Overcoming the five most common data analytics challenges
There are few common data analytics challenges that every business face from time to time. To optimize your business, you must accumulate and analyze the data and feedback you’ve been getting from all aspects of your business, which can be a nightmare.
If you lack adequate resources internally, you must hire a few competent data entry professionals to do your data analysis for you if you can. There is a massive shortage of professionals who understand big data analysis. If you can catch one looking for a job, you don’t need to give it a second thought. What good is data if you don’t learn anything from it?
Listed below are five common data analytics challenges and their solutions.
The first challenge you might run into when working with data analysis is the sheer amount of data itself. If you’re running a growing business, an increased amount of data should be an expected side effect of it.
Data can come from a million different aspects of your business – data about your employees, products, the company itself. You need to know how to integrate and make use of your data. Not managing your data correctly can also lead to more expenses, as you won’t be sure where the money is going.
Be organized and organize your data. If you can’t organize your data yourself, employ a professional to do it for you. Well-organized and optimized data can bring innumerable benefits to your business. Form happier employees, who will put in more work, to better cost-effectiveness of your business in general.
Well-organized data can also give you insights into the future of your business and possible insights into new trends that might be emerging on the scene. It can also help you dodge risks you might face in the future. There is nothing more important about data than keeping it in check.
Out of the many common data analytics challenges that companies face, one of them is that data can sometimes be unreliable. There is no secret about it, not every single piece of data is crucial or completely accurate, so you need to bear that in mind when you’re working with what you have.
Data can sometimes be not only unreliable but also blatantly dishonest. It can contain contradictions, duplicates, and a wide array of problems.
Although unreliable data is a huge problem, handling data is simple with a simple solution. You need to learn how to recognize fake and inaccurate data and root it out of your data stash. Hiring a professional to do this for you is the simplest way, but it’s not the most cost-effective.
Some ways of avoiding unreliable data are:
1. Having a proper data model
There is no business without a suitable model, and there is no useful data without a data model.
2. Comparing new data to existing data
When you’ve added your data to your data model, and it seems a little bit fishy, don’t fret! Compare it with existing data and use the next step to determine if it’s of any use.
3. Common sense and logic
You’ve added your data to your data model, and you’ve compared it with existing data. Good! Think about what you’ve accumulated and what you’ve added. Does it make any sense? Could it make any sense? If you’re not too sure about it, don’t be afraid to seek a second opinion.
Too many advanced and complicated aspects of your business can ruin it. Drowning yourself in addons and, in turn, addon data can be frustrating. There are essential addons any company should employ to make it run more smoothly, and that can provide valuable feedback for optimization.
Think before you add! More does not necessarily mean ‘better.’ What use are endless programs and addons if all they do is drown you in useless data, taking you away from more pressing issues?
Inaccessible data. What good is data if people who need to read it can’t reach it in any way, shape, or form? Decision-makers and people who are employed to predict and prevent risks become virtually worthless if you don’t give them the chance to do their job correctly.
You can’t ask a pot maker to make you a statue without any clay, can you?
You need to integrate all the data you accumulate into a centralized, secure, and available system that you can control. You need to determine who can see the data, and you must also ensure that the data you provide is safe from people who might have malicious intent.
Having a centralized data hub is a sure way to allow authorized people to observe and use the data in a split second, which can mean a lot for your decision-making and risk prevention.
Data accumulation itself can be a problem. Lack of organization within your business can cause both top and lower-level employees to submit their data infrequently. This automatically ruins the harmony and synchronization that properly organized data brings.
It can ruin a business with inconsistent data, and in turn, wrong data and predictions.
Proper management is the solution to this problem. You need to paint a picture of how crucial adequate data submission is for your business to all your employees. Without their cooperation, this whole topic is unavailable to you, so you need to do your best to encourage it.
Sometimes, the best way to paint a good picture is literally painting a picture. Don’t worry, though, you don’t have to bust out the paintbrush, as graphs and charts are an amazing way to show data. There are many s programs and tools that can help you represent data visually, eliminating the need to create a map on paper.
You need to take all your data seriously. Overcoming the few common data analytics challenges is not as difficult as it may seem. Data analysis is one of the best ways you can take your business to the next level, improving its effectiveness and increasing the amount of green in your pocket!