Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science

Today, industry experts participate in a discussion around analytics in the Fast-Moving Consumer Goods Space (FMCG). We open with a discussion of how millennial preferences have completely changed the FMCG market. Millennials are not typically drawn to one big brand; rather, they are more drawn to hyper localization; everyone wants a personalized product. Additionally, 40% of Millennials check online before even going into a store. All of this has significant implications for the FMCG field. Strategies will need to be developed to understand what people want before it reaches the market. We will see much more localized and customer-led strategies. Some easy to implement areas where we will undoubtedly see changes are: promotional spin, customer segmentation, and industry forecasting. Next, our guests talk about analytic capabilities. We are moving to do fewer things better because shoppers are expecting personalization, but businesses have to continue to be mindful of scale. There are many opportunities for retailers who are hoping to shift to a more centralized model; however, this is only possible if you have reliable data analytics, which enables you to implement things like automatic ordering and work few skews harder. Right now, our biggest challenge in analytic capabilities is how to tie all the data and tools together; we have tools for manufacturing, customer interest etc., but nothing that really ties all those insights together. The next step is to find ways to use advanced data on consumer opportunities at a localized level without losing the power of a company’s scale actually to bring things to the market. We wrap up the conversation with a discussion on promotional effectiveness. Here, the clunky companies are really at a disadvantage. They need to become more nimble and agile but hold the scale that makes them so profitable. Looking ahead, it's clear that purchasing behaviors will change; everyone will shop online. We need to get sophisticated and to the point where we can use promotional analytics to capture metrics like when are people shopping online the most and when are they really spending money. Enjoy the show! We speak about: [02:25] Introduction to Analytics in the FMCG Space [9:45] Key Learnings in Analytics Capabilities [19:30] Opportunities for Retailers [42:00] Data Analytics and Promotional Effectiveness Quotes: “Data is great, but only if you know what to do with it.” “The data assumes that consumers are rational, I assure you, they are not!” In promotional analysis, the art has to meet the science.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Today Felipe gives us a brief but holistic introduction into Data Science. We discuss myths, Felipe’s journey into the data science world, and demystify some of the field's elements. When Felipe started his career, he did not know anything about data science but found himself in the area of machine learning at the Australia New Zealand Banking Group (ANZ). Eventually, Felipe found himself pioneering the first data-driven strategy at ANZ. We learn that one of the biggest myths about data science is the fear that AI will eventually replace humans. Dispelling this myth is possible when we develop a wider understanding of what machine learning actually can and cannot do. First, we need to understand how machine learning works. We learn that machine learning updates the foundational data science process of input (data), algorithm (instructions), and output. Instead, it takes the job of developing the instructions, algorithm, or recipe off of the data scientist. Instead, an algorithm is created based on the data and feedback that is given to the machine. Felipe then dives into an explanation of the two basic types of algorithms, classification, and regression algorithms. Classification algorithms organize categories, and regressions deal with the likelihood of outcomes by shooting out a number from 0 to 1. Felipe spends some time breaking down concepts like AI and decision trees and shares some history of the development of algorithms. Bias data and the importance of understanding how algorithms can be biased are discussed. The power of the decision-making capacity of humans working with machines and data is highlighted. Felipe sees the potential of marrying human judgment and experience with algorithms and data as a game-changer in many areas including the medical field. We close with a Q&A and resources for people hoping to get started in data science, including programs that equip you with the skills and knowledge to get started in the field and include a mentorship program. Enjoy the show! We speak about: [01:25] About Felipe [04:55] What Can Data Science Do & How Does It Work? [17:00] Algorithms [32:00] Key Terms and Decision Trees [46:00] Coupling Machine Learning and Humans [60:00] Q&A and Resources To Get Started Quotes: “In today’s world, everyone should know how to read and write, in tomorrow’s world, everyone should know how algorithms work” “Machine learning can supplement thinking, show you things you haven’t considered, and give you a better perspective that allows you to make better decisions”. “Are humans going to be replaced? Will it always be a combination? That’s up to you.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

