Future Career as a Data Analyst: Skills, Programmes and Courses

If you are passionate about managing data and drawing insights from big data sets to help organisations make strategic decisions, a career as a data analyst is the best option. To stand out in this industry, you must have the technical and soft skills employers seek and complete programmes or courses to become experts in this field.

This guide explores how to become a data analyst, the expertise you need, and the career pathways you can take to progress. 

Table of Contents

• The Growing Demand for Data Analysts
• Top Programmes for Aspiring Data Analysts
• Top Courses for Data Analysts
• Core Technical Skills for Data Analysts 
• Essential Soft Skills for Data Analysts
• Career Pathways for Future Data Analysts
• Emerging Trends Shaping the Future of Data Analysis 
• Final Thoughts and Next Steps for Aspiring Data Analysts

As organisations process higher volumes of data, data analysts have become critical across various industries. A few reports highlight that data analyst jobs will grow by 25% between 2020 and 2030. This job growth rate is much higher than average, making data analysis a fantastic option. 

Here’s what you can expect to do working as a data analyst:

• Gather data from various sources.
• Cleaning and preparing data, ensuring data accuracy, consistency and quality.
• Verifying the integrity and quality of data.
• Use statistical methods to analyse data and trends.
• Draw meaningful insights from analysis.

Although data analysts have significant job growth potential, this field can be highly competitive. To stand out in the job market, you should develop your skillset and gain as much practical experience as possible. 

Here are a few programmes that cover all the soft and technical skills you need to excel as a data analyst.

The London Interdisciplinary School – BASc Degree

The BASc degree from The London Interdisciplinary School (LIS) offers an interdisciplinary approach to learning the skills you need to excel in data analysis and beyond. This degree helps you think critically and understand how to solve complex problems using diverse knowledge, disciplines, and skills. You’ll engage in multiple subjects simultaneously and gain different perspectives to apply to real-world problems. 

Curriculum:

• Quantitative Methods 1a: Thinking Like a Scientist – Learn basic technical literacy skills and use Python and Excel to visualise data. 
• Qualitative Methods 1a: Language and Communication – Understand the emotional impact of interactions with people through close reading, thematic analysis, and participant observation. 
• Quantitative Methods 1b: Thinking Through Data – Gain skills in data science, machine learning and statistics. 
• Natural Language Processing (NLP) – Develop knowledge of NLP using Python, linguistics, and data analytics. 
• Capstone Project – Choose a problem you are passionate about it and showcase your quantitative and qualitative skills through an independent research project. 

Programme Length:

• Three years

Tuition Fees:

• £9,275 / a year

IT Online Learning – Data Analyst Career Programme

IT Online Learning offers a one-year Data Analyst Career Programme. This programme is online, and students can complete it independently. Students will work through over 50 real-world assignments, nine portfolio projects, and interactive walkthroughs to learn the fundamentals of data analysis. This learning platform also provides recruitment support and an AI tutor bot to enhance your learning experience and make it easier to break into data analysis. 

Curriculum:

• Data Analysis
• Critical Thinking
• Python Essentials
• Tableau
• Microsoft Power BI
• Database Essentials

Programme Length:

• 12 months 

Tuition Fees:

• Available on request 

The University of Strathclyde – BSc Hons Data Analytics

If you’re looking for a more traditional way to learn data analytics, the BSc Hons Data Analytics programme at the University of Strathclyde might be suitable. Students will explore standard data analytics concepts, from computer science to mathematics and real-world projects, to test their practical skills. In the third year of your studies, you’ll also have the opportunity to study abroad. 

Curriculum:

• Machines, Languages & Computation
• Mathematical Foundations
• User & Data Modelling
• Building Software Systems
• Stochastics & Financial Econometrics

Programme Length:

• Four years 

Tuition Fees:

• £9,535/ year for home students.
• £21,550/ year for international students.

These are a few courses that will help you learn what it takes to become a data analyst. 

