Every business collects data, be it for market research, sales figures, logistics, or other expenses. Data alone is not enough to give meaningful information - they need to be analyzed. In doing this, companies will need data analysts. Data analysts interpret numbers and data into concise explanations to support companies in making informed business decisions. Various industries, such as finance, IT, consumer goods, and medical have made data analysts part of their business operation.
So, what does it take to be a data analyst? Read through this week’s Job Review on Data Analyst and see if you are a good fit for this career.
Data analysts’ core responsibility is to turn raw data into meaningful insights. They strive to uncover and share valuable insights by systematically analyzing data for patterns and correlations. Data analysts are also expected to address specific issues and answer questions based on the data insights obtained.
The analysis of data generally goes through five stages: identifying, collecting, cleaning, analyzing, and interpreting. Data analysts commonly make recommendations regarding how a company obtains and analyzes data in order to enhance the quality and efficiency of data systems. According to Hudson, here are some general responsibilities of a data analyst:
Identifying and collecting data source
Analyzing data to find answers to specific questions
Setting up data infrastructure
Developing, implementing, and maintaining databases
Assessing the quality of data and removing or cleaning data
Generating information and insights from data sets and identifying trends and patterns
Preparing reports for executive and project teams
Creating visualizations of data
Candidates with solid educational qualifications would be preferred among their competitors as entry-level analysts. Due to the rising demand for data analysts worldwide, those with no academic background in statistics, math, or data science can still have a shot as a data analyst if they have solid data science course certifications and proven experience.
Data Analyst = Data Scientist?
Data analyst job is often confused as data scientist, whereas the two are actually quite different. Both roles deal with data, yes, but their approaches to it differ. Data analysts generally use existing data to address specific business challenges. Meanwhile, data scientists create new algorithms and models to forecast the future. After acquiring experience, developing their programming and mathematical abilities, and getting an advanced degree, many data analysts move on to become data scientists.
Skills and Traits as a Data Analyst
Skills needed by data analysts vary depending on their industry, since analysts are expected to make business recommendations based on the data obtained. Even so, all beginner data analysts need to have a set of technical skills, and here are some of them:
Math and statistics
A good understanding of statistics and mathematics will help decide which tools are appropriate to use to address a certain problem. This can also help to spot errors in data and get a better comprehension of the outcomes. While a degree in Mathematics or Statistics can be useful for this, they are not always necessary. For newcomers, fundamental math skills like algebra and calculus can just be sufficient.
Common programming skills data analysts usually comprehend are Python or MATLAB and statistical computing languages like R and SAS. Understanding these programming skills can help in handling large sets of data and performing complex equations.
Microsoft Excel and SQL should be essential instruments in the portfolio of any data analyst. While Excel is extensively used across sectors, SQL can handle bigger data volumes and is often considered as a must-have tool for data analysis.
The capacity to display data through charts and graphs is a critical part of data analytics to spot patterns, correlations, and trends. Knowing how to best display information using charts and graphs can ensure that the work is understood by colleagues, employers, and stakeholders. Some tools used for this are Business Objects, PowerBI and Tableau.
In addition to these technical skills, data analysts are also expected to possess traits that will help them succeed in their job. Strong attention to detail is a must-have soft skill for data analysts, as they will need to identify trends, patterns and insights from data very closely. Presentation skill is another desirable trait of data analysts, as they will need to not only analyze data but also deliver presentations in a less technical and understandable manner. On top of that, problem solving skills need to be exercised continuously by data analysts for creating strategic business recommendations from the analyzed data.
If you think you have the skill and aptitude needed for this job, you can start your career as a data analyst. Talentvis provides plenty of job opportunities as a data analyst in some of the best Southeast Asian companies. Check them out!