In this episode, Felipe reflects on the past year with Data Futurology. One of the key themes is organizational outcomes. There is a difference between what people find interesting in the data science role and what organizations need from their data scientists. Organizations want to make better decisions based on data. However, data scientists like playing with shiny new toys and using the latest technology. People think about leaving their jobs because it feels like they have used all the techniques that companies have to offer. Mainly, people want to collect algorithms. However, leaders say they have made an impact without knowing all of the algorithms or cutting edge methods. It can be boring to focus on the same algorithms. Organizations need to focus on creating value by solving business problems. If you focus your efforts on solving traditional business problems with new approaches, it’s like a musician learning how to play instruments better. Whereas, data scientists want to learn how to play lots of different instruments. Learning the ins and outs of one algorithm will unlock various opportunities to create value for the organization. Plus, having a more in-depth understanding will allow for more creative applications. You don’t need more data or computing power; you need to be smarter with how you approach problems. Aim to be outcomes-driven and be better at using traditional tools. “I fear not the man who has practiced 10,000 kicks once, but I fear the man who has practiced one kick 10,000 times.” -Bruce Lee Enjoy the show! We speak about: [04:30] Introduction to organizational outcomes [08:25] Creating value by solving business problems [15:15] Change the way you approach problems Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Irina is Chief Product Officer for Kinetica. Irina has over a decade of product management experience across a variety of sectors, including enterprise software, networking, hardware, IoT, SaaS, and Cloud. Irina joins Kinetica from Riverbed Technology, where she held a variety of leadership roles including Vice President of Products and Strategy for the Service Provider Business and Vice President of Product Management for Steelhead, Riverbed's flagship product. Enjoy the show! We speak about: [00:30] About Irina Farooq [01:20] How did you get started in data? [02:50] Why did you switch from engineering to product management? [03:50] What did your career look like after switching to product management? [04:35] How did you learn the craft of being a product manager? [06:20] What type of products were you working on at the time? [08:10] What kept you going during the tough times? [11:25] What has your career looked like after Oracle? [16:00] What challenges did you help customers overcome? [18:15] How do the improvements work? [19:50] What is feature engineering? [24:15] How do you manage the lifecycle of operational models? [30:45] What type of information do you keep track of? [31:20] About Kinetica [34:00] What does a day on the job look like? [35:00] What are your biggest challenges? [37:00] Why did Kinetica decide to go to Australia? [39:30] How does tiered storage work? [42:15] How much has the platform changed? [44:45] What are you most proud of? [49:00] What do you think about challenges in the data space? [50:00] What is a piece of advice for the listeners? Resources: Irina’s LinkedIn: https://www.linkedin.com/in/irinafarooq/ Kinetica: https://www.kinetica.com Kinetica on Twitter: https://twitter.com/Kineticahq Kinetica on LinkedIn: https://www.linkedin.com/company/kinetica/ Kinetica on YouTube: https://www.youtube.com/kineticadb/ Quotes: “Learning and self-improvement kept me going during the tough times.” “The biggest transformation has been being deployed in some of the world’s largest enterprises.” “Figure out what your superpowers are and focus on those things.” “You can’t just fit the mold with everything.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

During this episode, Felipe talks about how to find and double down on your strengths. Instead of working on your weaknesses, Felipe says that we should do more of what we are already good at. Spend more time thinking about the things that you are talented in. Felipe is good at going and helping teams. Eventually, he makes himself redundant by doing these three things: 1. Sharing knowledge openly, quickly, and effectively. 2. Create a system that is self-organizing and self-sustaining. 