From the course: Learning Data Analytics: 1 Foundations

Discovering if you are an analyst

From the course: Learning Data Analytics: 1 Foundations

Discovering if you are an analyst

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- [Instructor] Do you have a fitness tracker or a calorie counter of some sort? If you said yes, then you're already gathering data. Do you walk more when you notice your steps are low? Do you eat more or less based on what you did earlier in the day or yesterday? Are you using your history to determine what you should do next? Do you set a target on your calories and do you monitor your calories and make adjustments to stay within your goals for the day? Then you're already using data for decision-making, which means you're already analyzing data. This is just a practical example of how we all capture and analyze data, but data analysts take these skills and go even further. For years, I suggested that there are far more people that are working as data analysts than we might believe based on their job titles. We did a small local study where we asked people to identify if they were data workers, and then we asked them things like their job titles. We asked people to self-identify if they were data workers based on the European Data Market Study definition who are workers who collect, store, manage and analyze data as their primary activity, or as a relevant part of their activity. We then analyzed their job titles to determine if job titles could and should be used as an indication of who's a data analyst. Overwhelmingly the response from people who considered themselves data workers in organizations of all sizes and all industries did not have the literal words data analyst in their job titles. Because we are data analysts, we searched deeper into the titles for the words data or analyst, and even though we found the word analyst was more prevalent, even then, 73% who considered themselves data workers had no occurrence of data analyst, or data or analyst in their titles, and their titles were all sorts of different things. Even more interesting to me was that even if they did not describe themselves as a data worker, they were still performing data-related tasks and processes and using data-related software. As data has grown and been adopted by organizations around the globe, more people are using data to provide information to their leadership, their departments, and they report outcomes even if it's just historical. People are performing key tasks, even on the smallest of datasets. They're inspecting, cleaning, transforming and modeling data for reports that are consumed weekly, monthly, or even annual. Ask yourself, are you exporting data out to Excel or CSV to work with it? I would call these flat files. Finding and accessing data to work with it is something that a data analyst does on every project. When you get that data out of the system or systems, do you ever delete columns or add calculations that your system doesn't provide? This is a form of data cleaning and transformation. It's an everyday part of life for a data analyst. Do you build V lookups or X lookups to bring data from other worksheets or other files? If you are, then you're using joins and modeling datasets. Are you then building pivots, crosstabs, charts or graphs? This would be an example of the visualization of information. Does this sound like you? Data analysts perform some or all of these tasks at any given time or all of the time. Data analysts find, collect, and/or capture data. They inspect it, they transform it. They add functions and formulas, and then they merge data sets so they can then further analyze it with pivots, charts and other visualizations. All data has a purpose and the data analyst is typically seeking answers to the questions and then performing tasks like cleaning and transforming data to provide insight and informed decision-making.

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