8 Challenges of Data Management and How to Fix Them

The use of data is becoming increasingly crucial for businesses worldwide to manage their day-to-day operations and make business decisions. 

We have benefited from data management solutions from a top data entry service provider in terms of communication, automation, and business operations. However, it has also created an increasingly complex data environment.

It is becoming increasingly difficult to manage it across the enterprise in such a large representation. More so when spread across multiple locations and business platforms.

In this post, we will look at the most common challenges of data management and offer a solution for each one of them!

    1.Sync Systems 

The most common problem data-driven organizations face is keeping different systems synced. 

For business intelligence to be useful, its data needs to be high quality. This means that it’s important to enter data consistently, timely, and predictably into the system.

For instance, if you pull a report at the beginning of the month, but only half of the data has spread, your report will be incorrect.

Solution: To solve this problem easily, implement real-time data streaming. In other words, instead of requesting data every day, the data will be pulled in immediately. This is a pretty standard and automated procedure for most data management systems.

2.Huge Data Storage

This is one of the most significant issues that companies face. 

Large companies may have dozens of business solutions, each with its data repository, like CRM, databases, ERP, etc. But having such big data storage, there is a considerable obstacle that must be overcome to evaluate and handle it.

When data is located in different soiled systems, finding and integrating it on a universal data platform is tough to speed up data-driven decisions.

Solution: An organization’s primary priority should be to create a single source of truth for its data by eliminating data silos and connecting data from users, products, and suppliers.

3.Unuseful Data

Even the best data management systems won’t help a company if stakeholders can’t access and use data productively.

Unless a clean and transparent dashboard answers the appropriate questions and offers relevant insights to the right individuals, the data will be unuseful.

Solution: We have a few solutions for this problem. 

The first step is to ensure you have the right dashboard tools. These tools deliver visual reports to individuals who will use the data and queries and analysis in a user-friendly environment.

Besides that, you should also consider providing training and support for your data management platform. Personnel involved with the business intelligence process should be trained and given simple, dependable access to assistance for inquiries and troubleshooting.

4.Data Duplication

As a result of multiple siloed systems, common in corporate travel, duplicating data is inevitable. 

For instance: trips can be booked through an agency and simultaneously appear on the credit card feed. These systems need to be combined for a total trip cost – leaving us with a duplicate record.

Solution: Make sure your data provider has appropriate data verification processes accompanied by data deduplication tools that identify duplicate records. This will help you organize company information and detect records that might not be the same but share some similarities. 

Because each data source supplier writes the same information differently, you need to ensure your data deduplication tool can identify similar data points and flag them for deduplication.

5.Incomplete Data

If data is captured manually, incomplete fields may occur. As we mentioned above, data analyses are only as good as the data that goes into them. This indicates that the data is vulnerable to human mistakes.

Solution: The solution is to implement better data processes; hence, roles and expectations must be defined, naming standards or timelines, etc. It will be easier to prevent data errors, identify them, and handle them more efficiently with defined processes. 

6.Unskilled Resources

There is a serious shortage of qualified data management professionals available for immediate hire. 

These trained experts are generally paid more because they are essential in any company that must maintain strict data protection and management.

Solution: Training entry-level employees will be expensive for a company that works with new technology. Therefore, companies must do a good job of keeping these employees after acquiring the required skill set.

Let’s put it more simply. What is a technology for financial services that is skilled personnel for a data management-driven company.

To generate data-driven insights, businesses are increasingly relying on automation, which includes cognitive technologies like machine learning and artificial intelligence.

7.Data Security

Data is a very important asset that is collected after extensive research and deployment of resources. It contains sensitive information that might hurt the company as well as the individuals in a number of ways. Depending on how the data is stored and handled, you may encounter security difficulties with data management.

Solution: By properly securing your data using cutting-edge technology and understanding how and by whom this data can be accessed, you will be able to avoid data breaches.

8.Data Analysis

The last but not least issue is the data analysis, and we have managed to master data management challenges. 

Even if the data is of great quality, its raw form is of limited use. Technology is helpful in the analysis of vast amounts of data, but many challenges remain, such as correctly running the tool, extracting data logically, and so on.

Solution: You can use several advanced tools to help you import data and temporarily manipulate it so that you can analyze it based on given parameters.