3. Helping individuals learn and improve as soon as possible. When working with individuals, find out what their strengths and weaknesses are. Also, learn where they want to go and what they want to know. Then, you will need to understand how they can learn and the ways they can get better. For example, Felipe caught up with a data scientist; he was working on learning his perceived strengths and weaknesses. However, the skills he was working on didn’t line up with a long-term vision for his career. That’s why it’s essential to have a vision in mind. Enjoy the show! We speak about: [01:30] How Felipe makes himself redundant [04:40] Working with individuals in the workplace Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Terence is a data scientist, software engineer and bioinformatician with over a 15 years of experience working on software solutions to big data related problems in industries as diverse as finance & investment banking, construction, manufacturing, healthcare and retail sectors. Terence is the CEO of Growing Data, a Melbourne based Data Science and Data Engineering consultancy, working with clients such as ANZ, CSL, Metricon and the Victorian Government. Enjoy the show! We speak about: [00:30] About Terence Siganakis [02:30] Marketing Growing Data [04:50] Working with the government [06:30] The numbers behind machine learning [10:00] Why does governance have negative connotations? [11:20] How do you minimize the work upfront? [15:55] How are you tackling big problems? [19:15] How do you stay engaged? [20:40] The way organizations interact with data [22:40] How does Growing Data work? [25:00] Data in the health industry [31:00] Working in finance, health, and construction [34:05] Driving innovation Resources: Terence’s LinkedIn: https://www.linkedin.com/in/terencesiganakis/ Growing Data: https://growingdata.com.au Quotes: “Think about the business outcome.” “Have confidence that what you are building is going to be production-ready when it reaches its targets.” “No one wants to come up with a solution and have nothing happen with it.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

During this special episode, Felipe gives a presentation on what data science can do for business. The CEOs in the audience were from all sorts of industries with companies of different sizes in various stages. Business leaders can use AI to offer new solutions to their customers. Felipe explains machine learning – humans give the input and the output. The machine will do the calculations in-between the input and the output. We can automate a lot of processes using machine learning – it can help us make better decisions, understand human bias, and help us create better businesses. Very few algorithms are 99% accurate. However, they will allow your business to automate decision making and give more insight to make better decisions. Next, Felipe talks about building a data science team. Once you pay people enough, they care about three things: autonomy, mastery, and purpose. Companies are focusing on creating data science products. Most of the value is designed this way; it is very enticing for a data scientist to work in production. Every process that you automate is creating a lot of data that you should be capturing. The ways you can get data is by buying it, scraping it from the web, or collecting it within your organization. Getting information from a different division of your business will improve what you can do internally. Later, Felipe speaks about design-thinking. Find problems that your customer cares so deeply about that they have hacked together a solution. When you find something they care about that has business value, it’s a great place to start. Stay tuned as Felipe takes questions from the audience.  Enjoy the show!  We speak about:  [01:15] About Felipe  [03:30] How does machine learning work?  [07:30] The algorithm will provide insight  [09:30] Building a data science team  [13:30] How to create data  [15:20] The difference between lake, warehouse, and swamp  [18:15] About design-thinking  [20:55] The key points  [22:00] Audience questions  Resources:  Idio: https://idio.ai  Quotes:  “When working with data scientists, get them away from thinking everything needs to be perfect.”  “Machine learning can be used for automation and to make better decisions.”  “Data scientists need to think about the outcome instead of research.”  Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

During this special episode, Felipe gives a presentation on what data science can do for business. The CEOs in the audience were from all sorts of industries with companies of different sizes in various stages. Business leaders can use AI to offer new solutions to their customers. Felipe explains machine learning – humans give the input and the output. The machine will do the calculations in-between the input and the output. We can automate a lot of processes using machine learning – it can help us make better decisions, understand human bias, and help us create better businesses. Very few algorithms are 99% accurate. However, they will allow your business to automate decision making and give more insight to make better decisions. Next, Felipe talks about building a data science team. Once you pay people enough, they care about three things: autonomy, mastery, and purpose. Companies are focusing on creating data science products. Most of the value is designed this way; it is very enticing for a data scientist to work in production. Every process that you automate is creating a lot of data that you should be capturing. The ways you can get data is by buying it, scraping it from the web, or collecting it within your organization. Getting information from a different division of your business will improve what you can do internally. Later, Felipe speaks about design-thinking. Find problems that your customer cares so deeply about that they have hacked together a solution. When you find something they care about that has business value, it’s a great place to start. Stay tuned as Felipe takes questions from the audience. Enjoy the show! We speak about: [01:15] About Felipe [03:30] How does machine learning work? [07:30] The algorithm will provide insight [09:30] Building a data science team [13:30] How to create data [15:20] The difference between lake, warehouse, and swamp [18:15] About design-thinking [20:55] The key points [22:00] Audience questions Resources: Idio: https://idio.ai Quotes: “When working with data scientists, get them away from thinking everything needs to be perfect.” “Machine learning can be used for automation and to make better decisions.” “Data scientists need to think about the outcome instead of research.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show! --- Send in a voice message: https://anchor.fm/datafuturology/message

