How to become a Data Analytics Manager

Data Analytics is the frontline of business management. Data is the language of growth: from understanding and adapting to business trends, to formulating more relevant HR strategies to draw the right people to a company. Data is the foundation of streamlining processes, improving products, understanding market forces, and running a better company.

Strategies for dealing with data are where Data Analytics Managers step in. DAMs are the leaders in this fast-moving field, providing guidance for data analytics teams to better draw data from specific fields, to aid business management, and to help make better business decisions.

Having the data is one thing but making good use of the data is another. This is the essence of Data Analytics Management – effective use of data in change management; improving systems and creating growth are the hallmarks of a good Data Analytics Manager. This means having an in-depth knowledge of company goals and business targets, and the efficient use of data to meet them. This means understanding what short term and long-term goals data can help meet, and how the effective interpretation of data can impact business decision making.

Step 1 – Get the right base experience

Data Analytics Managers can come from a variety of professional backgrounds, but at senior level being cognizant of data science, computer science, and niche business practice is essential.

Our advice is seeking an education foundation that compliments the day-to-day role of a Data Analyst, and in the move to management seek higher levels of qualification such as a master’s degree in business administration, management, data, or software development. Experience in emerging fields such as blockchain analysis are also skills that are highly sought after, and as we discuss below boot camps can provide a flexible system of skills upgrading to help further study in the field.

Step 2 – Certifications

To work as a Data Analytics Manager, you need some certifications in Data Analysis and, ideally, business management. This will mean competencies in everything from Structured Query Language (SQL) to Python, and Regression analysis to Data optimisation. This can be done through further education, or in-work experience, and as such there are myriad ways of becoming a senior Data Analyst.

A certification from CompTIA Data+ certification is a great starting point. Although there are no prerequisites for starting the course, a solid understanding of the above programming languages and some experience in the field are suggested.

Other analytics courses from Google, CareerFoundry, Springboard and many more provide boot camps and structured learning programmes to help your data analytics knowledge, from which you’ll gain certifications.

Further certifications, such as master’s programmes in Business Management and Computer Science are highlighted as good subjects for Data Analytics Managers.

Step 3 – Watch out for Emerging Trends

Data is incredibly trend-led. This means Data Analysis Managers need to be ahead of the data curve in every respect.

Having a handle on AI, Data Security, Visualisation, and Data Quality must be matched with an interest and viewpoint on predictive analysis, real-time data, automation…on and on the list goes. Emerging trends in Data Analysis will be another benchmark of your managerial credentials.

Learn more about Data Analytics Manager careers.

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Job Description & Profile, Qualifications, Skills & Requirements, CV building tips, Salary & Pay etc.

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