How To Become a Data Manager Plus Traits and Best Practices
Updated 27 April 2023
Data management refers to the development and governing of systems that handle, process and store data. These roles could be in a research facility, large organisation or similar entity. Whether data management is your first career choice or you desire a change in your career after years spent in another sector, there is much to know about being a data manager. In this article, we explain how to become a data manager and the best practices and traits for the role.
Related: How To Become a Data Analyst
How to become a data manager
If want to know how to become a data manager, here is a guide to the recommended career paths, education, formal training and other steps to take:
1. Graduate with a BA or equivalent qualification
A bachelor's degree is the standard minimum qualification required by most companies advertising for the position of a data manager. Some roles may even require a higher qualification, such as a master's degree, in a relevant field. In addition to degrees in IT and computing, there are also some dedicated data management degree options available. Check job advertisements to see what is most often requested, and this can help you choose the best degree type.
2. Gain an entry-level job as a data assistant or similar position
Unless you have ample experience in a managerial position or developing databases previously, you're probably going to start off in an entry-level job that can eventually progress into promotion as a data manager. This could be a job as a data assistant or any similar role that can lead to a promotion as a data manager. Once again, you can check data manager job advertisements to see what experience recruiters are looking for. This can inform your initial job search.
3. Grow your knowledge in the position and advance to data manager
As you continue to hone your data management skills as a data assistant or in a similar position, a promotion or a new role as a data manager may open up to you. As is the case with many careers, data management is a role you grow into. It's important to note that data management is important across a broad range of industries, including the medical, financial and education sectors. Because of this, there is no one set career roadmap into data management. Do you research beforehand and determine the best path for you.
What is the role of a data manager?
Though the role of a data manager may vary slightly depending on the industry and individual needs of a business, the fundamental responsibilities remain the same. The core roles of a data manager are:
The daily management of databases and the accounts of any clients and employees
The routine maintenance of these databases to ensure optimal function
The correction of any faults or inconsistencies in the database
The inputting of new data and subsequent organisation of it
Communication with colleagues and superiors regarding any changes to the database
Since the introduction of the UK General Data Protection Regulation (UK GDPR) and Data Protection Act 2018, it's essential that data managers manage their responsibilities in compliance with the latest regulations.
What are the challenges faced by a data manager?
As is the case with any career, data managers must handle a number of challenges. How effectively you deal with these challenges as a data manager relates to your individual experience and character. If you want to know more about whether you'll be able to effectively handle these challenges, you can read more about the best data manager traits below:
Effective management in stressful situations
Even the most experienced data managers may find themselves stressed with the sheer amount of data to manage. After all, you have several priorities to manage at once, including data input, data revision, data correction and finding data required by your team as and when needed. Learning how to effectively manage data is something that comes with time and experience.
Communication with other departments
As a data manager, you can typically expect to work in isolation from other departments. This is because your operations tend to be in the background, as opposed to at the forefront of the business. However, this isolation presents itself as one of the biggest challenges facing data managers. This is because other departments rely heavily on the data you input and maintain. Due to this, strive to work collaboratively with them by notifying them of any changes they need to know.
Though it may feel easier to simply presume everything is running smoothly with your databases until otherwise indicated, this often leads to problems arising unexpectedly and severely. Instead of taking a reactive approach to any database issues, try being proactive by seeking out potential areas of danger or improvement. By performing routine maintenance on your databases to ensure they are functioning effectively and containing the right information, you can carry out your daily tasks with heightened confidence.
What are the traits of the ideal data manager candidate?
There are many traits that make for the ideal data manager candidate. If you are considering a career in data management, ensure you possess a mix of these traits before applying to data management jobs. Similarly, if you are unsure of what career path is right for you but you hold many of the listed traits below, you might becoming a data manager. Desirable traits in a data manager include:
knowledge of modern technology, including both software and hardware
effective communicative skills, especially within a team
an eye for detail, most importantly when proofing and inputting data
analytical and problem-solving abilities
strategic oversight, such as seeing the long-term picture and identifying emerging trends
What are the best practices for data management?
Upon entering your new role as a data manager, there are some practices to integrate into your duties in order to ensure you perform your role to the best of your ability. Of course, these are just some of the best practices and the list is not exhaustive. There are many more you can tailor to your unique role to ensure you work efficiently and diligently to meet your company's needs. These best practices of a data manager typically include:
Use relevant data templates for a streamlined process
One of the most recommended practices you can implement as a data manager is the creation and use of templates that make data input more efficient. Dedicate some time to creating flexible templates that can be adapted to suit your unique data needs, as doing so saves you time later on. These templates also have the benefit of being transferable across other roles, positions, teams and organisations.
Document data usage frequently and thoroughly
Though inputting data can be an intricate process, a significant responsibility of the role of being a data manager is finding data as and when your colleagues need it, especially if your databases are complex and consist of many sets of data, as finding the precise numbers or results you need can be quite time-consuming. This is why it's important to regularly document what data you have inputted and where each set of data is.
Regularly inspect the data to identity inconsistencies or mistakes
As a data manager, your responsibility is to strive to be a proactive team player. Due to this, make sure to regularly and thoroughly inspect your data. In doing so, you can spot any inconsistencies and correct them before a colleague needs it. This prevents a potential issue from even arising before it has the opportunity to cause problems.
Create and maintain guidelines to ensure safe and compliant data usage
Whether for personal use or for implementation throughout the office, creating a set of guidelines and data usage rules is highly recommended, provided your employers agree to this. Not only does this ensure that you are complying with the latest data regulations in the UK, such as the GPDR, but it also ensures colleagues can handle data correctly and confidently. This minimises the risk of data going missing or ending up in the wrong place.
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