“Even if you don't drink one bit of the A.I. Kool-Aid and you're a senior expert practitioner in machine learning, when you're trying to start a new initiative at your corporation, you're still very liable to make this extremely prevalent mistake that leads to a lack of deployment. And the mistake is that we all, on some level, are fetishizing the technology.” -      Eric Siegel   In this episode of Data Chats, Chris Richardson interviews Eric Siegel, Ph.D., leading consultant and former Columbia University professor who makes machine learning understandable and captivating. He is also the founder of the Predictive Analytics World and Deep Learning World conference series, which has served more than 17,000 attendees since 2009.They discuss: How to use A.I. to improve your organization’s capabilities and performance Common mistakes business leaders make with understanding machine learning Why top data scientists fail to make successful models most of the time How operational changes lead to improved data analysis What separates a great organization from the rest when it comes to predictive analytics Necessity of socialization and buy-in to successfully implement predictive analysis  Ethical implications and risks of machine learning Continue Learning | Data Science for Business Leaders Data Science for Business Leaders shows you how to partner with data professionals to uncover business value, make informed decisions and solve problems. Learn More

“I encourage clients to do more automation, diagnostic, predictive or prescriptive work with their data. That's where the real value happens. Not in looking backward at lagging indicators.” - Douglas Laney   In this episode of Data Chats, Chris Richardson interviews Douglas Laney, author of Data Juice: 101 Stories of How Organizations Are Squeezing Value from Available Data Assets. Douglas is also an innovation fellow at West Monroe.   They discuss: How to generate economic value from data Why you should treat data like a business asset How to assess the value of data owned by your company What is inverted data monetization Thinking through the ethical considerations, legal aspects and unintended consequences of selling and using data before taking action Why we need more data managers and not just data analysts How to measure the financial value and business value of data Take Your Data Skills to the Next Level with Business-Driven Data Analysis This course teaches a proven, repeatable approach that you can leverage across data projects and toolsets to deliver timely data analysis with actionable insights. Learn More

This episode is from our latest Product Chat webinar >> watch the webinar Customer life value (CLV) is a key indicator for businesses to better understand long-term and financial viability. A high CLV translates into brand loyalty, increases in sales and recurring revenue from existing customers. So how do you determine the customer lifecycle in your organization to improve interaction? Learn strategies to evaluate and grow customer lifecycle value with Zach King, senior data scientist at GoDaddy. Zach will go in-depth on the importance of customer lifetime value, showcasing a framework to visually understand customer performance and drive long-term success.

“Businesses in the long term and people in the long term are better off strategically if they act in a way that people can trust,” — Kirsten Martin In this episode of Data Chats, Chris Richardson interviews Kirsten Martin about how to approach data from an ethical lens. Kirsten is the William P. and Hazel B. White Center Professor of Technology Ethics and a professor of IT, analytics, and operations in the Mendoza College of Business at the University of Notre Dame. Her new book is called Ethics of Data and Analytics and she is also the host of Tec Talks, a podcast about the impact of technology on humanity. They discuss: Where to find the latest information on ethics in data How to integrate ethics into business decisions involving data Future trends for regulation New ethical questions that data is provoking The questions data professionals can ask to help improve data projects and ensure the work is ethical Continued Learning Data Science for Business Leaders This course teaches you how to partner with data professionals to uncover business value, make informed decisions and solve problems. Learn More   Business-Driven Data AnalysisThis course teaches a proven, repeatable approach that you can leverage across data projects and toolsets to deliver timely data analysis with actionable insights. Learn More

“If something takes longer to automate than to actually do it then don't automate it. Because that's something that we see happening a lot, that analysis that happens maybe once every quarter gets automated. There's no point in that.” — Marco Szeidenleder   In this episode of Data Chats, host Chris Richardson interviews Marco Szeidenleder, managing partner at Pandata GmbH about the early stages of data projects and the importance of building a strong foundation for scalability.   They discuss: How to identify quality and trustworthy data consultants Looking for compatibility when deciding whether or not to switch databases or tools Leveraging data dashboards effectively with stories Why building data structures is an iterative process How to avoid wasting resources on data projects Businesses that benefit the most from machine learning Continue Learning | Data Science for Business Leaders Data Science for Business Leaders shows you how to partner with data professionals to uncover business value, make informed decisions and solve problems. Understand how business leaders and data practitioners contribute at each stage of data projects to drive results that have real impact on your organization Learn More

