Russell will go into details about the trials, tribulations, maths, complexities behind the scenes of building the tech.

Join us for a thorough discussion with data visualization expert Nick Desbarats. We will focus on creating charts and visualizing data.

Nick is a well-known instructor in the field of data & has taught many data professionals worldwide about visualizing data and designing dashboards.

In this episode, Nick explains how the choice of chart type affects how we understand data. He also discusses his recently published book, 'Practical Charts.'

Connect with Nick Desbarats :

🤝 Connect with Nick

🎒 Learn About Practical Reporting

📚 Purchase Practical Charts books

👍🏽 Leave your review and download the bonus:

🤖 Talk to AveryGPT for your data job hunt tips

🤝 Ace your data analyst interview with the interview simulator

📩 Get my weekly email with helpful data career tips

📊 Come to my next free “How to Land Your First Data Job” training

🏫 Check out my 10-week data analytics bootcamp

Timestamps: (03:42) - The Importance of Choosing the Right Chart (11:39) - The Ethics of Data Visualization (24:03) - Understanding Less Common Chart Types (33:02) - The Spray and Pray Chart Method

Connect with Avery:

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Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!

To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more

If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.

👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa

Learn statistics by analyzing professional basketball data! In this action-packed book, you’ll build your skills in exploratory data analysis by digging into the fascinating world of NBA games and player stats using the R language. Statistics Slam Dunk is an engaging how-to guide for statistical analysis with R. Each chapter contains an end-to-end data science or statistics project delving into NBA data and revealing real-world sporting insights. Written by a former basketball player turned business intelligence and analytics leader, you’ll get practical experience tidying, wrangling, exploring, testing, modeling, and otherwise analyzing data with the best and latest R packages and functions. In Statistics Slam Dunk you’ll develop a toolbox of R programming skills including: Reading and writing data Installing and loading packages Transforming, tidying, and wrangling data Applying best-in-class exploratory data analysis techniques Creating compelling visualizations Developing supervised and unsupervised machine learning algorithms Executing hypothesis tests, including t-tests and chi-square tests for independence Computing expected values, Gini coefficients, z-scores, and other measures If you’re looking to switch to R from another language, or trade base R for tidyverse functions, this book is the perfect training coach. Much more than a beginner’s guide, it teaches statistics and data science methods that have tons of use cases. And just like in the real world, you’ll get no clean pre-packaged data sets in Statistics Slam Dunk. You’ll take on the challenge of wrangling messy data to drill on the skills that will make you the star player on any data team. About the Technology Statistics Slam Dunk is a data science manual with a difference. Each chapter is a complete, self-contained statistics or data science project for you to work through—from importing data, to wrangling it, testing it, visualizing it, and modeling it. Throughout the book, you’ll work exclusively with NBA data sets and the R language, applying best-in-class statistics techniques to reveal fun and fascinating truths about the NBA. About the Book Is losing basketball games on purpose a rational strategy? Which hustle statistics have an impact on wins and losses? Does spending more on player salaries translate into a winning record? You’ll answer all these questions and more. Plus, R’s visualization capabilities shine through in the book’s 300 plots and charts, including Pareto charts, Sankey diagrams, Cleveland dot plots, and dendrograms. What's Inside Transforming, tidying, and wrangling data Applying best-in-class exploratory data analysis techniques Developing supervised and unsupervised machine learning algorithms Executing hypothesis tests and effect size tests About the Reader For readers who know basic statistics. No advanced knowledge of R—or basketball—required. About the Author Gary Sutton is a former basketball player who has built and led high-performing business intelligence and analytics organizations across multiple verticals. Quotes In this journey of exploration, every computer scientist will find a valuable ally in understanding the language of data. - Kim Lokøy, areo Transcends other R titles by revealing the hidden narratives that lie within the numbers. - Christian Sutton, Shell International Exploration and Production Seamlessly blending theory and practical insights, this book serves as an indispensable guide for those venturing into the field of data analytics. - Juan Delgado, Sodexo BRS

