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 responsibility of different roles in data analysis. Moreover, many job titles and descriptions in data analysis appear to have overlapping responsibilities. For comparison, let’s look at some major roles in the data ecosystem. Data scientists build machine learning or artificial intelligence models that can train on past data to create predictive and prescriptive models. Data analysts gather and translate data and numbers into actionable insights. Data analysts also mine, analyze, and visualize data and present their analyses as a coherent and compelling story. 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 engineers, analysts, and scientists 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: Inspect and clean data, called pre-processing, and conduct exploratory analyses. Translate data and numbers into insightful and actionable analyses. 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. All of this is meant to help drive important business decisions backed by data. 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. However, advanced data analysts sometimes do create their own models. A data analyst acquires information about specific topics and then interprets and presents findings in reports that make actionable conclusions more accessible. Often, data analysts are required to work cross-functionally to help define key performance indicators, then monitor and visualize them via creation of company-wide dashboards. 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, Predicting customer retention and churn, Predicting transportation costs, And understanding what causes website traffic fluctuations as well as what fluctuations mean. 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 a technical field. A degree in information technology or computer science with a minor in applied statistics or data analysis are great 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 and Looker. 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 prioritize one analysis over another. 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. As data analysis becomes more ubiquitous, there will be additional focus on specific domain expertise you bring to the table in specific industry. 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.