Welcome to Understanding the Role of a Data Analyst. After watching this video, you will be able to: Summarize the role and tasks of data analysts Identify some of the main skills a data analyst needs And describe some possible career paths for data analysts. In the industry, opinions differ about the skills and responsibilityof different roles in data science. Moreover, many job titles and descriptions in data science appear to have overlapping responsibilities. For comparison, let’s look at some major roles in the data ecosystem. Data scientists analyze data for actionable insights and build machine learning or deep learning models that can train on past data to create predictive models. Data analysts translate data and numbers into plain language. Data analysts also mine data and visualize it to interpret and present their findings. Data engineers extract and organize data from different sources, clean and prepare it, and then store and manage it in data repositories so that other data professionals can access it. There are other data professionals in the ecosystem too, such as business analysts and business intelligence analysts, who make decisions based on the data results. Regardless of the roles and job titles, data science professionals generally work collaboratively to extract the data needed to identify trends or correlations and make predictions. Now let’s consider what a data analyst does in more detail. Data analysts: Translate data and numbers into plain language to help organizations make important business decisions. Inspect and clean data to make sure insights are valid and usable. Identify correlations, find patterns, and apply statistical methods to analyze data for actionable results. And visualize data to interpret and present the findings of data analysis to stakeholders. Data analysts usually do not develop their own models and algorithms but use existing tools and data sets to provide insights and identify trends within many industries. A data analyst acquires information about specific topics and then interprets and presents findings in reports that make the conclusions more accessible. Many different types of businesses use data analysts to find trends and patterns that will help with important business decisions. Some examples of the issues data analysts help solve include: Estimating the price of materials using past prices Estimating market shares Predicting transportation costs And determining when to hire or fire workers Data analysts always protect the organization’s data, ensuring that they produce consistent, reusable guidance. A good foundation for a career in data analysis is a bachelor’s degree in that topic. A degree in information technology or computer science with a minor in applied statistics or data analysis are also good choices. Computer science courses that emphasize project management and database management will give you a broad base of knowledge. Domain-specific knowledge and skills in the field you want to enter are also helpful. For example, if you are interested in medical fields, some knowledge of research methods, biology, and so on will make you a stronger candidate. While you’re in school, consider working at an internship. The experience you gain will be valuable to your job search later. Which tools are in high demand for data analysts? Someone entering the field might want to develop skills in SQL, R, and Python Big data manipulation using Hadoop, Hadoop Hive, and Hadoop MapReduce High-level creation of Hadoop programs using Apache Pig And data visualization and storytelling with Tableau. In addition to technical skills, data analysts need an array of important soft skills: Communication and presentation skills, so that they can effectively convey the insights they derive from data sets. Critical thinking skills, so that they can analyze and solve problems that arise Creative thinking skills to develop innovative ways to approach the data and create useful models The ability to convert data into a story that the company can understand and apply to their goals A collaborative approach, because they will always be working with other data professionals to glean the most meaning from data And diligence and tenacity to stick with projects and see them through when they become complex or something unexpected happens. If you are new to the field of data analysis, your first job in any organization is likely to be in an entry-level role, but with a background from a different field, consider all of what you have learned as an important asset. Many skills are transferable, especially from other technical work. Even your hobbies and personal interests provide some experience and level of expertise that may boost your marketability, depending on the company or industry you decide to pursue. So be sure to examine your background and other activities for capabilities you can use. From the beginning or as you gain experience as a data analyst, you may advance your career in several different directions. Depending on your goals and interests, you may progress into becoming a specialist in some aspect of data analysis like social media, advancing your technical skills in programming or deeper data analysis, becoming a manager for a data analytics team, or going into business as a consultant, to name only a few. Let’s take a closer look. Sometimes a career path takes you deeper into the specialized knowledge of a specific discipline in data analytics, such as: Social media analytics Insurance and actuarial data analysis And fraud, credit, or sales analysis. If you have a love or aptitude for one of these areas, it can be a great idea to dive into it and become the go-to professional in that discipline. You may choose to progress into a senior role, building your toolkit as time goes by. This requires gaining more skills and developing the skills you have, including: Acquiring programming skills Learning more advanced mathematics And developing an understanding of many aspects of data science, such as AI and machine learning models, big data work, and others. Rather than diving deeper as a specialist, the senior data analyst works to broaden and grow many skills. If you’re interested in business, you may advance into a management position. This requires business aptitude and people skills as well as data analysis skills. Data analysis managers make a significantly higher salary, however. If this is your goal, you may want to: Focus on developing leadership and other people skills Acquire project management skills And consider acquiring a graduate degree or certifications in project management. Management isn’t for everyone, but it may a good fit for you if you like the required mix of skills and work. If you become a consultant, you can choose exactly what type of data expertise you want to develop. Since you are likely to be an independent worker, you may have some freedom about the situations you choose to work in. Consultants may want to: Develop experience working in the data-driven aspects of specific industries Acquire knowledge of policies and regulations that affect data management, such as customer privacy and data-collection protocols And understand the basics of running your own business. Consultancy can be a great path if you want to design your own career, with all the freedom and risk that may entail. In this video, you learned that: Data analysts apply their specific skills and expertise to derive business insights from data sets. A career in data analysis requires specialized knowledge and technical skills And there are several possible career paths that data analysts can follow as they progress. Data analysis is one of the fastest-growing professions in the world today, so if you set your sights on entering the field, the sky’s the limit for how far you can go.
