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Data Manager Duties and Responsibilities

To ensure that their company's data is stored, managed and analyzed correctly, Data Managers perform a variety of tasks. We analyzed several online job postings to identify these core duties and responsibilities.

Create Policies From the point that they begin working at their company, Data Managers will need to be continually developing data management policies. To do so effectively, they'll need to be familiar with the capabilities of their company's data system.

Revise Policies Data Managers must review each of their company's pre-existing data management policies to make sure that they are up to date and effective. If they aren't, the Data Manager will revise the policies as necessary.

Establish Protocols In any company, data must be shared with members of upper-level staff. Because of this, it's the responsibility of Data Managers to establish rules and procedures to that information can be shared with executives securely and responsibly.

Assist Colleagues Whether their colleagues are performing everyday data-related tasks or retrieving special reports or data sets, it's up to Data Managers to help them do so effectively without risking any data loss.

Secure Data In accordance with current best practices, Data Managers must ensure that their company's data systems are secured and protected from potential breaches or malicious attackers.

Troubleshoot Data Managers need to collaborate with fellow staff members to discuss any data problems that may arise and develop potential solutions.


Data Manager Skills

Successful Data Managers are detail-oriented individuals with a knack for analytical thinking. They're good at communicating with others, but where they truly excel is in the world of numbers, records and raw data. In addition to these general attributes and personality traits, employers are looking for Data Managers with the following skills and qualifications.
  • Data management skills - Above all else, Data Managers must have a thorough and proven understanding of the principles of data management and administration.
  • IT and database skills - Because they'll be working with IT systems and high-tech databases on a daily basis, it's crucial that they be familiar with modern databases and IT systems and how they work.
  • Analytical skills - Due to the importance of data analysis in their everyday duties, Data Managers need to be proficient at digesting and analyzing large amounts of data.
  • Problem-solving skills - No matter how state-of-the-art their database is, problems are bound to arise. Thus, it's essential that Data Managers be able to tackle problems under pressure.
  • Communication skills - Although human communication is an often overlooked component of data management, it is nonetheless essential. So, it's important that Data Managers have excellent verbal and written communication skills.

Data Manager Salary

According to the Bureau of Labor Statistics, Database Administrators, which includes Data Managers, make a median annual salary of $84,950 per year, with the lowest paid earning $47,300 or less per year and the highest paid earning $129,930 or more per year. Data Managers in New Jersey, the District of Columbia and Colorado enjoy the highest median annual wage in the United States, earning $106,330, $102,890 and $96,440 per year, respectively.

Additional Data Manager Resources

We compiled the following list of resources to help you continue exploring your career as a Data Manager.

TDWI: Analytics and Data Management Discussion Group - With more than 65,000 members, this LinkedIn group is an ideal place to discuss data and data management principles with fellow Data Managers.

Big Data and Analytics - With a member base of over 300,000 people, this LinkedIn group is full of Data Managers and other data professionals eager to share their wisdom.

Analytics Vidhya Blog - This frequently updated blog is focused on big data, data analytics, data science and everything in between.

Data Science for Business - This bestselling book covers the fundamentals of data science, data-mining techniques and much more.

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