Leigh McCormack is a thought leader with 10+ years of experience in developing and applying analytical solutions to complex healthcare problems. She has a deep understanding of data science concepts, methods, and technologies and how to appropriately apply each to accurately and creatively meet objectives. Leigh also has experience building analytic and technical teams from their genesis, through organizational design, and into maturation to the point of demonstrable business value. Leigh is the Chief Executive Officer of Base Camp, a healthcare analytics platform that leverages geospatial analytics, natural language processing, and machine learning to curate actionable social determinant of health insights. Enjoy the show! We speak about: [01:00] How Leigh got started in data [05:00] What data did you look at in clinical trials? [06:00] How can healthcare data be used and reused? [08:30] What type of analytics did you look at in the health care industry? [09:40] How detailed can you go into your findings from the data? [12:20] Were you able to measure health outcomes? [14:15] How was your journey advancing in the company? [16:00] Did your leaders see the importance of data? [20:10] How do you go on a data journey with your team? [22:00] Where else has your career taken you? [24:25] Do you need to sell the social side of data to organizations? [25:55] What type of projects have you been working on this past year? [27:40] How have career transitions been for you? [29:30] What are your other positions, and how do you balance your time? [33:30] Where does your drive come from? [35:40] How do you balance family life and work? [36:40] How did you come up with the idea to start your own company? [39:20] What part of your career set you up to tackle your startup challenges? [40:45] How do you spend your time at work? [42:11] What is a piece of advice you would give our listeners? Resources: Leigh’s LinkedIn: https://www.linkedin.com/in/leigh-mccormack-939a3222/ Base Camp Health: https://basecamp-health.com/ ChaTech: https://chatechcouncil.org/ Women in Analytics: https://womeninanalytics.com/ Quotes: “Healthcare organizations don’t understand the amount of data that they are sitting on.” “Not only do I have to live inside my data science framework, but now I have to master my marketing framework and a sales framework.” “There is something new every day in data science and artificial intelligence.” “Don’t stay in your lane.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

During this special episode, Felipe joins a panel at the Australian Taxation Office. Felipe speaks on four main topics: Improvements in the data industry. Felipe’s views on privacy. Quantum computing and how it will affect machine learning. New developments on AI and how they are impacting jobs. So much of the analytic work we do is to benefit the organization. How do you also ensure data analytics are helping the customer? It needs to be done in a way that is presenting meaningful insight for the individual. For instance, car technology today comes with a range of sensors and cameras that are making decisions. However, this data isn’t being collected and reported back to the customer. Grocery stores are also collecting data and using it to make predictions. For example, stores know when their consumers will need to buy toilet paper. The stores should be sending a reminder to their consumers by reusing the data they already have. Then, Felipe discusses ethics in artificial intelligence. Algorithms are consistently being deemed racist and sexist. We need to realize that the algorithm only learns the bias because the bias is in the data. When we find these errors, we can have tough conversations and improve the algorithms. Later, Felipe talks about how AI is impacting jobs. For instance, AI is now creating custom videos and articles for popular news websites. On one side of the argument, we are going to have a much more efficient economy. While on the other hand, many people say we are going to lose jobs. Felipe says that most jobs will be enhanced by AI instead of being replaced by AI. Enjoy the show! We speak about: [02:55] Making data analytics benefit the customer [11:30] Ethics in artificial intelligence [14:20] Felipe’s views on privacy [16:30] Quantum computing and how it will affect machine learning [19:00] How AI is impacting jobs Resources: ATO: https://www.ato.gov.au Quotes: “The same data that is prepared for the organization can be taken to benefit the consumer.” “The data is biased because it is a representation of our world.” “I think that the discussion around privacy heightens when we move it away from value.” “Jobs will be enhanced by AI, not replaced by AI.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

