Data Analysis Skills
Do you require data analysis skills to function well in your job role? This article provides a guide on how you can develop the skills and include them on your resume.
What is Data Analysis?
While many groups, organizations, and experts approach data analytics differently, most can be summed up in one universal definition. Data analytics is the process of cleaning, modifying, and processing raw data and extracting useful and relevant information that helps businesses make informed decisions. This process reduces the risks inherent in decision-making by providing useful information and statistical data, often presented in the form of charts, images, tables, and graphs.
A simple example of data analysis can be seen every time we decide on our daily lives, evaluating what has happened in the past or what will happen if we make that decision. It is essentially a process of analyzing the past or the future and making a decision based on that analysis.
It is not uncommon to hear the term “big data” when talking about data analytics. Data analytics plays a crucial role in turning big data into useful information.
Importance of Data Analysis Skills
- Define your target audience more precisely
You don’t want to waste your company’s valuable time, resources, and money running advertising campaigns aimed at demographic groups that have little or no interest in the products and services you offer. Data analysis will help you understand where to focus your advertising efforts.
- Gain insight into your target customers
Data analysis allows you to track the effectiveness of your products and campaigns with your target population. With data analytics, your company can better understand the consumer habits, disposable income, and most likely interests of your target audience. This data helps companies set prices, determine the duration of campaigns, and even predict the number of products needed.
- Reduce operating costs
Data analysis shows which areas of your business need additional resources and money, and which areas are not performing and therefore need to be reduced or eliminated.
- Better problem-solving methods
Informed solutions are more likely to succeed. Data provides information to the business. You can see where that progress is leading. Data analysis helps companies make the right choices and avoid costly mistakes.
- You get more accurate data
If you want to make informed decisions, you need data, but that’s not all. The data must be accurate. Data analysis allows companies to get up-to-date and accurate information suitable for developing future marketing strategies, and business plans and redefining the company’s vision or mission.
How to improve your Data Analytical Skills
- Clearly Define the Desired Outcomes and Outputs
As obvious as this point is, too often the desired outcome of a particular thinking exercise is not clearly defined or expressed, and therefore the results do not contribute to those outcomes. In general, analytical exercises are considered holistically and the necessary steps are planned with the result in mind. In addition, data can be processed to address a wide range of situations or problems. It is therefore very important for any team to clearly define and agree on the desired outcome – which may not be as easy as it sounds – because everything else will flow from it.
- Ensure that the Necessary Data is Collected
For the uninitiated, and even for those who hopefully know better, the assumption is that for any question asked, it is easy to find data that will provide the right answers. This is not the case. Systems must first be put in place to collect or generate that data.
For example, it may be necessary to conduct regular surveys, which requires the preparation and subsequent application of survey tools such as a questionnaire. Once this is done, there is likely to be a problem in obtaining enough valid responses and ensuring that the resulting data is in a format that can be easily manipulated and processed. Indeed, data collection can be a tedious and time-consuming process that cannot be done “now and for now.” It is therefore always advisable to ensure that the necessary data is collected from the outset.
- Understand what Is Possible with the Data Collected/Available
Despite carefully developed plans, something new will inevitably come up in the analysis that has already been done, such as a request from a senior manager for which the data already collected can be used. It is, therefore, necessary to consider how the data collected can be used and, therefore, when it may not be sufficient for certain purposes.
Furthermore, it is important to note that the results obtained from the data collected and the analysis performed are not infallible. It is therefore necessary to assess the margin of error and the extent to which the results can be trusted. These considerations are even more important when circumstantial or third-party data is used to assess the situation in your organization.
- Learn the Basics of Several Software Applications
Finally, to broaden the range of discussions you can have in your organization and to enhance your understanding of data analysis, it would be helpful to learn the basics of at least one software application. The application chosen can be used in your organization, e.g. Tableau, Pentaho, Google Analytics Premium, Wave Analytics, etc., and is therefore directly relevant. You can also start with Microsoft Excel, which most of us are familiar with and which is widely used in the corporate world, but extremely underutilized, given the functions and features it has.
Jobs that require Data Analysis Skills
- Medical and Health Analyst
As the name implies, medical and healthcare data analysts use data from a variety of sources to improve medical outcomes. They typically focus on the business side of medicine, improving the quality of patient care or streamlining operations.
- Market Research Analyst
Market research analysts collect and evaluate data on consumers and competitors. Market research analysts study market conditions to assess future sales of a product or service. They help companies determine what products customers want to buy, who will buy them, and at what price.
- Business Analyst
Data is used by business analysts to create business insights and advocate for improvements in businesses and other organizations. Business analysts can detect problems in almost every aspect of a business, including IT processes, organizational structures, and employee development. As companies constantly strive to improve their overall efficiency and reduce costs, business intelligence is gradually becoming an integral component of their operations.
- Business Intelligence Analyst
Business Intelligence Analysts (BI Analysts) analyze data and other information to help companies make effective business choices. They may collect, cleanse and analyze data such as company revenue, sales volume, market information, or customer engagement metrics. BI analysts may also create tools and data models to visualize or monitor data.
