your clients (e.g. different data sources are specifying different addresses). Much like data integration, validation can also be solved with the combination of improved data governance policies and tech updates.
We hope these five hints will give you some basic guidelines that will make your data collection process more streamlined and efficient. We are living in a world where knowledge is the greatest asset a business can possess. Use this fact as an advantage then, and try to collect the best data your resources allow you.