During this special episode, Felipe speaks at the IAPA National Conference. His presentation focuses on making analytics matter for your customers. More specifically, Felipe speaks on these topics: About organizations making a mindset shift. How analytics professionals can leverage the work they do. The ways we can add value to the end customer. Many companies claim they put customers first, but how do they show it? Companies have heaps of data on their customers. The next wave of companies that do great will actually show customers that they care about them. There are three simple ways to use analytics for your customers: Benchmarking. For instance, when a student gets a test back. What percentage of students did better them? Benchmarking is often overlooked, yet it can provide excellent value to the customer. Predictions and forecasts. We have loads of data on our customers to benefit the business. However, automated tools can redirect the data and use it for the benefit of the customer. Key drivers. Everyone wants to be better. We can give our customers feedback on how they can be better and achieve the goals that they have. Felipe uses grocery stores as his first example of how to implement these three steps. If the app sees you are buying pasta and sauce, they can offer their customer free garlic bread as a gift from the store. It’s a personalized and unexpected gift. The algorithms will also know when their customers are going to need toilet paper. This information is valuable to the company. It can be valuable to the customer because they can send a reminder to the consumer’s app. What do customers want? They want some perspective in their lives. What’s something about the customer you can inform them about that they don’t already know? Stay tuned as the audience asks questions to Felipe. Enjoy the show! We speak about: [01:40] About Felipe [04:10] Developing a relationship with your customer [06:30] Three ways to use analytics for your customer [12:50] Grocery store example [15:50] Car example [20:55] Business owners can also use analytics [24:30] What do the customers want? [27:15] Questions from the audience Resources: IAPA: https://www.iapa.org.au/advancing-analytics Quotes: “Five to seven percent of the data that is being captured is actually getting used.” “We can get more intimate with our services once we focus our value on the customer.” “Start with the data that you already have from the customers that you already have.” “There is a risk of being creepy when you have too much data on someone.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Barrett Hasseldine has held several leadership roles within the field of Data Science / Analytics. With a BSc majoring in Mathematics and an MBA, he is passionate about bringing mathematics and business closer together. In particular, he loves converting business problems to math problems, guiding analysts to solve the math, then converting the mathematical solution into a set of business actions that drive quantifiable business value. During his career, he has delivered analytic solutions in the domains of Credit, Fraud, Marketing, Politics, and Operations. Enjoy the show! We speak about: [00:30] About Barrett Hasseldine [01:20] How did you get started in the world of data? [02:55] Why did you pick operations research? [08:55] Do you find that people are thinking about business decisions affecting the model? [10:30] When were you able to see business problems in the math problems? [15:20] How do you turn the work environment into a positive feedback loop? [18:30] How did the opportunity come for you to step into management? [21:55] What would you change about your management techniques now? [25:00] How are you open to feedback? [26:45] How do you bring feedback out from people? [28:40] What do you think about imposture syndrome? [29:25] How did your career evolve after becoming a manager? [33:55] What would have made you better prepared for management? [39:30] What does the process look like when creating a new product? [42:00] How do you work with other teams? [42:50] How do you measure the demand for a new product? [49:35] How have your career goals changed? [52:00] What is a piece of advice you have for the listeners? Resources: Barrett’s LinkedIn: https://www.linkedin.com/in/barrett-hasseldine/ Manager Tools Podcast: https://www.manager-tools.com/all-podcasts Quotes: “People don’t follow equations.” “You learn from the people that you’ve had as bosses in your past, and you learn from your own experience.” “I’ve always been a fan of continuous learning. I’m open to feedback and use it to change continually. “The absence of imposture syndrome is an issue.