Data Chats Podcast

How to Become a Data-Guided Business

There is data and there is business. If we think of these in a concentric circles diagram, we often see them exist in their separate circles with some overlap. A data-guided business won’t be able to distinguish between data activities and business activities because it is embedded so closely together.

 

In this episode of Data Chats, Chris Richardson interviews Jason Foster, founder & CEO of Cynozure, host of the Hub & Spoken podcast, and co-author of Data Means Business: Level up your organisation to adapt, evolve and scale in an ever-changing world.

 

They discuss the process of becoming a data-guided business. And during the conversation, Jason explains the importance of

• Capturing the data your business is creating
• Identifying data signals
• Utilizing the iterative approach to business-driven data analysis
• Using collaboration as a way to create a data culture

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

Put Down the Pie Chart and Other Data Visualization Strategies

“It's a mistake to think that creating information from data is easy.” - Jose Berengueres

 

In this episode of Data Chats, Chris Richardson interviews Jose Berengueres. He is an associate professor in design thinking, data visualization and computer science at the United Arab Emirates University. He is also the author of Data Viz and Sketch Thinking

 

They discuss

• Why you should think beyond excel for creating graphs and charts
• The importance of the DIKW pyramid (Data, Information, Knowledge and Wisdom)
• How culture influences communication, specifically visualization decisions
• The problems with pie charts and color decisions

Recommended Resources
Tableau on Twitter
Email: jose@uaeu.ac.ae to receive a free PDF copy of the book Data Viz.
** Write DATAVIZ in the subject line of the email

 

Continue 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

Thinking about a data science career? Start here.

This episode was recorded during our recent Data Webinar.

Have you ever asked yourself any of these questions: What is data science? What does a data scientist even do? What’s the best way to launch a data science career? Skip the vague google search and get the answers you’re looking for from The Data Incubator's data science instructor and Data Chats guest host Rich Ott, who’s been in your shoes before. Through this podcast, Rich discusses:

• What data science means nowadays and what a data scientist really does
• Which skills you should know before you start
• What skills you’ll learn in the middle of your journey
• How to break into the data science field and land an interview
• What TDI brings to the table in all of this

How to Integrate Market Knowledge with Data-Driven Decision Making

Once you have data, it’s smooth sailing and straightforward decision-making, right? Not so fast. There are many ways data projects go wrong because data work requires human input and can have human errors.

In this episode of Data Chats, Chris Richardson interviews Ben Jones, founder & CEO of Data Literacy and author of Avoiding Data Pitfalls: How to Steer Clear of Common Blunders When Working With Data

They discuss:

• The relationship between the human realm and the data-realm
• Common data blunders and how to spot them
• How to effectively layer qualitative and quantitative data
• The gap between data and reality

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
Other Recommended Resources
Thinking Fast and Slow
Mind in Motion: How Action Shapes Thought

How to Avoid an AI Project Failure

When AI projects are successful, they provide enormous value through business insights. However, many AI projects fail—but why? In this episode of Data Chats, Chris Richardson interviews Harish Krishnamurthy about the mechanics of successful AI projects.

 

Harish Krishnamurthy is president at Sciata and has held leadership roles across P&L, sales, marketing and strategy during his tenure at IBM, Insight Enterprises and Spear Education.

They discuss:

• Early mistakes when companies begin data projects
• The ideal people to include on a data team
• 5 Reasons why AI Projects Fail
• Difference between AI projects and other data projects

Additional Resources:
Harish has created a library of resources to help data professionals begin leveraging AI effectively in their businesses:
Making the Leap from AI Investments to Business Results
Aligning IT and Business Strategy for Project Success
Using AI to Maximize Customer Lifetime Value
Transforming AI Insights into Actions
Designing AI Models to Extract Insights

 

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

 

 

 

Overcoming Imposter Syndrome in Data Science

This podcast was captured from a recent TDI webinar.

Everyone has it, no one thinks others have it and it seems like no one talks about it. What is it? Imposter syndrome.

The Data Incubator is committed to teaching the skills data professionals need to excel in their field, but that doesn’t end with just the technical skills. We teach students how to have confidence in all that they do and help them gain the personal tools to combat things like imposter syndrome.

Listen in to an all-star group of panelists as they talk about what imposter syndrome means, how to overcome the self-doubt it brings and some key tips in keeping those feelings at bay.

