Data Analytics Jobs 101: A Comprehensive Overview and Career Guide

Data analytics is one of the most highly sought-after technical competencies in the 21st century. Data analysts help organisations extrapolate and process the vast amounts of data they collect in order to leverage it to improve their products, services, and decisions. 

Data analytics jobs are diverse, rewarding, and in high demand across various industries and sectors. 

The article aims to explore what data analysis entails, the job responsibilities, salary prospects, and why data analytics is crucial for businesses across industries. 

What is data analysis?

Data analysis is fundamentally the iterative process of collecting, cleaning, transforming, and interpreting data to answer questions or solve problems. Data analysis activities can be executed manually, or with the aid of software tools and programming languages.

Read: “What is data analytics: A complete guide

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What does a data analytics job include?

A data analytics job principally revolves around applying data analysis techniques to answer questions or solve problems for an organisation. 

A data analyst typically works with data from various sources, such as databases, spreadsheets, web pages, social media platforms, sensors, or surveys. A data analyst also uses multiple tools and programming languages to manipulate, visualise, and communicate data.

A data analytics job may include the following tasks and responsibilities:

  • Gather data: A data analyst collects data from internal or external sources that are relevant to the problem or question at hand. Their work may involve designing surveys or questionnaires, scraping web pages or APIs (application programming interfaces), accessing databases or cloud storage services, or purchasing datasets from third-party providers.
  • Clean data: A data analyst ensures that the data is accurate, consistent, complete, and reliable by removing errors, duplicates, outliers, or missing values. In this respect, their tasks may involve using spreadsheet functions or formulas, writing scripts or queries in programming languages such as Python or SQL (structured query language), or using specialised data-wrangling software tools such as OpenRefine or Trifacta.
  • Model data: A data analyst organises and structures the data in a way that facilitates analysis and interpretation. 
  • Interpret data: Data analysts interpret the results of their analysis and draw conclusions or insights from them. They may utilise various tools and techniques to interpret data, such as statistics, data visualisation, machine learning, data mining, text analysis, sentiment analysis, web analytics, etc.
  • Present data: Data analysts communicate their findings and recommendations to their stakeholders or clients using clear and effective reports, dashboards, slides, or other formats. They may use various tools and techniques to present data, such as Tableau, Power BI, Excel, Google Sheets, Google Slides, etc.

Is data analytics a good career?

Absolutely! The field of data analytics offers promising career prospects. Organisations across industries are increasingly relying on data to drive decision-making and gain a competitive edge. As a result, there is an ever-increasing demand for skilled data analysts who can extract meaningful insights from complex datasets.

Industries that require data analysis

Data analytics skills are valuable across a wide range of industries. From finance, sports, and healthcare to marketing and retail, organisations in almost every sector can benefit from data-driven insights. Some of the standout industries that heavily rely on data analysis include:

  • Finance and Banking: Banks and financial institutions use data analysis to detect fraud, assess credit risk, and improve customer experience.
  • Healthcare: Data analysts in healthcare analyse patient records, clinical trials, and medical research data to enhance treatment outcomes and optimise operations.
  • Marketing and Advertising: By analysing customer behaviour and market trends, data analysts help organisations develop targeted marketing campaigns and improve customer engagement.
  • Retail and E-commerce: Data analysis is instrumental in optimising inventory management, personalising customer experiences, and predicting market demand.
  • Technology and Internet: Companies in the tech industry use data analysis to gain insights into user behaviour, enhance product development, and improve customer satisfaction.


Data analysis job responsibilities

The responsibilities of a data analyst may vary depending on the organisation and industry. However, some common tasks and responsibilities include:

  • Data Collection and Cleaning: Gathering data from various sources, ensuring data integrity, and transforming raw data into usable formats.
  • Exploratory Data Analysis (EDA): Performing statistical analysis, data visualisation, and identifying patterns, trends, and outliers.
  • Statistical modeling: Applying statistical techniques to identify correlations, forecast trends, and build predictive models.
  • Data visualisation: Creating visual representations of data using charts, graphs, and dashboards to communicate insights effectively.
  • Collaboration and Communication: Working closely with stakeholders to understand business requirements, present findings, and make data-driven recommendations.


What tools do data analysts use?

Data analysts exploit a variety of tools and technologies to perform their tasks efficiently. Here are some commonly used tools in the field of data analytics:

  • Microsoft Excel: Excel is a versatile tool for data analysis, offering functions, formulas, and data manipulation capabilities.
  • Python and R: These programming languages are widely used for statistical analysis, machine learning, and data visualisation.
  • SQL: Structured Query Language (SQL) is vital for working with databases and performing data querying and manipulation.
  • Data Visualisation Tools: Tools like Tableau, Power BI, and Matplotlib enable analysts to create compelling visualisations and dashboards.
  • Statistical Software: Statistical software suites such as IBM SPSS, SAS, and STATA provide advanced statistical analysis capabilities.

