Businesses are becoming increasingly reliant on data, so much so that it is considered the currency of the digital age. When they first start collecting data, businesses are prone to make mistakes, often due to the massive amount of data flowing through. And even though gathering data is now easier, data analytics solutions can only be as effective as those using them. 

Below we have mentioned some of the biggest mistakes businesses can make when managing data and how to avoid them. 

Taking on too much data to analyze from the get-go

Businesses are awash with data. It’s everywhere, from their website to their social media profiles and performance dashboards. Many businesses make the mistake of taking up too much data for analysis before considering what they want to solve.

Over time, if a company analyzes an overwhelming amount of data, it will eventually reach a point where projects get stalled due to “analysis paralysis.” It is better to take the project’s well-defined data, support the strategy and business initiative, and avoid overanalyzing it.  

Collecting subpar quality and inaccurate data

The problem with collecting low-quality data is that it can lead to inaccurate observations. This, in turn, can result in significant financial losses and wasted time for businesses. To counter this issue, businesses need to open up or create portals that are easy to navigate and accessible to non-analysts. They also need to ensure a shared space where only discussions about data analysis happen.

Another good way to combat this issue is by introducing machine learning and data analytics solutions to bolster the process further.

Not using a workflow-management tool.

Large businesses often produce analytics on big data to make better business decisions. However, knowing what to do with this information is only half the battle. Having a workflow-management tool to act on the results is critical for success. Therefore, companies should put an equal value on big data analytics solutions that can use this information automatically.

Investing in heavy infrastructure for data access and security

Companies need a secure and accessible infrastructure to handle all the data produced. However, with more and more businesses moving towards the cloud- and software-as-a-service models, they don’t need to make the mistake of investing too heavily in infrastructure. Some companies build their infrastructure specifically for big data analytics services, but this again requires them to have high–level expertise and try to replicate the best-in-class practices.

Not investing in a business intelligence professional or team.

One of the most common areas where certain businesses struggle and make mistakes is when they don’t have a dedicated business intelligence team. This team works with data and ensures efficient analysis so the company can progress.

It’s common for businesses to make the mistake of only considering the technical cost when budgeting for investment without considering other important factors, such as skills development and training for staff members, as these areas can significantly impact the business’s growth.

Conclusion

Data helps us answer questions and solve problems, and it can inform some of our most important business decisions. Whether a small startup or a multinational corporation, data can help you make more informed decisions, identify new opportunities, and even save money. However, when it comes to data at work, there are still some big mistakes that businesses continue to make. Be mindful of these mistakes and tread carefully to gain maximum results from your data analytics efforts.