How to become A Data Analyst

• Junior Data Scientist

What do Data Analysts do?

A Data Analyst would typically need to:

• Retrieve, gather, clean and interpret an organisation’s data sets to answer a question, solve a problem or reach meaningful conclusions
• Collect, understand and document detailed business requirements, using appropriate tools and techniques
• Work with technology teams, management and data scientists to set goals; mine data from primary and secondary sources
• Design and carry out surveys; analyse survey data; liaise with internal and external clients to understand data content thoroughly
• Clean and dissect data to remove unnecessary information; identify areas to increase the efficiency and automation of processes
• Identify, evaluate and implement external services and tools to support data validation and cleansing
• Analyse and interpret results using statistical tools and techniques; produce and track key performance indicators; pinpoint trends and patterns in data sets
• Monitor and audit data quality; track, analyse and interpret complex data sets relating to the employer’s business
• Analyse market research, opinion polls and trends in consumer feedback to help the organisation make sound business decisions
• Prepare reports for internal and external audiences, using business analytics reporting tools
• Create data dashboards, graphs and visualisations; provide sector and competitor benchmarking
• Mine and analyse large data sets, identify new opportunities for process improvement and present them successfully to management
• Establish records management processes and policies; set up and maintain automated data processes; develop and support reporting processes
• Fix code problems and data-related issues

Data Analysts usually work at a computer as part of a team. They can work from home or a remote office based on the type of data they process. They may need to travel to other locations to collect data. 

Working hours are typically 9-5, Monday to Friday, with occasional overtime and weekend work to complete important projects or meet looming deadlines.

Data analysis is a highly transferable skill required in almost every private and public sector industry. Data Analysts can boost their job search by asking their network for referrals, contacting companies directly, using job search platforms, going to job fairs, leveraging social media and inquiring at staffing agencies.

Data Analysts are generally employed by:

• ‘Big Four’ Consultancies
• Financial Services Firms
• Consumer Retail Firms
• Small & Medium-Sized Marketing Agencies
• Higher Education Institutions
• Insurance Companies
• Pharmaceutical Companies
• Telecommunications Companies
• Information Technology Firms
• Government Agencies
• Media Companies

Professional associations and organisations, such as The Institute Of Analytics, are crucial for Data Analysts interested in pursuing professional development or connecting with like-minded professionals in their industry or occupation. Membership in one or more adds value to your resume while bolstering your credentials and qualifications.

• Data collected can be overwhelming and makes it tough to mine meaningful and real-time data
• Pulling data from multiple sources and manually presenting them in visual graphs or charts is time-consuming
• Manually combining data from multiple, disjointed sources may lead to incomplete or inaccurate analysis
• Inaccessible and poor quality data
• Pressure from the management for reports on all kinds of data without proper organisational support
• Budgetary constraints and shortage of skills affect scaling data analysis

A period of supervised experience in the form of an internship or placement during your degree is an essential prerequisite for most Data Analyst positions. 

It would serve you well to check whether you can gain relevant skills and qualifications through related apprenticeships such as Digital Applications Specialist or the Technical Apprenticeship in Data Analytics. They may allow accelerated entry to the second or third year of some bachelor’s programmes or enhance your application to particular master’s programmes when combined with adequate related experience. 

Previous work experience as an administrative assistant or customer service representative will also help. Consulting firms, government agencies, media and telecommunications companies offer graduate schemes that facilitate access to entry-level roles.

Read about the profession and interview/job shadow experts working in data analytics to prove your commitment to course providers and prospective employers. 

Most Data Analysts have a bachelor’s degree in business information systems, computer science, economics, information management, mathematics and statistics.

Although it is not usually required, a sizeable number is increasingly opting for a master’s degree in data science, business analytics, data science, and big data. Some universities offer an integrated five-year-long Masters program, combining a degree and masters course. A few employers may ask for a doctorate in a relevant subject.

Candidates with a high school diploma, GED (General Education Development) or an associate degree also have a fair chance of getting the job, provided they demonstrate the relevant skills.

Focus on mathematics, economics, statistics and computer science in high school to facilitate entry to accredited colleges. It is possible to gain advanced access to the second year with a relevant HNC (Higher National Certificate) or HND (Higher National Diploma).