Summary

Monitoring and auditing IT systems for security events requires the ability to quickly analyze massive volumes of unstructured log data. The majority of products that are available either require too much effort to structure the logs, or aren't fast enough for interactive use cases. Cliff Crosland co-founded Scanner to provide fast querying of high scale log data for security auditing. In this episode he shares the story of how it got started, how it works, and how you can get started with it.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics. Trusted by teams of all sizes, including Comcast and Doordash, Starburst is a data lake analytics platform that delivers the adaptability and flexibility a lakehouse ecosystem promises. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data. Want to see Starburst in action? Go to dataengineeringpodcast.com/starburst and get $500 in credits to try Starburst Galaxy today, the easiest and fastest way to get started using Trino. Your host is Tobias Macey and today I'm interviewing Cliff Crosland about Scanner, a security data lake platform for analyzing security logs and identifying issues quickly and cost-effectively

Interview

Introduction How did you get involved in the area of data management? Can you describe what Scanner is and the story behind it?

What were the shortcomings of other tools that are available in the ecosystem?

What is Scanner explicitly not trying to solve for in the security space? (e.g. SIEM) A query engine is useless without data to analyze. What are the data acquisition paths/sources that you are designed to work with?- e.g. cloudtrail logs, app logs, etc.

What are some of the other sources of signal for security monitoring that would be valuable to incorporate or integrate with through Scanner?

Log data is notoriously messy, with no strictly defined format. How do you handle introspection and querying across loosely structured records that might span multiple sources and inconsistent labelling strategies? Can you describe the architecture of the Scanner platform?

What were the motivating constraints that led you to your current implementation? How have the design and goals of the product changed since you first started working on it?

Given the security oriented customer base that you are targeting, how do you address trust/network boundaries for compliance with regulatory/organizational policies? What are the personas of the end-users for Scanner?

How has that influenced the way that you think about the query formats, APIs, user experience etc. for the prroduct?

For teams who are working with Scanner can you describe how it fits into their workflow? What are the most interesting, innovative, or unexpected ways that you have seen Scanner used? What are the most interesting, unexpected, or challenging lessons that you have learned while working on Scanner? When is Scanner the wrong choice? What do you have planned for the future of Scanner?

Contact Info

LinkedIn

Parting Question

From your perspective, what is the biggest gap in the tooling or technology for data management today?

Closing Announcements

Thank you for listening! Don't forget to check out our other shows. Podcast.init covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning. Visit the site to subscribe to the show, sign up for the mailing list, and read the s

The Inside Economics team revels in the great economic numbers of the past week. The economy not only avoided a recession in 2023, but it ended the year enjoying robust GDP growth and tame inflation. But there are threats at the start of the new year, including a potential seizing up of the all-important Treasury bond market. Samim Ghamami of the SEC joins the podcast to discuss this threat, its causes and implications, and potential reforms to ensure it doesn’t upend financial markets and the economy.     Today’s guest Samim Ghamami is currently an economist at the U.S. Securities and Exchange Commission, where he works with the SEC senior management on the reform of the US Treasury market and several other capital market initiatives. Ghamami is also a senior researcher and an adjunct professor of finance at New York University, a senior researcher at UC Berkeley Center for Risk Management Research and the Department of Economics, and a senior advisor at SOFR Academy.  Ghamami has been a senior economist and a senior vice president at Goldman Sachs. He has been an adjunct associate professor of economics at Columbia University. Ghamami has also been an associate director and a senior economist at the U.S. Department of the Treasury, Office of Financial Research, and an economist at the Board of Governors of the Federal Reserve System. Ghamami’s work has broadly focused on the interplay of finance and macroeconomics, and on financial economics and quantitative finance. His work on banking, asset management, risk management, economic policy, financial stability, financial regulation, and central clearing has been presented and discussed at central banks. He has been an advisor to the Bank for International Settlements and worked as an expert with the Financial Stability Board on post-financial crisis reforms in 2016 and 2017. Ghamami also served on the National Science Foundation panel on Financial Mathematics in 2017 and 2018. Ghamami received his Ph.D. in Mathematical Finance and Operations Research from USC in 2009. His publications have appeared in different journals including Management Science, Journal of Applied Probability, Mathematics of Operations Research, Journal of Financial Intermediation, Journal of Credit Risk, Journal of Derivatives, Quantitative Finance, and Journal of Risk.   Follow Mark Zandi @MarkZandi, Cris deRitis @MiddleWayEcon, and Marisa DiNatale on LinkedIn for additional insight.