Looking to spruce up your resume and stand out in the STEM field?   This episode features our elite resume writing service, RiseSmart, to discuss the tips and tricks on writing a killer resume to get you noticed for your first or next data job. RiseSmart will review the key competencies you want to have before applying and how to make them pop on a resume. You will also learn how written branding materials open doors and help individuals.   This episode also covers how to: Get market-ready faster Generate more interview invitations Establish a competitive advantage Project an image as a good fit for target companies Shorten job searches Produce better job offers Receive higher starting salaries About our Partner: Randstand RiseSmart We empower organizations globally to excel by helping them unleash work-life possibilities for every employee throughout their employment journey. RiseSmart was founded in response to rapid workforce changes, talent mobility challenges, and the absolute necessity for companies to establish stellar employer brands. Since then, we have addressed the needs of organizations and their employees with innovations and a contemporary approach to career development and talent mobility. Through Randstad, our parent company, Randstad RiseSmart has expanded its offerings to more than 100 countries and 40 industries. We are now one of the world’s leading coaching and career transition firms.

“It's really in that communication piece is where things either succeed or fail, irrespective of all the hard work that happened up until that point.” —  Cole-Nussbaumer-Knaflic   In this episode of Data Chats, Chris Richardson interviews Cole-Nussbaumer-Knaflic Founder & CEO of Storytelling with Data and author of ****best-selling books Storytelling with Data: Let's Practice and Storytelling with Data: A Data Visualization Guide for Business Professionals.They discuss: The importance of answering “so what” when sharing data How to do a better job of defining the audience for the data story Tips for communicating data after all the analysis is done The ways organizations can support data teams learn how to share insights through storytelling Strategies to get more comfortable with storytelling with data Continued Learning Data Science for Business Leaders This course teaches you how to partner with data professionals to uncover business value, make informed decisions and solve problems. Learn More   Business-Driven Data Analysis This course teaches a proven, repeatable approach that you can leverage across data projects and toolsets to deliver timely data analysis with actionable insights. Learn More   Connect with Cole-Nussbaumer-Knaflic: Storytellingwithdata.com and follow her on LinkedIn or Twitter

“The first piece of advice I give people in the book is when you see a chart, don't assume that it's a picture that you can simply look at and quickly understand” - Alberto Cairo In this episode of Data Chats, Chris Richardson interviews Alberto Cairo author of How Charts Lie, about why charts intentionally or not can mislead people, and how companies can create smarter visualization choices.   They discuss: Why there is never neutral choices in data visualization Ethical considerations in visualization techniques How to assess whether or not mean, median or mode is appropriate Finding a balance between simplicity and complexity in visualization practices Continued Learning Data Science for Business Leaders This course teaches you how to partner with data professionals to uncover business value, make informed decisions and solve problems. Learn More   Business-Driven Data Analysis This course teaches a proven, repeatable approach that you can leverage across data projects and toolsets to deliver timely data analysis with actionable insights. Learn More

What does diversity, equity and inclusion really mean? And what does it mean for the world of STEM and those of us who are immersed in it? We’re committed to fostering a diverse community here at TDI and it’s important that marginalized voices are heard within our unique platform. With the launch of our newest Diversity, Equity & Inclusion Scholarships, we wanted to take a moment to show off our amazing alumni and lift the voices of those who may not always be prominently seen in the data world. Listen to our special ask me anything podcast as we focus on diversity, equity and inclusion in data with a panel of fantastic alumni who will tell us their unique perspectives and what it means to be part of the diverse revolution in STEM.

“I don't love statistics. I don't love economics. I love what economics and statistics can do for me.” - Charles Wheelan In this episode of Data Chats, Chris Richardson interviews Charles Wheelan, senior lecturer and policy fellow at the Rockefeller Center at Dartmouth College and author of several books, including Naked Statistics, Naked Economics and Naked Money.   They discuss: How to approach complicated topics like data and statistics when that’s not your area of expertise Examples of organizations using data brilliantly and examples of why data might fail Why persistence and investment are needed for successful quality data collection Why do we have to approach metrics cautiously to prevent distortion Find all of Charles resources at https://charleswheelan.com/   Continued Learning Data Science for Business Leaders This course teaches you how to partner with data professionals to uncover business value, make informed decisions and solve problems. Learn More   Business-Driven Data Analysis This course teaches a proven, repeatable approach that you can leverage across data projects and toolsets to deliver timely data analysis with actionable insights. Learn More