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#76 Providing Financial Inclusion with Data Science, with Vishnu V Ram, VP of...

In this episode of DataFramed, we speak with Vishnu V Ram, VP of Data Science and Engineering at Credit Karma about how data science is being leveraged to increase financial inclusion.Throughout the...

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#77 Acing the Data Science Interview

As we enter the new year—it seems like we’re telescoping into the future of work. Companies embracing remote work, the great resignation putting pressure on teams to create more fulfilling...

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#78 How Data & Culture Unlock Digital Transformation

When most people hear digital transformation, it’s almost always the technology that first springs to mind.That’s a mistake.You can have the most sophisticated tech stack in the world, but if you don't...

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#79 Delivering Smarter Cities & Better Public Policy w/ Data

Throughout the middle east, efforts are underway to build smart cities from the ground up. But to create a modern, intelligently-designed city, you first need to lay a solid foundation. And the...

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#80 The Rise of Hybrid Jobs & the Future of Data Skills

It’s no secret that data science jobs are on the rise; but data skills across the board are rising — leading to what today’s guest calls “hybrid jobs.” This will require a paradigm shift in how we...

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#81 The Gradual Process of Building a Data Strategy

The data journey is a slow painstaking process. But knowing where to start and the areas to focus on can help any organization reach its goals faster. Today’s guest, Vijay Yadav, Director of...

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#82 Successful Digital Transformation Puts People First

When you hear the term-digital first, you might think about tech, platforms and data.  But digital transformation succeeds when you put people first. Gathering and analyzing data, then using it to...

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#83 Empowering the Modern Data Analyst

As data volumes grow and become ever-more complex, the role of the data analyst has never been more important. At the disposal of the modern data analyst, are tools that reduce time to insight, and...

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#84 Building High-Impact Data Teams at Capital One

Diversity in both skillset and experience are at the core of high-impact data teams, but how can you take your data team’s impact to the next level with subject matter expertise, attention to user...

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#85 Building Data Literacy at Starbucks

Data literacy at any organization takes buy-in from all levels of the company, from C-suite leaders all the way to customer-facing team members. But how do you get that buy-in, build a team around data...

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DataFramed Careers Series Special Announcement!

Introducing the DataFramed Careers Series. Over the past year hosting the DataFramed podcast, we've had the incredible privilege of having biweekly conversations with data leaders at the forefront of...

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[DataFramed Careers Series #1] Launching a Data Career in 2022

Today is the start of a four-day careers series covering breaking into data science in 2022. With so so much demand for data jobs today, we wanted to demystify the ins and outs of accelerating a career...

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[DataFramed Careers Series #2] What Makes a Great Data Science Portfolio

Today marks the second episode in our DataFramed Careers Series. In this series, we will interview a diverse range of thought leaders and experts on the different aspects of landing a data role in...

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[DataFramed Careers Series #3]: Accelerating Data Careers with Writing

Today is the third episode of this four-part DataFramed Careers series being published every day this week on building a career in data. We’ve heard from Nick Singh on the importance of portfolio...

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[DataFramed Careers Series #4]: Acing the Data Science Interview

Today marks the last episode of our four-part DataFramed Careers Series on breaking into a data career. We’ve heard from Sadie St Lawrence, Nick Singh, and Khuyen Tran on best practices to adopt to...

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#90 How Data Science is Transforming the Healthcare Industry

The healthcare industry presents a set of unique challenges for data science, including how to manage and work with sensitive patient information and accounting for the real-world impact of AI and...

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#91 Building a Holistic Data Science Function at New York Life Insurance

When many people talk about leading effective Data Science teams in large organizations, it’s easy for them to forget how much effort, intentionality, vision, and leadership are involved in the...

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#92 Democratizing Data in Large Enterprises

Democratizing data, and developing data culture in large enterprise organizations is an incredibly complex process that can seem overwhelming if you don’t know where to start. And today’s guest draws a...

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#93 How Data Science Drives Value for Finance Teams

Building data science functions has become tables takes for many organizations today. However, before data science functions were needed, the finance function acted as the insights layer for many...

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#94 How Data Science Enables Better Decisions at Merck

In pharmaceuticals, wrong decisions can not only cost a company revenue, but they can also cost people their lives. With stakes so high, it’s vital that pharmaceutical companies have robust systems and...