Distance Learning Centre – CIW Data Analyst Course

The CIW Data Analyst course by the Distance Learning Centre is a 120-hour short course covering the basics of data analysis. This self-paced course offers students the opportunity to gain a fundamental understanding of data analysis before committing to a degree programme. There are practice tests and live labs to help you practice what you learn. 

Curriculum:

• Fundamentals of Data Science 
• Introduction to Big Data
• Working with Data Sources 
• Tools for Capturing and Analysing Data
• Analysing and Reporting Data 

Programme Length:

• 120 hours 

Tuition Fees:

• £400

Coursera - Google Data Analytics Professional Certificate

Coursera offers a free Data Analytics Professional Certificate. You will study online at your own pace and gain a basic understanding of data analytics. This course is ideal if you want to learn at your own pace. You will complete a capstone project to showcase your practical skills. Once you complete this course, you can access resume review, interview prep, and career support. 

Curriculum:

• Foundations: Data, Data, Everywhere
• Prepare Data for Exploration
• Process Data from Dirty to Clean
• Share Data Through the Art of Visualisation
• Data Analysis with R Programming

Programme Length:

• 6 months 

Tuition Fees:

• Free

London School of Economics and Political Science – Data Analysis for Management

The London School of Economics and Political Science (LSE) offers a course in Data Analysis for Management. This online course will help you gain data analysis skills to develop data-driven models, evaluate risk and extract strategic business insights. You’ll also work on a capstone project to reflect your practical skills. 

Curriculum:

• Data visualisation and descriptive statistics
• Quantifying risk through probability
• Evidence-based decisions
• Data integrity and statistical inference
• Time series forecasting

Programme Length:

• 2 months 

Tuition Fees:

• Available on request

Here are a few top technical skills every data analyst must have to fulfil their day-to-day tasks. 

Data Visualisation

Data analysts use visual elements, such as charts, scatter plots and graphs, to reflect their insights from data analysis. This technique makes it easier to identify data patterns, trends and anomalies and share this information with stakeholders for accurate decision-making. If data analysts were to present data without making it easy to understand, stakeholders would struggle to find value in these insights. 

To become a data analyst, you must know how to use data visualisation tools, choose the best chart type for stakeholders to interpret data, and make your visualisations appealing. Data analysts use many tools to visualise their findings, including Tableau, Power BI, and Google Charts. 

Statistical Analysis

Statistical analysis enables data analysts to examine and interpret data, making it easier to identify trends and relationships within datasets. Data professionals use statistical analysis methods like regression analysis, hypothesis testing, descriptive statistics, and exploratory data analysis to extract valuable insights from data.

Statistical analysis can be complex, especially as this technique is relevant to large data sets. As a result, professionals must know how to use data analysis and visualisation tools to automate statistical analysis processes. 

Programming Languages

Coding languages are imperative for data analysis because they allow professionals to manipulate, analyse and extract insights from high volumes of data. Analysts use programming languages to collect, clean, and organise data, build predictive models, and uncover data patterns. The most common coding language for data analysts is Python. However, analysts need many other coding languages, such as R and SQL. 

In addition to technical expertise, data analysts also need soft skills to optimise their working experience and stand out to potential employers. These are a few soft skills to have. 

Critical Thinking

To succeed in a data analytics career, you must know how to think logically and critically. You’ll probably handle unexpected problems and must know how to apply innovative methods to solve them. Critical thinking for data analysts means being curious and understanding the reason behind trends and patterns. Professionals must know how to analyse data, question assumptions objectively, and draw informed conclusions by considering all aspects of data sets. 

Collaboration

Data analysts must collaborate with other professionals, such as data scientists, engineers, and other analysts. Understanding how to communicate and work together to achieve better business outcomes is essential. Analysts should also comprehensively understand cross-functional teams and what it takes to share insights and work alongside other departments to achieve stakeholder objectives. 