Proficiency in these tools is crucial for data analysts, and staying updated with the latest tools and technologies is essential to excelling as a Data Analyst.


Data analyst salary

Data analytics is a rewarding field, both intellectually and financially. While salaries can differ depending on factors like location, experience, and industry, data analysts generally enjoy competitive compensation. 

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The average salary for Data Analyst in Singapore is SGD 13,550 per month. 

Do kindly note that these figures are approximate and may vary significantly based on individual circumstances and factors specific to each job market. 

Therefore, it’s always advisable to research salary trends in your desired location and industry.


What types of data analytics jobs do businesses need to help them succeed in the new data-driven world?

Data analytics jobs are in very high demand across various industries and sectors as more and more organisations realise the value of data-driven decision-making. 

In today’s fast-paced and modern business landscape, data analytics professionals can help businesses to:

  • Understand their customers’ needs, preferences, and behaviour better.
  • Optimise their marketing campaigns and increase their return on investment.
  • Improve their services, marketing campaigns and services based on customer feedback and market trends.
  • Enhance their operational efficiency and reduce costs.
  • Identify new opportunities and risks and act on them proactively.
  • Innovate and create competitive advantages in their industry.

Accord Training is a leading provider of data analytics courses and certifications for professionals who desire to advance their careers in this field. We offer virtual and on-site courses that cover various topics such as data analysis, data visualisation, machine learning, artificial intelligence, and more. We also help organisations design and implement data analytics solutions that suit their specific needs and goals.

Why do companies need to create in-house data analysis profiles or train their employees

According to a study by MicroStrategy, companies worldwide are widely leveraging data to: 

  • Appreciably improve efficiency and productivity (64 percent). 
  • Achieve more effective decision-making (56 percent). 
  • Drive better financial performance (51 percent). 

The research also denotes that 65 percent of global enterprises plan to increase analytics spending.

However, not all organisations have the necessary skills and resources to leverage data analytics effectively.

According to a survey by Accenture, only 21% of business leaders are confident in their workforce’s ability to use data and analytics tools. This means that many organisations are missing out on the benefits of data analytics and losing their competitive edge.

One way to overcome this overarching systemic challenge is to create in-house data analysis profiles or train existing employees on data analytics skills. By doing so, organisations can:

  • Empower their employees to use data for problem-solving, innovation, and decision-making.
  • Reduce their reliance on external consultants and vendors for data analysis.
  • Increase their agility and responsiveness to changing market conditions and customer needs.
  • Enhance their data quality, security, and governance.
  • Foster a data-driven culture that values evidence over intuition.

To create in-house data analysis profiles or train existing employees on data analytics skills, organisations must invest in effective and engaging learning programmes catering to different proficiency and interest levels. One such programme is Accord Training’s Data Analytics: An Overview in Stories course.

This course is expressly designed for anyone who seeks to learn the basics of data analytics without any prior knowledge or academic background in analytics. It uses storytelling techniques to explain key concepts and methods of data analytics in a simple and intuitive way, covering topics such as:

  • Basics of data analytics 
  • Applications of analytics
  • Framework for analytical decision making
  • Overview of predictive analytics and machine learning
  • Common techniques used in predictive analytics and the intuitive thinking behind these techniques
  • Demonstration of analytics using tools
  • Examples of the applications of analytics across functions and industries
  • Trends in analytics

The course also provides real-world examples and case studies from various industries and domains to illustrate how data analytics can be applied in different contexts and scenarios. It is interactive and engaging, with quizzes, exercises, assignments, and feedback to reinforce learning outcomes.

It is, therefore, a great way for organisations to create in-house data analytics profiles or train existing employees on data analytics skills. The course is well-suited to anyone who seeks to learn how to leverage data for better decision-making and business outcomes.



In conclusion, data analytics jobs play a vital role in today’s data-driven world. The demand for skilled data analysts continues to grow as organisations seek to extract valuable insights from vast amounts of data. By understanding the responsibilities, salary prospects, and importance of data analytics across industries, individuals can make informed decisions about pursuing a career in this field.

Furthermore, organisations can greatly benefit from investing in in-house data analysis capabilities or providing training to their employees. By developing data analytics skills within their workforce, companies can easily unleash the full potential of their data assets and make data-driven decisions that drive success.

Remember, data analytics is not only about numbers and statistics; but also, it’s about uncovering meaningful insights that can shape the future of businesses and industries. 

So, whether you’re embarking on a career in data analytics or considering training opportunities for your organisation, embrace the power of data and take advantage of the exciting possibilities it offers.

Reach us at Accord training to learn more about customisable data analytics courses.

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