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#95 How to Build a Data Science Team from Scratch

While leading a mature data science function is a challenge in its own right, building one from scratch at an organization can be just as, if not even more, difficult. As a data leader, you need to...

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GPT-3 and our AI-Powered Future

In 2020, OpenAI launched GPT-3, a large language AI model that is demonstrating the potential to radically change how we interact with software, and open up a completely new paradigm for cognitive...

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#97 How Salesforce Created a High-Impact Data Science Organization

Anjali Samani, Director of Data Science & Data Intelligence at Salesforce, joins the show to discuss what it takes to become a mature data organization and how to build an impactful, diverse data...

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#98 Interpretable Machine Learning

One of the biggest challenges facing the adoption of machine learning and AI in Data Science is understanding, interpreting, and explaining models and their outcomes to produce higher certainty,...

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#99 Post-Deployment Data Science

Many machine learning practitioners dedicate most of their attention to creating and deploying models that solve business problems. However, what happens post-deployment? And how should data teams go...

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#100 Embedded Machine Learning on Edge Devices

Machine learning models are often thought to be mainly utilized by large tech companies that run large and powerful models to accomplish a wide array of tasks. However, machine learning models are...

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#101 How Real-Time Data Accelerates Business Outcomes

Most companies experience the same pain point when working with data: it takes too long to get the right data to the right people. This creates a huge opportunity for data scientists to find innovative...

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#102 How an Always-Learning Culture Drives Innovation at Shopify

Many times, data scientists can fall into the trap of resume-driven development. As in, learning the shiniest, most advanced technique available to them in an attempt to solve a business problem....

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Announcing Data Literacy Month

Taking inspiration from International Literacy Day on September 8, DataCamp is dedicating the whole month of September to raising awareness about Data Literacy. Throughout the month, we are featuring...

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#103 How Data Literacy Skills Help You Succeed

Data Literacy is increasingly becoming a skill that every role needs to have, regardless of whether their role a data-oriented or not. No one knows this better than Jordan Morrow, who is known as the...

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#104 How the Data Community Can Accelerate Your Data Career

Data Literacy may be an important skill for everyone to have, but the level of need is always unique to each individual. Some may need advanced technical skills in machine learning algorithms, while...

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#105 What Data Visualization Means for Data Literacy

Understanding and interpreting data visualizations are one of the most important aspects of data literacy. When done well, data visualization ensures that stakeholders can quickly take away critical...

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#106 How CBRE is Increasing Data Literacy for Over 3,000 Employees

Throughout data literacy month, we’ve shined a light on the importance of data literacy skills and how it impacts individuals and organizations. Equally as important is how to actually approach...

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#107 The Deep Learning Revolution in Space Science

We have had many guests on the show to discuss how different industries leverage data science to transform the way they do business, but arguably one of the most important applications of data science...

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#117 Successful Data & Analytics in the Insurance Industry

The insurance industry thrives on data from utilizing data and analytics to determine policy rates for customers to working with relevant partners in the industry to improve their products and...

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#118 How Power BI Empowers Collaboration

In programming, collaboration and experimentation can be very stressful, since sharing code and making it visible to others can be tedious, time-consuming, and nerve-wracking.Tools like Power BI are...

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#119 Data-Driven Thinking for the Everyday Life

Just as data is used to help businesses determine new directions, set new goals, and measure progress, data can be used in everyday life to help people do the same as they seek to improve themselves.As...

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#120 Data Trends & Predictions for 2023

In 2022, we saw significant developments in the field of data. From the emergence of generative AI to the growth of low-code data tools and AI assistants—these advancements signal an upcoming paradigm...

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#121 — ChatGPT and How Generative AI is Augmenting Workflows

Throughout 2022, there was an explosion in generative AI for images and text. GPT-3, DALLE-2, pointed us towards an AI-driven future. Recently, ChatGPT has taken the (data) world by storm — prompting...

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#122 How Organizations Can Bridge the Data Literacy Gap

Something we talk about alot on DataFramed is the importance of data literacy and data skills — and how they help both individuals and organizations succeed with data. Oftentimes, when organizations...

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#123 Why We Need More Data Empathy

When working with data, it’s easy for us to think about it as a mechanistic process, where data comes in and products come out. But as we’ve explored throughout the show, succeeding in data, whether...

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