Brands and businesses worldwide are increasingly analyzing the massive amount of data generated every second from social media, online purchases, smartwatches, and online browsing. Data analytics professionals have become the need of the hour, helping companies leverage data to drive business goals.

Data analytics manager is among the top roles in this field. They fulfill technical, leadership, and project management responsibilities and often serve as a glue that brings together a data science team and leads them to achieve the desired outcomes.

If you want to become one, this guide is for you. Keep reading as we dive deeper into the roles and responsibilities of a data analytics manager, the career paths, the skill requirements, and the demands of the position. We will also cover how a good data analytics bootcamp will give you a head-start on becoming a successful manager of a data-driven department.

Who is a Data Analytics Manager?

These managers lead a team of data science professionals consisting of data engineers, data analysts, data scientists, statisticians, database administrators, business analysts, and data architects.

They are responsible for liaising with each team member and keeping them on track to achieve a collective goal. However, they may take on multiple roles in smaller firms where a large team may not be needed or be affordable.

What Does a Data Analytics Manager Do?

They wear several hats. Their roles may vary from reviewing reports and analyzing data to assisting in data collection and analytics software installation.

Here’s a quick list of the primary responsibilities:

• Collate data from various sources
• Segment and analyze data sets
• Utilize data analysis techniques to gain valuable insights from data, such as increased web traffic
• Prepare and review reports on the analysis
• Review reports from other team members
• Research and assess new data collection techniques and analysis methodologies
• Collaborate with other departments to share analytics reports and receive data
• Recommend and install data collection software for client websites
• Train new members of the data analytics team
• Audit data collection methods for authenticity, ethics, and integrity

Here’s what a typical day in the life of a data analytics manager looks like:

• Check email communication and review reports from the other team members
• Meet with stakeholders to discuss the critical points of the reports and get feedback regarding the additional and new requirements
• Collaborate with other departments to facilitate effective data collection for the team members
• Meet with team members to discuss work progress, reports, and current and future goals
• Incorporate feedback regarding any issues within the team, the tools, or inter-departmental communication in the process to improve collaboration
• Conduct training for new members team members
• Work on self-allotted data analysis projects and initiatives
• Explore tools and methodologies that may help the team members and improve the data analytics Initiative for the organization as a whole

Data analysis, and hence a data analytics manager, is not restricted to a computer science or analytics company. Almost every industry has a department dedicated to data analytics.

For example, if you are from an instrumentation engineering background, a company in sensor and equipment manufacturing will be a potential employer. Meanwhile, suppose you are a graduate in biology. In that case, you can work as an analytics manager in a biosciences firm working on developing analysis techniques for big data generated in the biology research laboratories of the firm.

Types of Data Analytics Manager Careers

Data analytics is a diverse field where you usually begin as an entry-level data analyst. After that, you can then take various paths as follows.

• Data scientist: In this role, you will combine skills related to mathematics, statistics, coding, machine learning, and predictive modeling to analyze big data for the development and testing of hypotheses. You will go beyond that of a data analyst by drawing inferences from the data and being involved in continual research to devise newer analysis techniques and models based on scientific principles.
• Data engineer: This role requires you to design algorithms to manage and organize data. You will be focused more on developing data infrastructure rather than interpretation.
• Data architect: Here, you will envision, conceptualize, and design the blueprint for the enterprise data management framework. You will construct the structure for data collection, analysis, and interpretation, which will then be developed by the data engineer for the data scientist who will use it for analysis.
• Senior-level analyst: In this role, you will diversify as a management, business intelligence, or operations research analyst.
• Management: As a management analyst, you will harness the skills of data analysis and interpretation to collect the right kind of data, such as process efficiency, employee performance, sales activities, etc., to enhance the management of the various branches of a business.
• Business intelligence: As a business intelligence analyst, you will collate data from teams such as marketing, sales, after-sales, customer service, competitor performance, etc., and analyze them for trends and insights to add value and communicate possible opportunities to the company leaders.
• Operations research analyst: Here, you will be responsible for data analysis of various operations branches, including the workflow from design to production and the individual processes in production, warehousing, and sales. You will scrutinize the operations for trends and flaws and provide feedback and recommendations for improvement based on big data.

Despite such diversity in the roles, a common pathway will progress in the following order: entry-level data analyst → senior-level analyst → data analytics manager → director of analytics → chief data officer

Becoming a Data Analytics Manager: Prerequisites

This role requires you to be proficient in technical and managerial skills. Here are some prerequisites for becoming one.