Questions or Comments, please email us at [email protected]. We would love to hear from you.    To stay informed and follow the insights of Moody's Analytics economists, visit Economic View.

Pelo quarto ano consecutivo, ainda acreditamos no IPO da Databricks e o Paulo Vasconcellos, já apostou todas as suas forças na venda da Stability AI, em 2024. E se você ouviu o episódio de Tendências, que gravamos no ano passado, acertamos quase todas previsões !!

Agora, chegou aquele momento do ano em que vamos tentar prever o que será tendência em Dados e AI para o ano de 2024! Vem com a gente pra esse papo com nossos community managers: Marlesson Santana , Pietro Oliveira e a bancada Data Hackers.

Façam suas apostas !! 

Lembrando que você pode encontrar todos os podcasts da comunidade Data Hackers no Spotify, iTunes, Google Podcast, Castbox e muitas outras plataformas. Caso queira, você também pode ouvir o episódio aqui no post mesmo!

[EMBEDAR_EPISODIO]

Conheça nosso convidado:

Pietro Oliveira Marlesson Santana

Nossa Bancada Data Hackers:

Monique Femme — Head of Community Management na Data Hackers Paulo Vasconcellos — Co-founder da Data Hackers e Principal Data Scientist na Hotmart. Gabriel Lages — Co-founder da Data Hackers e Data & Analytics Sr. Director na Hotmart.

Falamos no episódioLinks de referências:

Ouça o episódio de Tendências de 2023: https://medium.com/data-hackers/as-tend%C3%AAncias-para-dados-e-ai-em-2023-data-hackers-podcast-62-2dff6fdddb6e O Brasileiro com a IA mais baixada do Mundo — Data Hackers Podcast 70:https://medium.com/data-hackers/o-brasileiro-com-a-ia-mais-baixada-do-mundo-data-hackers-podcast-70-e13a8c66fbcd Matéria:É verdade? Museu do Louvre pega fogo e vídeo viraliza": https://www.folhavitoria.com.br/geral/noticia/01/2024/e-verdade-museu-do-louvre-pega-fogo-e-video-viraliza-assustador-viral Pika (AI Video): https://pika.art/login Eleições na Argentina: IA vira arma de campanha: https://olhardigital.com.br/2023/11/17/pro/ia-vira-arma-de-campanha-durante-eleicoes-na-argentina/ Cloud da Magalu: https://medium.com/data-hackers/magalu-cloud-por-dentro-da-primeira-cloud-brasileira-em-hiperescala-data-hackers-epis%C3%B3dio-79-3ca324ddf66e

In this episode, host Jason Foster explores the captivating world of LIV Golf with special guest Ross Antrobus, Vice President of Insight, Analytics, and Loyalty at LIV Golf. Together, they delve into the intriguing LIV story and brand, shedding light on the pivotal role insights play in shaping the newest brand in global golf and how insights drive decisions, influence commercial success, and foster loyalty among fans. Join the conversation to unravel the fascinating intersection of sports, data, and innovation, and explore the strategic moves that propel LIV Golf to success.

Tune in to this inspiring podcast episode filled with positive affirmations specially tailored for YOU, aspiring data professionals.

The episode seeks to motivate and mentally uplift listeners, encouraging you to embrace your potential in the field of data analysis.

Apart from helping deal with stress, anxiety, perfectionism, and imposter syndrome, let’s appreciate life's simple joys, promote confidence, and encourage problem-solving and personal growth.

🤝 Ace your data analyst interview with the interview simulator

📩 Get my weekly email with helpful data career tips

📊 Come to my next free “How to Land Your First Data Job” training

🏫 Check out my 10-week data analytics bootcamp

Connect with Avery:

📺 Subscribe on YouTube

🎙Listen to My Podcast

👔 Connect with me on LinkedIn

📸 Instagram

🎵 TikTok

Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!

To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more

If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.

👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa

Send us a text GenAI in Marketing.  Making Data Simple welcomes Michael Cohen, Chief Data Analytics Officer and ML and AI product and marketing expert in consumer data technologies.  Marketing Operations, Automated Decision Activation, Measurement and Analytics, Info Security and Privacy.  01:15 Meeting Michael Cohen03:33 The Plus Company08:06 Traditional Approaches to Marketing12:03 The Future of Marketing17:31 Data Augmentin's Role24:46 Data Inputs26:18 The AIOS Product31:39 Algorithms34:03 2 Min Plus Pitch41:13 Aggressive Innovation Roadmaps44:44 Next Marketing Disruption46:33 For FunLinkedIn: www.linkedin.com/in/macohen1/ Website: www.macohen.net, https://pluscompany.com Want to be featured as a guest on Making Data Simple?  Reach out to us at [email protected] and tell us why you should be next.  The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

The backlog of data requests keeps growing. The dashboards are looking like they might collapse under their own weight as they keep getting loaded with more and more data requested by the business. You're taking in requests from the business as efficiently as you can, but it just never ends, and it doesn't feel like you're delivering meaningful business impact. And then you see a Gartner report from a few years back that declares that only 20% of analytical insights deliver business outcomes! Why? WHY?!!! Moe, Julie, and Michael were joined by Kathleen Maley, VP of Analytics at Experian, to chat about the muscle memory of bad habits (analytically speaking), why she tells analysts to never say "Yes" when asked for data (but also why to never say "No," either), and much, much more! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Summary

Databases and analytics architectures have gone through several generational shifts. A substantial amount of the data that is being managed in these systems is related to customers and their interactions with an organization. In this episode Tasso Argyros, CEO of ActionIQ, gives a summary of the major epochs in database technologies and how he is applying the capabilities of cloud data warehouses to the challenge of building more comprehensive experiences for end-users through a modern customer data platform (CDP).

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics. Trusted by teams of all sizes, including Comcast and Doordash, Starburst is a data lake analytics platform that delivers the adaptability and flexibility a lakehouse ecosystem promises. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data. Want to see Starburst in action? Go to dataengineeringpodcast.com/starburst and get $500 in credits to try Starburst Galaxy today, the easiest and fastest way to get started using Trino. Data projects are notoriously complex. With multiple stakeholders to manage across varying backgrounds and toolchains even simple reports can become unwieldy to maintain. Miro is your single pane of glass where everyone can discover, track, and collaborate on your organization's data. I especially like the ability to combine your technical diagrams with data documentation and dependency mapping, allowing your data engineers and data consumers to communicate seamlessly about your projects. Find simplicity in your most complex projects with Miro. Your first three Miro boards are free when you sign up today at dataengineeringpodcast.com/miro. That’s three free boards at dataengineeringpodcast.com/miro. Your host is Tobias Macey and today I'm interviewing Tasso Argyros about the role of a customer data platform in the context of the modern data stack

Interview

Introduction How did you get involved in the area of data management? Can you describe what the role of the CDP is in the context of a businesses data ecosystem?

What are the core technical challenges associated with building and maintaining a CDP? What are the organizational/business factors that contribute to the complexity of these systems?

The early days of CDPs came with the promise of "Customer 360". Can you unpack that concept and how it has changed over the past ~5 years? Recent years have seen the adoption of reverse ETL, cloud data warehouses, and sophisticated product analytics suites. How has that changed the architectural approach to CDPs?

How have the architectural shifts changed the ways that organizations interact with their customer data?

How have the responsibilities shifted across different roles?

What are the governance policy and enforcement challenges that are added with the expansion of access and responsibility?

What are the most interesting, innovative, or unexpected ways that you have seen CDPs built/used? What are the most interesting, unexpected, or challenging lessons that you have learned while working on CDPs? When is a CDP the wrong choice? What do you have planned for the future of ActionIQ?

Contact Info

LinkedIn @Tasso on Twitter

Parting Question

From your perspective, what is the biggest gap in the tooling or technology for data management today?

Closing Announcements

Thank you for listening! Don't forget to check out our other shows. Podcast.init covers the Python language, its community, and the innovative ways it is being us

Robert Dietz, Chief Economist of the National Association of Home Builders, joins Mark Zandi, Marisa DiNatale, and Cristian deRitis to discuss the outlook for mortgage rates, home sales, and construction activity.  The team delves into the immigration and demographic trends affecting housing demand along with the 5 L's (Laws, Labor, Land, Lending, and Lumber) limiting homebuilding today.  Rob's quoting of Tolstoy catches everyone off guard while the wide-ranging discussion made it difficult for the team to come up with a clever podcast title so we took a cue from Friends.   Follow Mark Zandi @MarkZandi, Cris deRitis @MiddleWayEcon, and Marisa DiNatale on LinkedIn for additional insight.

