Lou Bajuk

Lou is a passionate advocate for data science software, and has had many years of experience in a variety of leadership roles in large and small software companies, including product marketing, product management, engineering and customer success. In his spare time, his interests include enjoying the Pacific Northwest outdoors, books, science advocacy, great food and theater.


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Announcing RStudio on Amazon SageMaker

November 2, 2021

RStudio is excited to announce the release of RStudio on Amazon SageMaker. Developed in collaboration with the Amazon SageMaker team, this release makes it easy for data scientists to use the full power of SageMaker for machine learning from their favorite data science workbench.

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The Advantages of Code-First Data Science

September 16, 2021

Three key attributes define Serious Data Science; open-source software, code-first development, and a centralized data science infrastructure. This approach has been successful at driving value and impact at hundreds of organizations. In this post, we will focus on the advantages of code-first data science.

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A CEO’s View of Open Source Data Science in the Enterprise

July 15, 2021

We recently sat down with Art Steinmetz, former CEO of OppenheimerFunds, to get his unique perspective on the value and viability of code-first, open source data science for the enterprise.

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Debunking the Myths of R vs. Python

June 15, 2021

Data science teams sometimes believe that they must standardize on R or Python for efficiency, at the cost of forcing individual data scientists to give up their preferred, most productive language. RStudio’s professional products provide the best single home for R and Python data science, so teams can optimize the impact their team has, not the language they use.

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Code-First Data Science for the Enterprise

May 12, 2021

While you may already be a practitioner of code-first data science with R or Python, chances are you work within a larger organization with many analytic tools. In this post, we give you some advice on navigating this landscape, and convincing others in your organization of the value of code-first data science.

Webinars

Why Your Enterprise Needs Code-First Data Science

April 27, 2021

A modern enterprise needs code-first data science. Navigating this landscape, and convincing others in your organization of the value of open source data science, can be challenging.

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BI and Data Science: Matching Approaches to Applications

March 18, 2021

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.

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BI and Open Source Data Science: Strengths and Challenges

March 11, 2021

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.

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BI and Data Science: The Best of Both Worlds

March 4, 2021

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.

Webinars

RStudio: A Single Home for R & Python

February 3, 2021

Many Data Science teams today are bilingual, leveraging both R and Python in their work. While both languages are tremendously powerful, teams frequently struggle to use them together.

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2020 at RStudio: A Year in Review

January 19, 2021

In this blog post, I take a look back at some of the many announcements, product releases, etc. that RStudio did in 2020. It was an exciting year, despite the challenges that 2020 presented to everyone, and we were pleased to continue to support and deliver value to the R and Python data science community.

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RStudio: A Single Home for R and Python Data Science

January 13, 2021

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.

Webinars

Why Data Science in the Cloud?

December 2, 2020

As business and organizational needs expand, a centralized ecosystem such as the cloud is needed to securely store and access data, conduct analyses, and share results.

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Why RStudio Focuses on Code-Based Data Science

November 17, 2020

Michael Lippis of The Outlook podcast recently interviewed RStudio's Lou Bajuk to discuss open source data science, support for R and Python, and how leaders are getting value from data science.

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Where Does RStudio Fit into Your Cloud Strategy?

November 12, 2020

Over the last few years, more companies have begun migrating their data science work to the cloud. As they do, they naturally want to bring along their favorite data science tools, including RStudio, R, and Python. In this blog post, we discuss the various ways RStudio products can be a part of that journey.

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RStudio Named Strong Performer in the Forrester Wave™: Notebook-Based Predictive Analytics and Machine Learning, Q3 2020

September 25, 2020

Read The Forrester Wave™: Notebook-Based Predictive Analytics and Machine Learning, Q3 2020 Report to learn why RStudio was named a Strong Performer by this independent research firm, and received the highest scores possible in the evaluation criteria of security, apps, open source and platform infrastructure.

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Do, Share, Teach, and Learn Data Science with RStudio Cloud

August 5, 2020

RStudio is proud to announce the general availability of RStudio Cloud, its cloud-based platform for doing, teaching, and learning data science. WIth RStudio Cloud, there's nothing to configure and no dedicated hardware or installation required. Individual users, instructors, and students only need a browser.

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Interoperability: Getting the Most Out of Your Analytic Investments

July 15, 2020

No single platform meets all the analytic needs of every organization. To avoid productivity-sapping complexity and underutilized infrastructure, encourage Interoperability so that your data scientists can access everything they need from their native tools.

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Does your Data Science Team Deliver Durable Value?

June 24, 2020

Delivering persistent value over the long haul from your data science team requires reusability, reproducibility, and up-to-date insights, built on a sustainable platform.

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Is Your Data Science Team Agile?

June 9, 2020

Data science teams struggle to deliver results quickly. Agile techniques such as rapid iteration and continuous collaboration with stakeholders can help overcome these challenges.

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Is Your Data Science Credible Enough?

June 2, 2020

For Data Science to be applied, decision makers must trust and accept the insights. Your team needs the tools to find relevant insights, and to communicate these insights in a way that builds trust and understanding.

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Driving Real, Lasting Value with Serious Data Science

May 19, 2020

Driving lasting value in an organization with data science is critical but difficult. The truth is most projects fail. What’s the answer? Serious Data Science is credible, agile and durable.

Webinars

R & Python: A Data Science Love Story

January 22, 2020

In this webinar, you'll learn how to develop, collaborate, manage and share your data science work in R and Python.

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R vs. Python: What's the best language for Data Science?

December 17, 2019

We will briefly examine the debates over R vs. Python, and then share

Webinars

Why Data Science in the Cloud?

January 1, 0001

A joint webinar with RStudio and ProCogia

Webinars

Using R & Python to Augment Tableau

January 1, 0001

A Joint Webinar with Solita, an RStudio Full Service Partner