Responsibilities Of A Data Manager
Ensure Data Integrity
Data integrity is the security of the data. Data managers should always handle data with care. They should not only guarantee the accuracy of the data but encrypt sensitive information in the dataset for security purposes as well. Incorrect data will harm the work of data analysts/data scientists.
Different Mappings of Data
Always make sure that everything line-up at the end when matching information from different sources.
Punctuality of Deliverables
Data managers take the first step in any data processing, which lays the foundation for the work of data analysts/data scientists. Therefore, all databases must be ready and available when they are requested.
Connecting Technical and Business World
Data managers are the bridge connecting the technical and business side of a product/service.
Typical Day of a Data Manager
- Communication with suppliers
- Chase down inaccurate information
- Identify logic enhancements
- Construct data models
How to Start as a Data Manager
Look for positions in business intelligence and/or analytics, most of which implement data on a daily basis. Make sure to understand how companies are utilizing the influx of data. If the company is capable of building databases, it will need data managers.
- You can apply for an entry-level position and advance your career from there.
- If you have an entrepreneurial mindset, you should consider starting your own company.
- You can do freelance if you are good at Excel. Ask local businesses if you can help with the data.
Tips to Make Your Resume Standout
Have Good Excel Skills
Mastery of Excel will help jumpstart one’s career as a data manager. It will be easier to pick up things.
Point Out Your Logical Thinking
You must have some aptitude for coding, at least understand the logic behind it.
Show Off Statistic Skills
Statistic skills can definitely make you shine during the interview.
Job Search Strategy for Data Manager
Companies that are looking for talents in business intelligence, information systems, and data scientists will definitely need data managers. Data scientists or data analysts won’t necessarily create the databases. In addition, companies that are focusing on AI deal with tons of data; for those companies, data managers are as important as data scientists and data analysts.
5 Common Interview Questions for the Data Manager Position
- Describe a time when you failed to meet a deadline and how did you communicate that up to the chain?
- Excel Quiz
- Describe a time when you had to solve a technical problem.
- Can you prioritize different technical responsibilities within the job? If not, will you be able to communicate with different teams regarding this matter?
- How have you been coaching Data Managers? (for Senior role)
3 Best Resources for Data Management Jobs
Google is the best resource for all types of information
Data Management by Richard Watson
The book dives into the broad world of data management and provides a good overview of what goes into modeling data storage.
Any Programming Book with "Hello World" Section
You will garner technical skills from those books.
3 Must-Have Skills for Data Managers
Without it, you will fail to generate any small pieces of information.
The ability to solve technical problems and provide solutions is crucial.
With statistical knowledge, you can help data analysts and data scientists with ongoing problems.
4 Challenges That You Face In Your Job
- Technical problems
- Security problems
- Working with suppliers
- Constant changes of laws
Career Path Options for Data Managers
- Data producer
- Database administrator
- Project manager/Product manager
- Business analyst
- Security position
3 Things To Consider When Selecting An Employer
- Always invest in the tools
- Company culture is crucial
- Type of data you will be working with
Advice For Aspiring Data Manager To Succeed
Look into the data before you prepare it for Data scientists/analysts.
Don’t stop learning
As data science is continuously progressing, so are the tools used to handle it. Stay focused, and learn new tools to stay successful.
Troubleshoot with hypothesis
Whenever you encounter a problem, always revisit the hypothesis and secure constant variables.