Celebrating our first anniversary of Data Science at Microsoft
What we’ve learned this year — and where to go next
One year ago, on January 9, 2020, members of the Customer Growth Analytics team at Microsoft launched this online publication on Medium: Data Science at Microsoft. Our objectives were to share our data science best practices, discuss the value of our work, show our impact on the business, and connect with the broader data science community. These objectives remain the same today. In these ways, we’ve wanted to use the social journalism platform enabled by Medium to tell the story of Microsoft data science, and share it with business decision-makers, data science practitioners, customers, and partners.
One year later, we’ve published 40 articles — nearly one per week — on a variety of topics related to data science, in the areas of data science methods, data visualization, data engineering, organization, professional development, and people. We’re approaching 1,000 followers and our stories have garnered 50,000 views.
What have we learned about our readership during this time? Articles on data science methodology — cutting edge ones like causal inference and foundational ones like calculating customer lifetime value — have done very well, suggesting deep interest in the nuts and bolts of doing data science work. Writing about data engineering and what we’ve learned about it along the way has also found a wide audience, as have articles on how to think about data science as a discipline and as it relates to the larger organization. Articles on data visualization have received a warm welcome, too.
I was particularly gratified by the response to our article by Alex Blanton on building a machine learning and data science community at Microsoft, which suggested a hunger for connection during a year that many of us have been physically and socially isolated from colleagues. This also marked a key turning point for us as we started hearing from data scientists across Microsoft who expressed interest in adding their voices to our online publication, which we envisioned as encompassing all of Microsoft from the start.
As we prepare to begin our second year of this online publication, and as you’ve had a chance to see the range of articles and topics we’ve published, we would like to extend an invitation to you to compare your interests to ours. What would you like to see us cover more of? Less of? What would make Data Science at Microsoft — “DS@M,” as we refer to it internally — more interesting and relevant to you? I invite you to leave your comments below.
Whether you’re a data scientist, machine learning scientist, data engineer, customer, partner, business decision-maker, student, or other interested party, here’s to a great new year together in 2021, both for DS@M and our professional interests!
Casey Doyle is managing editor of Data Science at Microsoft.