Questions or Comments, please email us at [email protected]. We would love to hear from you.    To stay informed and follow the insights of Moody's Analytics economists, visit Economic View.

Você já deve ter ouvido, sobre o lançamento da nova Cloud Publica e Brasileira, que movimentou muitos rumores no mercado de tecnologia. E atendo a pedidos da comunidade, agora você tem a chance de conhecer as estratégias, e um pouco mais, sobre a Magalu Cloud.

Neste episódio do Data Hackers — a maior comunidade de AI e Data Science do Brasil-, chamamos o Vaner Vendramini — Field CTO na Magalu Cloud, para desmitificar tudo que está por de trás deste lançamento da primeira Cloud Brasileira em Hiperscala, da Magalu. 

Lembrando que você pode encontrar todos os podcasts da comunidade Data Hackers no Spotify, iTunes, Google Podcast, Castbox e muitas outras plataformas. Caso queira, você também pode ouvir o episódio aqui no post mesmo!

Conheça nosso convidado:

Vaner Vendramini — Field CTO na Magalu Cloud

Nossa Bancada Data Hackers:

Monique Femme — Head of Community Management na Data Hackers Allan Senne — Co-founder da Data Hackers e Co-Founder & CTO at Dadosfera.

Paulo Vasconcellos — Co-founder da Data Hackers e Principal Data Scientist na Hotmart. Gabriel Lages — Co-founder da Data Hackers e Data & Analytics Sr. Director na Hotmart.

Falamos no episódioLinks de referências:

Sobre o evento de lançamento da Magalu Cloud: https://www.magazineluiza.com.br/blog-da-lu/c/dl/dldc/magalu-cloud-a-nuvem-do-magazine-luiza/12434/ Cloud Alema citada pelo Vaner: https://www.stackit.de/en/ Estudo da McKinsey sobre o mercado de cloud Computing em 2030: https://www.mckinsey.com/br/our-insights/all-insights/computacao-em-nuvem-2030 Progressão do market sharing de Cloud, de 2018 até 2021, da digital cloud training: https://digitalcloud.training/comparison-of-aws-vs-azure-vs-google/ Página de parceiros da Magalu Cloud: https://magalu.cloud/solucoes/

Cookies were invented to help online shoppers, simply as an identifier so that online carts weren’t lost to the ether. Marketers quickly saw the power of using cookies for more than just maintaining session states, and moved to use them as part of their targeted advertising. Before we knew it, our online habits were being tracked, without our clear consent. The unregulated cookie-boom lasted until 2018 with the advent of GDPR and the CCPA. Since then marketers have been evolving their practices, looking for alternatives to cookie-tracking that will perform comparatively, and with the cookie being phased out in 2024, technologies like fingerprinting and new privacy-centric marketing strategies will play a huge role in how products meet users in the future.  Cory Munchbach has spent her career on the cutting edge of marketing technology and brings years working with Fortune 500 clients from various industries to BlueConic. Prior to BluConic, she was an analyst at Forrester Research where she covered business and consumer technology trends and the fast-moving marketing tech landscape. A sought-after speaker and industry voice, Cory’s work has been featured in Financial Times, Forbes, Raconteur, AdExchanger, The Drum, Venture Beat, Wired, AdAge, and Adweek. A life-long Bostonian, Cory has a bachelor’s degree in political science from Boston College and spends a considerable amount of her non-work hours on various volunteer and philanthropic initiatives in the greater Boston community.  In the episode, Richie and Cory cover successful marketing strategies and their use of data, the types of data used in marketing, how data is leveraged during different stages of the customer life cycle, the impact of privacy laws on data collection and marketing strategies, tips on how to use customer data while protecting privacy and adhering to regulations, the importance of data skills in marketing, the future of marketing analytics and much more. Links Mentioned in the Show: BlueConicMattel CreationsGoogle: Prepare for third-party cookie restrictionsData Clean Rooms[Course] Marketing Analytics for Business

In this episode of the Data Career Podcast, we include a variety of listener questions, shedding light on topics like the future of data engineering, requirements for becoming a data analyst, showcasing data cleaning proficiency in Excel, and securing data analyst internships.