Education requirements

You will need to hold a minimum of an undergraduate degree in quantitative branches such as computer science, data science, computer engineering, Statistics, Accounting, Finance, Information Management, mathematics, economics, and predictive modeling. If you hold a Master’s degree in any such branch, the years of experience the recruiter will ask for will reduce.

However, data science is an eclectic field. Hence, if you have an undergraduate degree in any other field, such as mechanical, electrical, or metallurgical engineering or biosciences, you can still enter this field by gaining data science knowledge in a non-traditional path.

Skill requirements

As a future data analytics manager, you must be:

• Proficient in programming languages and data visualization tools such as Python, R, Matlab, Tableau, SAS, QlikView, D3, SQL 2016, Big Query, Excel, and Java.
• Familiar with machine-learning
• Well-versed in database systems of SQL and NoSQL.
• Knowledgeable in Market Mix Modeling, Attribution Modelling, visitor behavior analysis, and customer sentiment analysis if you aim for the marketing vertical.
• Expert in testing, both A/B and MVT, using tools such as Maxymiser, Adobe Target, Google Web Optimizer, and Qubit Deliver.
• Proficient in Google Analytics and GTM audits and able to implement recommended changes.
• Project management and teamwork

While you may already possess some of these, enrolling in a well-structured and industry-recognized online data analytics training will help you build more employable skills in this field and arm you with practical experience.

Work experience

For a beginner, you should have a portfolio of your projects and work demonstrating your skills. An internship is an excellent addition to this portfolio, especially in today’s remote work trend, where you can find numerous work-from-home internships for data analytics.

However, for the data analyst managerial position, you will require about five years of experience in a data science/analytics role and a couple of years of experience in a managerial role. You must present projects you have completed as the main analyst and a team lead. A proven track record of cross-functional collaboration may also be required.

Steps to Become a Data Analytics Manager

Now that you know what being a manager who can leverage data analytics entails, here’s the step-by-step roadmap to become one.

• Step 1: Complete your undergraduate degree. Degrees in computer science, statistics, business management, and information technology can give you the foundation to build the required skills later.
• Step 2: Develop the essential skills. Research the skills needed and focus on learning additional skills that may not be included in the normal coursework.
• Step 3: Build a strong portfolio showcasing data analytics skills. Work on as many aspects as possible that testify to your skills and furnish your diversity of experience.
• Step 4: Obtain professional certifications. Enrolling in a data analytics program is a great way to solidify your knowledge and gain project-based experience. Still, it will also reward you with certifications on completion. This will add value to your portfolio and significantly enhance your resume.
• Step 5: Network with professionals in the field. Staying connected with peers and professionals is vital for keeping up with the latest trends and updates and can positively affect your career growth. Social media platforms, such as LinkedIn and data science forums like Kaggle, Reddit’s r/datascience, and GitHub’s data analytics forum, are excellent spaces for data analytics aspirants and professionals to be in.
• Step 6: Start working as a data analyst and gain 1-5 years of experience. A manager oversees different roles, and you must first learn what those individual roles entail. Hence, gaining experience in roles such as data analyst and senior analyst is crucial to understanding the nitty-gritty of this field.
• Step 7: Go for a postgraduate or advanced degree. Knowledge is never enough, so you can pursue a postgraduate degree in data analytics or business administration to understand higher-level concepts such as project management, team collaboration, etc.
• Step 8: It is never too early to apply for the position. Typical job descriptions require five years of experience. Still, if you have additional qualifications and fit the criteria, you can always apply to become one.

Why Choose a Career in Data Analytics Management?

Firstly, there is demand for data analytics management in almost all industries, from FMCG and biosciences to marketing, finance, and manufacturing. As more and more companies continue to integrate data analytics into their business, this profession faces a massive growth potential. Even government statistics predict the jobs in this market will grow by 35 percent.

Secondly, it can be a highly fulfilling career. A data analytics manager in the US earns an average annual salary of $136,730. However, it’s not just about monetary compensation. The exciting opportunities and the ability to drive innovation add to the rewarding nature of this job.

Get Started with the Right Course and Certifications

Are you ready to take the next steps to become a data analytics manager? Join our expert-led data analytics bootcamp designed to teach you the skills and fundamentals necessary to carve a successful career in data analytics. Besides learning, get hands-on training with the opportunity to work on capstone projects and network with industry experts and like-minded peers for a holistic career development experience.

According to the latest reports, the data analytics market will likely grow from US$ 307.52 billion in 2023 to US$ 745.15 billion in 2030. With heightened demands and booming growth, this is a lucrative market to build a career in.