In a recent post about the benefits of data marts, Vicky Yu highlighted a surprising stat: just a few years ago, data scientists would spend up to 80 percent of their work hours wrangling and cleaning data. Even if the percentage is lower these days (as some surveys suggest), that still leaves relatively little time for analysis and insight generation. Which makes one wonder: isn’t that supposed to be the core of a data professional’s job?
This week, we turn to the crucial (if sometimes under-discussed) area of data analysis, and share several recent articles that focus on how analysts should work—and how they can make the most of their finite time and powerful skills.
- Are we doing exploratory data analysis all wrong? “EDA is not a specific set of instructions one can execute — it is a way of thinking about the data and a way of practicing curiosity.” Viyaleta Apgar’s recent post is a thought-provoking invitation to reevaluate the way we approach analysis, and to avoid rushing into the process without reflecting on our own assumptions, biases, and blind spots.
- Take a glimpse into the day-to-day experience of a healthcare data analyst. Data-focused work can look strikingly different across industries and workplaces, which is why it’s so useful to learn about the real-life experiences of practitioners. Rashi Desai generously shares her firsthand impressions of data-analytics work in the healthcare sector, and dispels some common misconceptions along the way.
In a recent post about the benefits of data marts, Vicky Yu highlighted a surprising stat: just a few years ago, data scientists would spend up to 80 percent of their work hours wrangling and cleaning data. Even if the percentage is lower these days (as some surveys suggest), that still leaves relatively little time for analysis and insight generation. Which makes one wonder: isn’t that supposed to be the core of a data professional’s job?
This week, we turn to the crucial (if sometimes under-discussed) area of data analysis, and share several recent articles that focus on how analysts should work—and how they can make the most of their finite time and powerful skills.
- Are we doing exploratory data analysis all wrong? “EDA is not a specific set of instructions one can execute — it is a way of thinking about the data and a way of practicing curiosity.” Viyaleta Apgar’s recent post is a thought-provoking invitation to reevaluate the way we approach analysis, and to avoid rushing into the process without reflecting on our own assumptions, biases, and blind spots.
- Take a glimpse into the day-to-day experience of a healthcare data analyst. Data-focused work can look strikingly different across industries and workplaces, which is why it’s so useful to learn about the real-life experiences of practitioners. Rashi Desai generously shares her firsthand impressions of data-analytics work in the healthcare sector, and dispels some common misconceptions along the way.