The Communication Skills Needed to Improve Data Projects

How can product professionals communicate better with data teams? How do data teams make sure they are answering the right questions for product teams?

 

Most organizations want to be more data-informed and data-driven, but communication is often the first hurdle to success. In this episode of Data Chats, host Chris Richardson interviews Kevin Hanegan, chief learning officer at Qlick, who shares practical strategies for communicating insights to stakeholders at all levels in the organization.Kevin discusses

• The value of systems thinking
• How to start small to gain momentum
• Ways to influence company culture when you’re not the CEO
• Reflecting on bias and flawed mental models

Connect with Kevin and find his book Turning Data Into Wisdom at kevinhanegan.com

 

Kevin is also chair of the advisory board of the Data Literacy Project

 

Learn how to translate data insights into business strategy in the course: Data Science for Business Leaders.

 

This course shows you how to partner with data professionals to uncover business value, make informed decisions and solve problems.

Enroll Today 

How Product Teams Should Tackle Responsible AI

Guest host Michael Li—the founder and president of The Data Incubator—sits down with Aishwarya Srinivasan, an Artificial Intelligence and Machine Learning Innovation Leader at IBM. Aishwarya works cross-functionally with the product team, data science team and sales to research AI use cases for clients at IBM Data & AI. In her role, she conducts discovery workshops and builds assets to showcase the business value of the technology. Aishwarya holds a postgraduate degree in data science from Columbia University.

The two data science experts discuss the importance of building responsible AI systems that aren't harmful to society, citing examples in the media. Aishwarya shares the responsibilities of roles like AI ethicists, UX researchers, data scientists and cybersecurity officers in upholding responsible AI standards. She also highlights the key issues organizations will have to grapple with as AI continues to evolve, and she shares key takeaways for leveraging machine learning and AI to create business value. Find links to resources shared in this episode:

• Trusted-AI/AIF360 via Github
• "Adversarial attacks in machine learning: What they are and how to stop them" via VentureBeat
• "What is Adversarial Machine Learning?" via Towards Data Science

How to be Proactive in Implementing Data Standards

The opportunity is the data; the challenge is the data. Everyone agrees that data is incredibly important, but how do you convert data into a usable resource?

During this conversation, the host Chris Richardson, senior instructional designer at Pragmatic Institute, interviews Verl Allen, the CEO of Claravine, who explains the importance of implementing data standards to prevent data quality problems.

Successful data projects require an organization-wide buy-in, so Verl describes how to craft teams that can collaborate. He also talks about the future of data, specifically the role of privacy and what businesses can do to be proactive in staying

TDI Alumni Stories: Peter Yu

Get a behind the scenes look at how leading data scientists land their dream roles and how their journey can lead to unexpected but interesting outcomes. Our host and data science guru Michael Li chats with TDI alumni Peter Yu about his data path, what led him to data science and what he learned along the way from being a 2015 graduate to working for McKinsey & Company to landing his dream job at Amazon Web Services (AWS).

Women in Data: Eugenie Packer, Senior Director of Development Systems & Analytics at Mount Sinai

(This episode was recorded during our recent data chat webinar)

Pragmatic Institute, with The Data Incubator, is excited to announce our “Women in Data” series. Eugenie Packer is the Senior Director of Development Systems and Analytics at Mount Sinai Health Systems and a graduate student in statistics, as well as a Data Advisory Board member at Pragmatic Institute. 

She has designed, developed, implemented and overseen fundraising systems, business intelligence data products, and analytics platforms at organizations of all sizes. However, data wasn’t always her primary focus: Eugenie brings a background in the arts and a Master of Fine Arts to her work. 

In a conversation led by Pragmatic Institute Marketing Manager Erin Tibeau, learn about:

• Eugenie’s experience at the intersection of data, information design and fine art
• How she’s made transitions and overcome obstacles as a woman in STEM
• What she’s learned in her career journey
• Her advice for others following a non-traditional path who want to make an impact in data

Filling Skill Gaps Crucial to Success in Data Roles

Data Chats host Chris Richardson sits down with Ahmad Namini, a Business Analytics Professor at Brandeis University and data analytics instructor at The Data Incubator who has held leadership roles across the financial investment management industry. The two discuss key data roles and how to create a culture where data professionals can develop business knowledge and gain those "missing" skills that are crucial to success.