Often, businesses collect and store more data than they need or can handle. To turn data into actionable insights, companies often employ professionals like data analysts. Knowing what these professionals do and what skills they possess can help you plan a career in this field. In this article, we will discuss what data analysts do and outline the 10 data analysis skills they need to excel in their career.
What does a data analyst do?
A data analyst collects, interprets and analyses data and turns it into insightful information. An organisation uses this information to make business decisions and enhance their growth.
Often, their analysis can help an organisation improve efficiency, enhance production, understand customer needs, increase profit and positively impact other valuable aspects of business operation. Apart from conducting extensive research, these professionals develop meaningful reports and share them with internal stakeholders.
What are the duties of a data analyst?
Regardless of the industry in which they work, a data analyst is responsible for the following tasks:
- Collecting and interpreting data gathered from various sources
- Designing data systems and databases
- Analysing the collected data and presenting it in a format that is easily understandable
- Streamlining data collection methods to automate different business processes
- Using statistical software to interpret data and paying attention to trends and patterns in the data set
- Maintaining databases by monitoring performance and addressing errors
- Collaborating with engineers, programmers and stakeholders to identify various opportunities for process improvement and to develop data governance policies
- Preparing informative reports for internal stakeholders to use in client meetings
What is data analysis?
Data analysis is the process of collecting, interpreting, evaluating, analysing and visualising a dataset to find meaningful insights that help in taking effective business decisions. It can help businesses improve specific aspects of their products and services and positively affect their productivity. Also, through data analysis, organisations can understand the needs of their customers and employees.
For example, the product team may use data analysis to understand how customers interact with their products and what extra features they want to see. Organisations can convert this insight to make improvements in the product and enhance functionality by adding extra features.
Top 10 data analysis skills
Here are the top 10 data analysis skills to master for a successful career in this field:
- Structured Query Language (SQL)
- Microsoft Excel
- Mathematical skills
- Statistical programming language
- Machine learning
- Data visualisation
- Data collection and cleaning
- Critical thinking
SQL is the database coding language that extracts, organises and manages large datasets stored in relational databases. Proficiency in SQL can help you add, delete, update and extract information from any database. Without SQL, you cannot perform any substantial analysis. Therefore, it is a prerequisite for data analysis.
Employers prefer data analysts with this skill because it helps them carry out analytical functions and transform data structures. As a data analyst, you should know how to create joins, retrieve data, develop stored procedures and create aggregations so that you can analyse data and provide meaningful business insights to your clients.
2. Microsoft Excel
Microsoft Excel is one of the most well-known tools for working with data. Apart from providing quick analytics, it offers an easy way to store data. As a result, many organisations prefer storing and analysing data in Excel. Furthermore, employers prefer analysts with advanced Excel knowledge because it helps manipulate and visualise data to draw profitable insights from it.
For example, you may use the “Named Range” feature to create a makeshift database in Excel or use “Pivot Tables” to summarise, reorganise, group, count, sort or calculate the average of your data. You may also use Visual Basic for Application (VBA) to create macros that facilitate speedy data analysis.
3. Mathematical skills
Data analysts often need to quantify and process loads of data. Because of this, they should possess strong mathematical skills. Additionally, expertise in advanced mathematics can help you understand numbers and how to operate and combine them to support your analysis.
For example, you may use probability distribution to analyse and visualise data to discover meaningful insights. Or, you may use the concept of dimensionality reduction to process a dataset with too many variables. This makes mathematics the most in-demand skills when employers hire a data analyst.
4. Statistical programming language
Statistical programming language like Python and R can help your perform analysis in a way no spreadsheet can do. The ability to write codes in these languages ensures you can analyse and visualise large data sets more efficiently. Mastery over one language is sufficient to excel at your workplace. Both these statistical programming languages can help you accomplish your day-to-day duties.
Data analysts use R specifically for statistical data analysis and Python for a more general approach to data analytics. As both the languages are open source, learning any of them can increase your employability and get you hired fast.
5. Machine learning
Machine learning is a branch of Artificial Intelligence (AI) that is important in data analytics. It primarily focuses on building algorithms specifically designed to find trends and patterns in a data set. Over time, the algorithm improves the accuracy of finding patterns. A data analyst can use machine learning to automatically create analytical models.
Also, many organisations that use highly specialised machines to carry out data analysis prefer hiring professionals who understand how machine learning works. With AI being a growing field, data analysts with machine learning skills are incredibly valuable and often preferred over candidates who do not understand machine learning.
6. Data visualisation
Data visualisation is the ability to communicate and present your insights and findings via graphs, charts or other illustration. It is an essential skill because it facilitates information in a way that is easily understandable by someone with no training in data analysis. Using this skill, you can help organisational leaders understand complex ideas and identify patterns.
Also, with data visualisation, you can provide simplified business solutions that maximise understanding and cognition. The ability to use the right chart to answer a common business question can make you a desirable candidate for a data analyst role.
Related: Types of Graphs and Charts
7. Data collection and cleaning
Data collection is the process of collecting and managing data based on the variables related to the goal an organisation wants to accomplish through analysis. It is the foundation and a necessity for a job in data analytics. While you should have a comprehensive understanding of collecting data, it is important to understand data cleaning.
Data cleaning is removing and fixing all incorrect data in the dataset. This includes duplicate, corrupted and incorrectly formatted data. Data cleaning is a desirable skill because it ensures the accuracy of data, as inaccuracy in the dataset often results in erroneous analysis.
8. Communication skills
Data analysts work together with diverse departments and professionals to develop profitable solutions for an organisation. You communicate and work in close liaison with IT representatives, developers, other data analysts, clients and organisational leaders. So, you should be able to effectively communicate insights derived from your analysis and suggest solutions to improve your organisation's productivity.
You may also be responsible for writing performance reports that are easy to understand. Excellent communication skills for a data analyst include active listening, written and verbal communication.
9. Critical thinking
When performing data analysis to come to logical solutions, you have to determine a hypothesis. For determining a hypothesis, it is essential to know what data to collect and how to process it. Excellent critical thinking skills allow you to understand the type of data to collect, identify the connection between distinct data points and use that information to create intelligent solutions to a business problem. Employers prefer hiring critical thinkers to assess all available information to reach logical decisions.
Many organisations hire data analysts to interpret and analyse data to solve or prevent problems from occurring. Good problem-solving skills can help you identify current and potential issues and determine a viable solution based on the data you collect.
Skills associated with problem-solving that a data analyst should possess are dependability and decision-making. Employers highly value employees on whom they can depend for identifying and implementing solutions as fast as possible.
Please note that none of the companies mentioned in this article is affiliated with Indeed.