Also discusses the significance of storytelling and views on Power BI versus Tableau & the impact of AI on data analysis roles.

Tune in now!

👍 Leave your review and download the bonus!

🤝 Ace your data analyst interview with the interview simulator

📩 Get my weekly email with helpful data career tips

📊 Come to my next free “How to Land Your First Data Job” training

🏫 Check out my 10-week data analytics bootcamp

Timestamps:

(02:10) - What’s the future of data engineering in 2024? (03:06) - Do you need a degree to become a data analyst? (04:57) - How to showcase Excel skills? (07:22) - How to land data analyst internships? (10:10) - What are the main technical skills required to land your first data job? (14:40) - Have you worked with many teachers looking to make a career transition? (16:24) - How to get a data analyst job for people with no work experience? (25:13) - Can you suggest SQL and Excel videos for data analysis? (28:46) - Do you think the data analysis industry is saturated? (28:21) - Do you find data analysts transferring to becoming a data scientist or a data engineer?

Connect with Avery:

📺 Subscribe on YouTube

🎙Listen to My Podcast

👔 Connect with me on LinkedIn

📸 Instagram

🎵 TikTok

Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!

To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more

If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.

👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa

Sandy Iyer has been General Manager of Data Science at Sportsbet since the beginning of 2023, leading a dynamic team that leverages data in innovative ways. But what does it take to lead in such a data-driven environment? How does one balance the promotion of betting products with social responsibility? And how does data shape the strategy of a betting giant like Sportsbet? These are just a few of the questions we'll explore today. I’ve watched Sandy's career trajectory skyrocket in the last few years, and It's been nothing short of inspiring. In this conversation we explore the key elements behind her impressive progression, including the leadership lessons has she gleaned from her time in the trenches of data science. And more importantly, Sandy explains how can you apply these insights to your own career. From discussing unique data science use cases that have propelled Sportsbet's success, to exploring emerging trends that will shape the future of the betting industry, Sandy offers a wealth of insights. She also shares personal stories of challenges faced and overcome, revealing the qualities essential for any budding data scientist aspiring to become a senior analytics leader.

In this wide-ranging podcast, we tackle the CPI inflation report, the mounting threat posed by cyberattacks on the financial system and broader economy, and the regulatory response. Jill Cetina and Lesley Ritter of Moody’s Investor Service and Joe Lyons of BitSight join us with their insights. And we finally learn how to pronounce Matt’s last name. Follow Mark Zandi @MarkZandi, Cris deRitis @MiddleWayEcon, and Marisa DiNatale on LinkedIn for additional insight.

Questions or Comments, please email us at [email protected]. We would love to hear from you.    To stay informed and follow the insights of Moody's Analytics economists, visit Economic View.

Your data project doesn't end once you have results. In order to have impact, you need to communicate those results to others. Presentations filled with endless tables and technical jargon can easily become tedious, leading your audience to lose interest or misunderstand your point. Data storytelling provides a solution to this: by creating a narrative around your results you can increase engagement and understanding from your audience. This is an art, and there are so many factors that contribute to visualizing data and creating a compelling story, it can be overwhelming. However, with the right approach, creating data stories can become second nature. In this special episode of DataFramed, we join forces with the Present Beyond Measure podcast to glean the best data presentation practices from one of the leading voices in the space. Lea Pica host of the Founder and Host of the Present Beyond Measure podcast and is a seasoned digital analytics practitioner, social media marketer and blogger with over 11 years of experience building search marketing and digital analytics practices for companies like Scholastic, Victoria’s Secret and Prudential. Present Beyond Measure’s mission is to bring their teachings to the digital marketing and web analytics communities, and empower anyone responsible for presenting data to an audience. In the full episode, Richie and Lea cover the full picture of data presentation, how to understand your audience, leverage hollywood storytelling, data storyboarding and visualization, the use of imagery in presentations, cognitive load management, the use of throughlines in presentations, how to improve your speaking and engagement skills, data visualization techniques in business setting and much more.  Links Mentioned in the Show: Present Beyond MeasureLea’s BookConnect with Lea on LinkedinHollywood Storytelling[Course] Data Storytelling Concepts