Data Science Leadership

BI and Data Science: Deliver Insights Through Embedded Analytics

2021-04-01 Daniel Petzold
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Continuing our series on self-service BI tools and code-first, open source data science, we explore embedded analytics and why they are a critical way for a data science team to deliver insights. We also discuss the unique needs that will be demanded of data science teams as they deliver insights that are secure, scalable, and flexible to multiple end user’s needs. Read more →

BI and Data Science: Collaboration Using Data Handoffs

2021-03-25 Sean Lopp
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One powerful approach for BI and data science collaboration is to share augmented data. In this post we cover the details of this technique and include an example where data scientists supply BI teams with forecasts and calculated columns. Read more →

BI and Data Science: Matching Approaches to Applications

2021-03-18 Lou Bajuk
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In this post, we’ll provide some insights from organizations who have used both types of tools and give some guidance about which you should use when. Read more →

BI and Open Source Data Science: Strengths and Challenges

2021-03-11 Lou Bajuk
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Continuing our series on self-service BI tools and code-friendly, open source data science, in this post we dive into the strengths and challenges of the different approaches. Read more →

BI and Data Science: The Best of Both Worlds

2021-03-04 Lou Bajuk
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In many large organizations, Business Intelligence and Data Science teams compete for budget and mindshare. By focusing on how data science can both augment and complement BI tools such as Tableau and PowerBI, these teams can unite on their common goal: delivering data-driven insights for better decision making. Read more →

RStudio: A Single Home for R and Python Data Science

2021-01-13 Lou Bajuk
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Over the past year, RStudio has invested in making our pro and open source offerings the best common home for both R- and Python-based Data Science. In this blog post, we explain why we support both Python and R, review these recent features, and encourage readers to attend our upcoming webinar. Read more →

Custom Google Analytics Dashboards with R: Building The Dashboard

2021-01-06 Carl Howe
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In this post, I continue our series on how to create your own Google Analytics dashboard in R. Using the data we downloaded in our last post, we’ll now create a simple dashboard showing blog page views over time and highlighting the most popular ones. Read more →

Exploring US COVID-19 Cases and Deaths

2020-12-23 Art Steinmetz
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Arthur Steinmetz, former Chairman, CEO, and President of OppenheimerFunds, uses R and the tidymodels package to explore the relationship between COVID-19 cases and mortality in the US. Read more →

Announcing the 2020 R Community Survey

2020-12-11 Carl Howe
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Want data about how people learn and use R? If so, please fill out our 3nd annual survey so that we can better understand today’s R community. We’ll publish the results in February 2021 as free and open source data. Read more →

Custom Google Analytics Dashboards with R: Downloading Data

2020-11-27 Carl Howe
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This article, the first of three, describes how to use a code-oriented data science approach to Google Analytics data from a blog. It creates custom views of raw GA data while hiding the complexity of the Google Analytics data and interface Read more →