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Mary L. Gray is a Senior Principal Researcher at Microsoft Research as well as an E.J. Safra Center for Ethics Fellow and Berkman Klein Center for Internet and Society Faculty Affiliate at Harvard University. Mary also maintains a faculty position in the School of Informatics, Computing, and Engineering with affiliations in Anthropology and Gender Studies at Indiana University. Mary, an anthropologist and media scholar by training, focuses on how everyday uses of technologies transform people’s lives. Enjoy the show! We speak about: [00:30] About Mary L. Gray [04:25] What’s it like in the Microsoft Research Center? [06:25] What surprised you the most about researching with Microsoft? [08:40] Is your work focused mostly in the United States? [10:10] Is your previous work focused on the social side of technology? [14:40] What other interesting viewpoints did you learn during your research? [24:00] How are people’s work lives being shaped by AI? [35:30] How is automation going to affect the execution of algorithms in specialized fields? [42:40] How do you see AI evolving in different countries? Resources: Mary’s Website: https://marylgray.org Mary’s Twitter: https://twitter.com/marylgray Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass In Your Face: Stories from the Lives of Queer Youth, Queering the Countryside: New Directions in Rural Queer Studies Out in the Country: Youth, Media, and Queer Visibility in Rural America Quotes: “I love studying gender and sexuality because it is so intimate.” “If we are constantly interacting with each other, we can constantly transform into different senses of who we are.” “When you introduce new technologies, it is shaping conversations.” “The work of data science is a global project.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Scott is a firm believer in “making your data do the work,” and he has enlightened countless business executives to the value of proper data management by focusing on the strategic rationale and business alignment rather than technical implementation and system integration. Scott is more of the strategic WHY than the technical HOW. He has spent over two decades guiding Tech Brand owners to leverage their reference data and taxonomy assets. In a variety of strategic marketing, GTM, innovation, and consulting roles, Scott has worked with some of the world’s most iconic business data brands, including Dun & Bradstreet, Nielsen, Microsoft, Kantar, NPD as well as start-ups such as Qoints and Spiceworks. Enjoy the show! We speak about: [00:30] How Scott started in the world of data [04:30] How did you develop your engaging videos? [07:50] How have you seen data change over time? [11:30] What are people not understanding about MDM? [16:35] What are the classic pitfalls? [19:45] Is master data similar to data engineering? [21:00] Do people struggle to talk about data as an asset? [25:50] How are you having the best time in your career right now? [30:55] What’s the philosophy behind your content? [38:30] How did you land on the Data Whisperer and Meta Meta Consulting? Resources: Scott’s Website: http://metametaconsulting.com Scott’s YouTube: https://www.youtube.com/channel/UCVQ1YhjNqc77GVsb3Xs4tvw Scott’s Twitter: https://twitter.com/stdatawhisperer Scott’s LinkedIn: https://www.linkedin.com/in/scottmztaylor/ Quotes: “You need data management first before you do business intelligence.” “I’m the sous chef in the back, making sure we have the right ingredients.” “Do upon your data as you would have it do upon you.” “Master data is your most important data.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Emrah Gultekin is the co-founder and CEO of Chooch. Chooch AI is a complete visual AI platform with an API, a dashboard, and a mobile SDK. Combining computer vision training with machine learning, Chooch offers object recognition and facial authentication, with autonomous labeling, data collection, neural network selection, and more. Chooch is used in the media, advertising, banking, medical, and security industries. Enjoy the show! We speak about: [00:30] How Emrah started in the world of data [03:00] What is the inspiration behind your company? [05:00] How did you meet your co-founder? [06:45] How do you tackle disagreements with your co-founder? [08:00] Did you de-risk your life from the start-up? [11:00] About Emrah’s products [14:00] Case study examples [20:20] What makes Chooch different? [23:30] Do you have methods to prioritize your labeling? [30:40] What has surprised you the most about Chooch? [33:40] When did you decide to move to Silicon Valley? [34:30] What are you working on now? [36:15] Advice for the listeners Resources: Emrah’s LinkedIn: https://www.linkedin.com/in/emrah-gultekin-6123ab1/ Chooch: https://chooch.ai Quotes: “We automate the labeling process – that has been a key thing to scale.” “No data is perfect.” “We have to understand that bias is a natural state.” “The more you know about something, the more critical you will be.” Thank you to our sponsors: Fyrebox - Make Your Own Quiz! RMIT Online Master of Data Science Strategy and Leadership Gain the advanced strategic, leadership and data science capabilities required to influence executive leadership teams and deliver organisation-wide solutions. We are RUBIX. - one of Australia’s leading pure data consulting companies delivering project outcomes for some of the world’s leading brands. Visit online.rmit.edu.au for more information And as always, we appreciate your Reviews, Follows, Likes, Shares and Ratings. Thank you so much for listening. Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message