Adaptability 

Data analysts must readily learn new tools and processes to make data-driven decisions. They must also keep up with this constantly evolving industry, develop a flexible approach to handling various data analysis problems, and navigate changing business needs and technologies. To become agile, professionals should experiment with different tools, network and share knowledge with peers and test their skills through real-world projects. 

Starting as a data analyst, you can work toward becoming a senior data analyst. However, there are many other career pathways to consider. 

Business Intelligence Analyst

Business intelligence (BI) analysis is a typical starting point for aspiring data analysts. Professionals in BI analysis use data analysis tools and techniques, like data mining, to help businesses make strategic decisions. They work with data from companies and their competitors to help these businesses optimise their overall performance. 

The average salary for BI analysts is £42,066 per annum. Here’s what BI analysts can expect to do daily:

• Gather, clean and organise data from various sources, such as revenue, sales and customer engagement.
• Perform data analysis to understand how to help businesses improve efficiency, service delivery and product quality.
• Brainstorm new ways to collect and classify data.
• Generate reports to help internal and external stakeholders make strategic decisions. 

Data Engineer

Data engineers design and build systems to collect, store, and analyse data. They also develop data pipelines that transfer data through companies so stakeholders can use these insights for decision-making. Data engineers are crucial in data analysis and must implement strategies to maintain a sound data infrastructure. The average annual salary for data engineers is £55,837. 

These are the typical responsibilities of a data engineer:

• Design, develop and test data pipelines.
• Ensure data security to prevent and mitigate data breaches.
• Build storage solutions that can manage high volumes of data.
• Work with data scientists to improve the accuracy and quality of data. 

Data Scientists

Data scientists work closely with analysts and share many of the same skills and responsibilities. As a result, professionals in data analysis often have an interest in data science careers and vice versa. Data scientists collect large volumes of data using programming languages and analytical and statistical skills. These professionals earn around £51,990 per year. 

Here’s a glance at what data science job roles include:

• Collect and prepare data from various sources.
• Develop new features from existing data to improve model performance.
• Examine data to identify trends, anomalies and patterns.
• Access and manipulate data stored in databases. 

Financial Analyst

Financial analysts analyse financial data to help firms make strategic investment decisions. They implement research to determine the value of stocks, companies, bonds, and similar financial assets. Professionals in this job role work for banks, insurance companies, and investment firms, among other businesses. They earn around £40,192 per annum.

This is what a financial analyst job role covers:

• Analyse financial statements.
• Make financial forecasts and predictions.
• Study financial markets and economic data.
• Guide and determine the value of mergers and acquisitions.

Data analysis is an ever-evolving industry, and many trends are shaping the future of how professionals work. These are the top trends to consider for a career in data analysis.

AI and Machine Learning

Data analysts use AI and machine learning to identify patterns and trends within large datasets automatically. This is helpful because finding trends manually can be challenging when working with extensive, complicated datasets. AI and machine learning also make it easier to make data predictions while automating repetitive tasks, freeing up time for data analysis. 

Edge Computing

Edge computing processes data close to its source via IoT devices and sensors. This approach enables real-time analysis and quicker decision-making as it reduces latency and increases responsiveness to rapidly changing analytics environments. With the demand for more real-time analytics, data analysts will increasingly adopt edge computing in their processes.  

Explainable AI (XAI)

Explainable AI refers to AI systems designed to allow humans to understand and trust the generated results and output. In sectors where AI predictions are critical and may even impact human lives, XAI has become an integral tool for data analysts. Ultimately, XAI improves transparency and accountability in AI-driven decision-making. 

Data analysts use predictive analysis, complex data sets, and big data to provide insights that guide decision-making. This makes it critical for them to have skills like data visualisation, statistical analysis, programming languages, critical thinking, collaboration, and adaptability. 

There are many programmes and courses to help you launch your career as a data analyst. 

At LIS, we provide an interdisciplinary BASc degree to equip you with well-rounded skills focusing on applying logical and innovative thinking to complex real-world problems.

Ready to start your career as a data analyst? Contact us today.