12 Common Data Management Mistakes to Avoid for Lenders

One of the largest data breaches in history occurred in 2016 on MySpace. About 360 million records were exposed. 

If you're a business owner, then you might wonder how to make the best use of your company's data? While data management might seem tough, there's hope. 

This article will explore the common data management mistakes to avoid. Read on to explore these mistakes, and keep your business not only efficient but protected today. 

Why Is Data Management Important? 

Data is what helps you determine business strategies at different levels. It's vital for the development and growth of your business. 

When you have strong data management, it'll lead to actionable, accurate, and quality data. Without data management, your data assets can become useless. 

What Is Data? 

Data is a set of characters that is obtained and then translated for a purpose. It's normally for analysis. 

It needs to be put into context in order to do anything. There are different types of data including video, picture, sound, text, numbers, single character, etc. 

1. No Data Protection

You want to ensure that your data management strategy includes being able to recover stored data no matter what. Use effective data frameworks before transferring data. 

2. Ignoring Data Quality Roadmaps

A data quality roadmap is where you collect the input of developers, support staff, the business community, and the entire team. This takes into account the stability, size, and time cost of an application.

It can also make sure that the right members are involved in the correct projects. Straying from this roadmap can cause problems going forward. 

3. No Governing Body Manager

In order to ensure that the governance framework is put in place effectively, you need a governing authority to oversee this. This can be individuals with the proper skills to ensure that proper data administration occurs. 

If a problem occurs, then they can obtain answers from the employees involved in the data project. This step is vital since it makes sure that complete control is over the implementation process. 

4. Ignoring Data Architecture

This means when you don't invest in the proper tools and architecture, no architectural methodology, etc. It can also mean that while you have limited investments with periodic reviews, you don't have a dedicated practice. 

5. No Purpose

A common misconception is that if you start collecting data, it'll take care of itself. Before beginning data practices, it's important to understand what you need or want in a data operation. 

6. the Lack of Visualization

Data can be difficult to understand, and many companies might have the tools necessary to develop insights, but instead leave it hard to understand. Consider placing data into charts and graphs to better understand it, and make use of the data that you have available. 

7. Ignoring Quality

You need to maintain data accuracy in order to drive more success. Your business needs to make decisions based on the data available. 

8. No Data Profiling

For all businesses, data profiling must occur. It's not enough to just have developers look at current models and develop new datasets. Instead, you need in-depth data profiling in order to spend less valuable time on development updates. 

9. Lacking Creativity

If you let data management become a priority and let creativity fall to the side, that can lead to problems for your business. While collecting and running data management processes is important, don't let it sacrifice creativity. 

Have a balance between managing data and creativity. Have data help you make decisions for your business while allowing creativity to happen as well. 

10. Redundant Methods

You might find duplicate files in business and personal data. A single file can have multiple copies within different systems. 

That file can also be stored in many different places within the same system. This redundant data needs to be found and removed. 

When you have a data management system in place, then you can remove any repetitions from occurring, and have them in one location. This leads to more accurate data and better methods in which you can use your resources. 

11. A Lack of Compliance

When you don't have a data management system in place, there can be a lack of unity within your company. A data management system will ensure that there's consistency within your entire organization. 

It'll also help your company remain in compliance with government processes. When you're able to define a structure, you'll be able to answer who is allowed to access data points within your company.

This process will make sure that your company's policies are documented to have only the responsible parties maintaining them. It also ensures that you have high-quality data. 

12. Allowing Data Loss

Avoid losing data since it can cause financial problems for your company. Within a regular file processing system, there are regular data backups. When this occurs, it uses a large number of resources from the storage space. 

A data management system will perform all backups for you. When you have automatic backups, it'll reduce the number of people necessary to keep your data safe. It'll also keep your database's most recent version restored. 

Exploring Common Data Management Mistakes

Now that you've explored these different data management mistakes, you should be set to ensure that you have a strong data management system in place. Are you ready to have the right solutions and tools not only for your data but to protect your company from fraud as well? 

Contact us today. We'll go over the different tools available to help you find the right solutions for your business today.