Data analyst what is

Data analyst: job description Data analysts collect, organise and interpret statistical information to make it useful for a range of businesses and organisations.

Typical employers Qualifications and training Key skills A data analyst is someone who scrutinises information using data analysis tools. Typical duties include: using advanced computerised models to extract the data needed removing corrupted data performing initial analysis to assess the quality of the data performing further analysis to determine the meaning of the data performing final analysis to provide additional data screening preparing reports based on analysis and presenting to management Typical employers of data analysts Banks Specialist software development companies Consultancies Telecommunications companies Public sector organisations Social media specialists Colleges and universities Pharmaceutical companies Manufacturers Qualifications and training required Both university graduates and school leavers can enter the data analysis profession.

Read our IT graduate salaries article to find out how much you could earn in IT. Key skills for a data analyst A high level of mathematical ability Programming languages, such as SQL, Oracle and Python The ability to analyse, model and interpret data Problem-solving skills A methodical and logical approach The ability to plan work and meet deadlines Accuracy and attention to detail Interpersonal skills Teamworking skills Written and verbal communication skills Next: search graduate jobs , internships and school leaver opportunities in IT.

Spotlight organisations. Credit Suisse. Enterprise Rent-A-Car. Osborne Clarke LLP. Essential advice Green careers: find a graduate job that helps the environment. Careers advice and planning. Interviews and assessment centres. Skills and competencies. Read on to discover the daily job duties that could be part of your future career. Generally speaking, a data analyst will retrieve and gather data, organize it and use it to reach meaningful conclusions.

Companies in nearly every industry can benefit from the work of data analysts, from healthcare providers to retail stores to fast food chains. The insights that data analysts bring to an organization can be valuable to employers who want to know more about the needs of their consumer or end user. Regardless of which industry they work in, data analysts can expect to spend their time developing systems for collecting data and compiling their findings into reports that can help improve their company.

Analysts can be involved in any part of the analysis process. In a data analyst role, you could be included in everything from setting up an analytics system to providing insights based on the data you collect—you may even be asked to train others in your data-collection system. We enlisted some experts to help you get a sneak peek of the daily duties of a typical data analyst. Those reports give management insights about new trends on the horizon as well as areas the company may need to improve upon.

The most effective data analysts are able to use data to tell a story. In order to produce a meaningful report, a data analyst first has to be able to see important patterns in the data. Reporting in regular increments, such as weekly, monthly or quarterly, is important since it helps an analyst notice significant patterns. Surprised to see this on the list? Being able to communicate well is important. This often means working together with web developers to optimize data collection, according to Pearson.

Streamlining this data collection is key for data analysts. They work to develop routines that can be automated and easily modified for reuse in other areas. Analysts keep a handful of specialized software and tools in their arsenal to help them accomplish this. With all that in mind, you might be wondering about another prominent data role—the data scientist. Since the role of a data scientist is relatively new and sometimes nebulous, those in the field have worked to define and differentiate it from that of the data analyst.

This means responsibilities may change depending on the organization. At its core, data analytics is about answering questions and making decisions. Data analysts can tailor their work and solution to fit the scenario. For instance, if a manufacturer is plagued with delays and unplanned stoppages, a diagnostic analytics approach could help identify what exactly is causing these delays.

From there, other forms of analysis can be used for fixing these issues. These data sets are typically too large to process using traditional data analysis methods.

Big data is characterized by the three Vs: high volume , variety of data types, and the velocity at which the data is received. Programming languages: Learning a statistical programming language like Python or R will let you handle large sets of data and perform complex equations. Data visualization: Presenting your findings in a clear and compelling way is crucial to being a successful data analyst. Knowing how best to present information through charts and graphs will make sure colleagues, employers, and stakeholders will understand your work.

Tableau, Jupyter Notebook, and Excel are among the many tools used to create visuals. Statistics and math: Knowing the concepts behind what data tools are actually doing will help you tremendously in your work. Having a solid grasp of statistics and math will help you determine which tools are best to use to solve a particular problem, help you catch errors in your data, and have a better understanding of the results. Problem solving: A data analyst needs to have a good understanding of the question being asked and the problem that needs to be solved.

They also should be able to find patterns or trends that might reveal a story. Having the critical thinking skills will allow you to focus on the right types of data, recognize the most revealing methods of analysis, and catch gaps in your work.

Communication: Being able to get your ideas across to other people will be crucial to your work as a data analyst. Strong written and speaking skills to communicate with colleagues and other stakeholders are good assets in data analysts. Industry knowledge: Knowing about the industry you work in—healthcare, business, finance, or otherwise—will give you an advantage in your work and in job applications.

Acquiring these skills are the first step to becoming a data analyst. Here are a few routes you can take to get them that are flexible enough to fit in around your life.

Professional certificate: Entry-level professional certificate programs usually require no previous experience in the field. They can teach you basic skills like SQL or statistics while giving you the chance to create projects for your portfolio and provide real-time feedback on your work.

Several professional certificate programs on Coursera do just that. Get started with this data analytics reading list for beginners. For more on how to become a data analyst with or without a degree , check out our step-by-step guide.

Being a data analyst can also open doors to other careers. Many who start as data analysts go on to work as data scientists. Like analysts, data scientists use statistics, math, and computer science to analyze data.

A scientist, however, might use advanced techniques to build models and other tools to provide insights about future trends. Read more about other career paths open to data analysts , including management, consulting, or specializing. Learn how to clean, organize, analyze, visualize, and present data from data professionals at Google.

Data analysts tend to be in demand and well paid. If you enjoy solving problems, working with numbers, and thinking analytically, a career as a data analyst could be a good fit for you. Fields of study might include data analysis, mathematics, finance, economics, or computer science.

You might not be required to code as part of your day-to-day requirements as a data analyst.