Learn to Avoid the Potential Data Management Pitfalls

Learn to Avoid the Potential Data Management Pitfalls

In this data-centric and data-driven world, managers are bombed with data through dashboards, systems, and reports. Business leaders and managers are repeatedly reminded to make decisions based on data analysis. Senior leaders are tempted towards big data offers because it helps to develop a competitive edge yet some of them struggle in describing the probable tangible benefits.

The data scientist role is in demand as organizations are spending fortunes each year to install software that captures, stores, and analyzes the data. The marketing department is jammed with tech, data-savvy experts. The business arena is data-focused, where data is a tool bursting with opportunities. It needs a proper approach to identify the potential of the data for making remarkable business decisions.

EWSolutions offers data management articles and podcasts to help readers. Their online library has plenty of topics regarding data governance and management. Give it a visit or you can enroll in their data governance or data steward training course.

Remember obtaining and evaluating data is not without risks and challenges. Data is a business savior assumption is a myth. Let’s discuss some potential pitfalls and take steps to avoid them.

Poor data quality

Data quality also counts just like in physical products or objects. The data that is stored in organized repositories or databases is often inconsistent, incomplete, or obsolete. For example, marketer’s database holds duplicate records with a little different version of names or addresses. This tiny data quality error becomes expensive for the marketer. Data quality is significant when decisions associated with marketing or strategies are being planned. There are software solutions available to track and enhance the quality of formatted data.

Drowned in data

Data is all across the business. Everyone involved in the business collects data including marketing, executives, sales, management team, accounting & billing department, and customer support. Besides, information is obtained from social media and search feeds.

With the increase in the data volume organization feels drowned and if data cannot be easily accessed or is incomplete or duplicate then it becomes useless as you cannot leverage it for making decisions.

So, data quality becomes an inherent issue. Even a powerful and advanced data analytic application offers flawed decisions. Therefore, never blindly trust data analysis output. You must have confidence in the information used to perform the analysis. Data integrity is a must!


Never view data analysis output as a conclusive report because often it reveals the correlation and not causation. Trusting the data analysis can create confusion between causation and correlation. The latter displays a relationship but does not imply B causes F. Establish a causal relationship for making insightful and less flawed decisions.

Amplified biases

Even after a complex and extensive analysis of data, you have to still draw an implication and make a judgment. Here your cognitive biases amplify. It is a human tendency to trust the data from sources they depend on or like. Many trust data that supports their expectations and quash data that doesn’t. These biases add to the challenges and increase the chances of making a false decision from the analyzed data.

Learn to leverage the valuable data and win. Besides, avoid the above pitfalls you encounter on this journey!