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Data Analytics Manager

Data analytics managers are the overseers of a team of data analysts, aiming to collate, analyze and disseminate information from large sets of data. They are responsible for ensuring accurate data collection, manipulation and interpretation of the data and its presentation.

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Data analytics managers are the overseers of a team of data analysts, aiming to collate, analyze and disseminate information from large sets of data. They are responsible for ensuring accurate data collection, manipulation and interpretation of the data and its presentation.

Career Path

While a college degree in computer science, data science, statistics or analytics is preferred, it is not always required for this role. Some start as data analysts, specializing in a certain area and gaining higher level expertise before moving into management. Others start with a degree in business management or technology and work their way up. Relevant certifications include:

  • Certified Analytics Professional (CAP)
  • Data Analytics Certification
  • Google Analytics Individual Qualification

Essential Skills

Data analytics managers need excellent mathematics and analytical skills. They must be able to derive meaningful insights from data and communicate these insights to both technical and non-technical audiences. Strong communication, leadership, and problem-solving skills are also essential.

Tools of the Trade

Data analytics managers use a variety of software tools to collect, clean, and analyze data, such as:

  • SQL
  • Python
  • R
  • Tableau
  • Power BI

Growth Opportunities

Data analytics managers can advance to more senior roles, such as chief data officer or chief analytics officer. They can also start their own businesses or consult for other organizations.

Transferable Skills

The skills that data analytics managers develop are transferable to other roles in the tech industry, such as data science, data engineering, and machine learning. They can also be used in other industries, such as finance, healthcare, and retail.

A Typical Day

A typical day for a data analytics manager might include:

  • Meeting with clients to discuss their data needs
  • Developing and executing data analysis plans
  • Interpreting and presenting data analysis results
  • Managing a team of data analysts
  • Staying up-to-date on the latest data analysis techniques

Challenges

Data analytics managers face a number of challenges, such as:

  • The need to constantly learn new data analysis techniques
  • The challenge of communicating complex data analysis results to non-technical audiences
  • The need to work with large and complex data sets
  • The need to keep up with the latest data analysis software and tools

Projects

Data analytics managers may work on a variety of projects, such as:

  • Developing a data analysis plan for a new product launch
  • Analyzing customer data to identify trends and patterns
  • Building a predictive model to forecast future sales
  • Creating a data visualization dashboard to track key performance indicators

Personal Growth Opportunities

Data analytics managers have the opportunity to develop their skills and knowledge in a number of ways, such as:

  • Taking online courses
  • Attending conferences and workshops
  • Reading books and articles
  • Working on personal data analysis projects

Traits and Interests

Data analytics managers are typically:

  • Analytical
  • Problem-solvers
  • Communicators
  • Leaders
  • Curious
  • Lifelong learners

Self-Guided Projects

There are a number of self-guided projects that students can complete to better prepare themselves for a career as a data analytics manager, such as:

  • Building a personal data analysis portfolio
  • Participating in online data analysis competitions
  • Working on open source data analysis projects

Online Courses

Online courses can be a great way to learn about data analytics management. These courses can provide students with the skills and knowledge they need to enter the field or advance their career. Online courses typically cover topics such as data collection, data analysis, data visualization, and data interpretation.

Online courses can help students to better prepare for a career as a data analytics manager by providing them with the opportunity to:

  • Learn from industry experts
  • Gain hands-on experience with data analysis software and tools
  • Network with other data analytics professionals

While online courses alone may not be enough to prepare someone for a career as a data analytics manager, they can be a helpful learning tool that can bolster the chances of success.

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Salaries for Data Analytics Manager

City
Median
New York
$170,000
San Francisco
$187,000
Seattle
$157,000
See all salaries
City
Median
New York
$170,000
San Francisco
$187,000
Seattle
$157,000
Austin
$158,000
Toronto
$200,000
London
£77,000
Paris
€60,500
Berlin
€78,000
Tel Aviv
₪572,000
Singapore
S$135,000
Beijing
¥741,000
Shanghai
¥422,000
Shenzhen
¥198,000
Bengalaru
₹1,028,000
Delhi
₹645,000
Bars indicate relevance. All salaries presented are estimates. Completion of this course does not guarantee or imply job placement or career outcomes.

Path to Data Analytics Manager

Take the first step.
We've curated 24 courses to help you on your path to Data Analytics Manager. Use these to develop your skills, build background knowledge, and put what you learn to practice.
Sorted from most relevant to least relevant:

Reading list

We haven't picked any books for this reading list yet.
By two renowned data science experts provides a comprehensive guide to building data-driven organizations, including strategies for data collection, analysis, and decision-making.
Provides a practical approach to designing and implementing data science solutions, covering the entire process from data acquisition to model deployment, addressing key aspects of data science management.
Covers data mining techniques and their applications in business, emphasizing the use of R and Python for data analysis and visualization.
Provides a comprehensive overview of Tableau Desktop for beginners and those preparing for the Tableau Desktop Certified Associate Exam. It covers all of the topics that are included on the exam and includes practice exercises and sample questions.
Introduces the fundamental concepts and techniques of data science using Python, providing a solid foundation for understanding data science management principles.
Aims to bridge the gap between technical data science and business decision-making, making it suitable for executives seeking to gain a high-level understanding of data science management.
Discusses the ethical and societal implications of data science, providing insights into the responsible use and management of data.
This accessible guide provides a basic overview of data management principles and practices, making it suitable for beginners or those seeking a non-technical introduction to data science management.
While focusing primarily on the ethical implications of data science, this book also discusses data governance and privacy, which are important considerations in data science management.
Provides a comprehensive overview of data analysis and visualization using Tableau. It covers all of the topics that are included on the Tableau Desktop Certified Associate Exam, but it also goes into more depth on some of the more advanced topics.
Provides a practical guide to data visualization using Tableau. It covers all of the topics that are included on the Tableau Desktop Certified Associate Exam, but it focuses on the business user perspective.
Guide to using Tableau Desktop for visual analytics. It covers the basics of the software, and it includes tutorials and exercises.
Provides a basic overview of Tableau for beginners. It covers some of the topics that are included on the Tableau Desktop Certified Associate Exam, but it does not go into as much depth as some of the other books on this list.
Provides a step-by-step guide to data visualization using Tableau. It covers all of the topics that are included on the Tableau Desktop Certified Associate Exam, but it focuses on the practical aspects of using Tableau.
Provides a comprehensive overview of data visualization using Tableau. It covers all of the topics that are included on the Tableau Desktop Certified Associate Exam, but it also goes into more depth on some of the more advanced topics.
Provides a practical guide to data visualization using Tableau for business users. It covers all of the topics that are included on the Tableau Desktop Certified Associate Exam, but it focuses on the business user perspective.
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