- Operations Research Analyst
Operations research analysts are senior-level professionals who use sophisticated problem-solving approaches such as optimization, data mining, statistical analysis, and mathematical modeling to provide solutions that help businesses and organizations operate more efficiently and profitably.
- Intelligence Analyst
Intelligence analysts examine information and data to identify and mitigate security issues. Examples of information sources include internal and external statistics, databases, and field reports. To synthesize information and develop action plans, analysts must have good research, comprehension, and analytical skills.
How to include Data Analysis Skills in your Resume
- Give a concise professional summary
A professional summary is a perfect place to get the hiring manager’s attention. Start your data analyst resume by highlighting your best skills and professional achievements related to the position. Always study the job description and choose the most important desired qualifications listed there to include in your professional resume as well as the rest of your resume.
- List your relevant skills
List a few key digital skills in the essential qualifications section of your data analyst resume, especially if the job posting lists them as desired skills. Be sure to include soft skills, such as communication or problem-solving, as well as specific skills in your resume.
- Include your work history as a data analyst
List your work experience in reverse chronological order, meaning your current or most recent job comes first. For each job, include three to five bullet points indicating the major responsibilities and accomplishments in that job; avoid just mentioning routine daily tasks.
- Show your educational qualifications
As a data analyst, you’re likely to have a bachelor’s degree in statistics, as shown in our sample data analyst resume, or another relevant field, such as information technology. Use the “Education” section to indicate your degree. If you graduated from college more than 10 years ago, you don’t need to list the graduation date.
Example of How to include Data Analysis Skills in your Resume
The example below are good examples of how to include analytical skills on a resume for someone seeking the post of Data Analyst;
- Collect data from sales, marketing, and finance departments for use in the development of the organizational structure.
- Organize, extrapolate and disseminate data across departments to conclude the success of current practices.
- Provide detailed reports on the meaning of the data collected to senior management and assist in identifying scenarios that leverage changes in the data.
How to Demonstrate Data Analysis Skills in an Interview
- Explain your data analysis methodology
Share your approach to data analysis, such as the type of analysis you typically use, the data sources and tools you use, and the methods you use to interpret the data.
- Demonstrate your data analysis skills
Showcase any projects you have completed or specific examples of your work to demonstrate your data analysis skills.
- Explain the results of your analysis
Talk about the results of your analysis, such as the insights or conclusions you were able to make from the data.
- Discuss challenges and solutions
Describe any challenges you faced in your analysis, such as data quality or missing information, and how you addressed them.
- Walk through a case study
Provide a step-by-step walkthrough of a data analysis case study to show how you approach data analysis problems.
- Highlight your communication skills
Describe how you communicate your findings, such as presenting data-driven stories or translating complex analysis into easy-to-understand visuals.
Examples of Interview Questions to Test Data Analysis Skills
- Are you comfortable working with large amounts of data?
This question will help the reviewer determine if you have the skills and experience to work with large amounts of data. Use your answer to highlight your analytical, problem-solving, and communication skills.
- What skills are most important for a data analyst?
This question will help the reviewer determine if you have the skills needed to succeed in this role. Use your answer to highlight some of the most important skills for a data analyst and explain why they are so important.
- How do you look for errors in spreadsheets?
This question will help the reviewer understand your analytical skills and how you use them to solve problems. Use examples of past experiences where you have used data analysis to look for errors in spreadsheets or other documents.
- What is your experience with data visualization tools?
Data visualization tools are a common skill for data analysts. They allow you to create graphs and charts that help you analyze large amounts of data more quickly. Your answer should show the reviewer that you know how to use these tools effectively. You can mention which ones you have used in the past, what your experience was with them, and why you chose them.
- Give an example of a time when you used data to make a decision that benefited your employer.
This question allows you to highlight your analytical skills and how they can benefit the company. When answering this question, try to provide an example that demonstrates your ability to use data to make decisions quickly and efficiently.
- If you discovered that your information was incorrect, how would you react?
This question is an opportunity to demonstrate your problem-solving and coping skills. Your answer should include a concrete example of how you have responded to a similar situation in the past.
- What would you do if you were given a large data set and limited time to conduct your analysis?
This question will help reviewers understand how you prioritize your work and manage deadlines. Use examples from past experiences to explain how you would plan a project, set goals, and complete the analysis promptly.
- How well do you understand the concepts of probability and risk?
This question is a great way to test your knowledge of data analysis and how you apply it. Give examples of past experiences where you have used the concepts of probability and risk to solve problems or make decisions.
- Do you have experience using SQL to query large data sets?
SQL is a common language used to query data and interact with databases. Employers ask this question to see if you have experience using SQL in previous positions. If so, give an example of how you used it. If not, explain what you are willing to learn.
- When analyzing large amounts of data, how do you prioritize tasks?
This question will help the reviewer understand how you approach your work and which tasks are most important. Use examples from previous experience to explain how you prioritize and manage multiple projects simultaneously.