Certification demonstrates a Data Analyst’s competence in a skill set, typically through work experience, training and passing an examination. Certification from an objective and reputed organisation can help you stand out in a competitive job market and allow you to become an independent consultant. Successful certification programs protect public welfare by incorporating a Code of Ethics.

Microsoft Certified: Data Analyst Associate Certification is one of the most valued certifications you can acquire. It will make you proficient in data preparation/modelling/visualisation/analysis in leveraging the potential of Power BI (business intelligence) to optimise the value of the company’s data assets. Prerequisites include prior experience working with Power BI.

Complete novices may opt for Google Data Analytics Certification to develop skills essential for entry-level positions as Certified Data Analysts, using tools such as SQL(Structured Query Language), Tableau and R.

Performance, experience, and the acquisition of professional qualifications drive career progression. 

Data Analysts with consistently high-performance levels may be eligible for eventual promotion as Project Manager before being elevated to the position of Contract Project Manager much later.

Skilled analysts can also find lucrative opportunities in academic research or government advisory bodies. You could switch to freelancing as a Consultant and be paid handsome fees per project.

It is also possible to specialise in a particular technical language as a Specific Domain Campaign Expert. Specialising opportunities also exist in data mining, data infrastructure, data visualisation and data analysis.

Candidates with a bachelor’s degree in data-related fields, certification, and relevant work experience have the best job prospects.

Continuing professional development (CPD) will help an active Data Analyst build personal skills and proficiency through work-based learning, a professional activity, formal education, or self-directed learning. It allows you to upskill continually, regardless of your age, job, or level of knowledge.

Advanced level certification as a Certified Analytics Professional (CAP) will make you familiar with business and analytical problems, various analytical methodologies and lifecycle management skills.

Data Analysts with at least two years of professional experience and a knack for problem-solving and critical thinking can opt for online certification in data analytics. It may offer project-based assignments and real-life case studies to test the student.

You could also seek professional certification in project management or consider a postgraduate degree in data science to enhance your analysing skills or change careers. 

Data Analysts interested in academic research can expect support and additional training from the educational institution or from Vitae, a non-profit global leader with over 50 years of experience in enhancing the skills of researchers. 

In partnership with governments, funders of research, professional bodies, trusts & foundations, universities, and research institutes, Vitae offers training, resources, events, consultancy, and membership.

Range of Responsibilities

Data Analysts perform various duties, depending on the industry they work in. You may predict demand for services or goods in the manufacturing and education sectors, check quality control standards in fields such as drug and food testing and collate data on population trends, the economy, the labour market, transport and crime if working for government agencies, research councils and universities.

Current Scenario

Data analysis is a fast-growing field. The demand for experienced Data Analysts will only grow worldwide across multiple industries and domain types, including healthcare, pharmaceuticals, manufacturing, education, marketing, sales, media, finance, consulting, retail and even real estate.

Tools of the Trade

Analysts use computer systems and calculation apps to make sense of the given data. They begin with understanding facts and numbers before presenting their conclusions effectively, using graphs, charts, tables and graphics.

Get Skilled Up!

Data Analysts need excellent research, problem-solving, mathematical, analytical, collaborative and reporting skills. Knowledge of various programming languages, data analysis tools, data enrichment techniques, open-source data analytics, data protection issues, industry-specific databases and data sets and the ability to prioritise tasks will make you a force to contend with.

Potential Pros & Cons of Freelancing vs Full-Time Employment

Freelancing Data Analysts have more flexible work schedules and locations. They have full ownership of the business and can select their projects and clients. However, they experience inconsistent work and cash flow, which means more responsibility, effort and risk.

On the other hand, a full-time Data Analyst has company-sponsored health benefits, insurance, and retirement plans. They have job security with a fixed, reliable source of income and guidance from their bosses. Yet, they may experience boredom due to a lack of flexibility, ownership, and variety.

When deciding between freelancing or being a full-time employee, consider the pros and cons to see what works best for you.

A 10 per cent increase in data accessibility will result in more than USD65 million additional net income for the typical Fortune 100 company.

Whether it is the pricing of new merchandise, reducing transportation costs or dealing with issues that cost the company money, Data Analysts play a crucial role in translating numbers and data into language that can help the company understand how to make excellent business decisions.

Your ability to take, understand, process, extract value from, visualise and communicate data will become increasingly important as you move up the career ladder.