Learn how to empower teams to speed development of the latest enterprise-grade innovations on Google Cloud Marketplace, from data analytics and generative AI to best-of-breed business applications. Discover features to help maintain real-time visibility and governance over your development and operations so you can mitigate shadow IT. You’ll hear from customers who have successfully grown their business and increased time-to-deployment.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

The key to maintaining a strong cloud security posture is to build from the start on a robust foundation of baseline security controls. Google Cloud’s Security Foundation provides recommended controls to common cloud adoption use cases, including infrastructure modernization, AI workloads, data analytics, and application modernization. In this session, you’ll learn how to start secure and stay secure in the cloud using the Security Foundation.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

Learn how Google detects threats against Google Cloud to protect multicloud environments. Join this technical session and find out how industry-leading Mandiant threat intelligence combines with planet-scale data analytics to detect new and persistent threats to cloud environments, cloud identities, and cloud workloads. See how end-to-end investigation and case management support the right security outcomes.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

In this episode of the Data Career Podcast, Avery chats with Josh Starmer, PhD, also known as StatQuest on YouTube, about the common fear of math and statistics, and how to overcome it.

They delve into Josh's journey from hating math to becoming a beloved statistics YouTuber, his unique approach to making complex statistical concepts accessible, and the importance of understanding one's learning style.

✉️ Discover what we wish we knew about landing the dream job

⁠🤖 Data Analytics Answers At Your Finger Tips

Connect with Josh Starmer PhD:

🤝 Follow on Linkedin

▶️ Subscribe on YouTube

📘 Get StatQuest Illustrated Guide to Machine Learning

🤝 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:

(01:54) - Learning Styles and Overcoming Math Fear (07:03) - The Illustrated Guide to Machine Learning: A Must-Read (21:55) - The Practicality of Statistics: Learning by Doing (28:07) - The Birth of StatQuest: Transforming Teaching with YouTube (33:27) - Learning in Public: The Impact of Sharing Knowledge

Connect with Avery:

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👔 Connect with me on LinkedIn

📸 Instagram

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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

Join us as we go from zero to insights in 15 minutes. Alex will build an entire analytical report, from SQL query to python to data visualization. We’ll cover the basics of a modern data notebook, some of the technical AI Magic behind the scenes, and show how hundreds of customers accelerate time to insight with Hex.

As the field of data analytics continues to progress and expand, the role of semantic layers in harnessing the power of AI is becoming increasingly crucial. The incorporation of context and constraint is essential to optimizing the potential of Language Model Models (LLMs), which requires a more structured and specialized approach. While traditional methods have made strides in providing some context through prompt engineering and knowledge graphs, semantic layers offer unparalleled clarity and efficiency in bridging the gap for LLMs. To further unfold the narrative on semantic layers and their transformative impact on AI-enabled analytics, we invite you to a thought-provoking session with Artyom Keydunov, Cube's CEO & Co-founder.

Big Data Europe Onsite and online on 22-25 November in 2022 Learn more about the conference: https://bit.ly/3BlUk9q

Join our next Big Data Europe conference on 22-25 November in 2022 where you will be able to learn from global experts giving technical talks and hand-on workshops in the fields of Big Data, High Load, Data Science, Machine Learning and AI. This time, the conference will be held in a hybrid setting allowing you to attend workshops and listen to expert talks on-site or online. Ibrahim Muzaferija

We'll explore how integrating AI, serverless computing, data analytics, and APIs can revolutionize the retail landscape. Learn how Google Cloud Run, Apigee, BigQuery, and Vertex AI collaborate to create personalized shopping experiences, streamline operations, and drive sustainability. Key takeaways include implementing conversational AI for enhanced customer interaction, leveraging BigQuery for data-driven insights, and using Cloud Run for efficient, scalable retail solutions.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

With the surge of new generative AI capabilities, companies and their customers can now interact with systems and data in new ways. To activate AI organizations require a data foundation with the scale and efficiency to bring business data together with AI models and ground them in customer reality. Join this session to learn the latest innovations for data analytics and BI, and why tens of thousands of organizations are fueling their journey with BigQuery and Looker.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

Data Analytics, Level 300 In this session we will highlight CME Group's approach to enabling data access to our customers in non-traditional ways, making it easy for new customers to access CME Group data and how we have designed solutions to securely and efficiently provide access to public and private datasets to customers. Please note: seating is limited and on a first-come, first served basis; standing areas are available

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

Install data analytics into your brain with this comprehensive introduction Data Analytics & Visualization All-in-One For Dummies collects the essential information on mining, organizing, and communicating data, all in one place. Clocking in at around 850 pages, this tome of a reference delivers eight books in one, so you can build a solid foundation of knowledge in data wrangling. Data analytics professionals are highly sought after these days, and this book will put you on the path to becoming one. You’ll learn all about sources of data like data lakes, and you’ll discover how to extract data using tools like Microsoft Power BI, organize the data in Microsoft Excel, and visually present the data in a way that makes sense using a Tableau. You’ll even get an intro to the Python, R, and SQL coding needed to take your data skills to a new level. With this Dummies guide, you’ll be well on your way to becoming a priceless data jockey. Mine data from data sources Organize and analyze data Use data to tell a story with Tableau Expand your know-how with Python and R New and novice data analysts will love this All-in-One reference on how to make sense of data. Get ready to watch as your career in data takes off.

Matt Turck has been publishing his ecosystem map since 2012. It was first called the Big Data Landscape. Now it's the Machine Learning, AI & Data (MAD) Landscape.  The 2024 MAD Landscape includes 2,011(!) logos, which Matt attributes first a data infrastructure cycle and now an ML/AI cycle. As Matt writes, "Those two waves are intimately related. A core idea of the MAD Landscape every year has been to show the symbiotic relationship between data infrastructure, analytics/BI,  ML/AI, and applications." Matt and Tristan discuss themes in Matt's post: generative AI's impact on data analytics, the modern AI stack compared to the modern data stack, and Databricks vs. Snowflake (plus Microsoft Fabric). For full show notes and to read 7+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com. The Analytics Engineering Podcast is sponsored by dbt Labs.

The Complete Power BI Interview Guide is your companion to mastering Power BI roles and acing data analyst interviews. With hands-on skills, expert tips, and targeted preparation strategies, this resource equips you to excel in interviews and certifications while navigating the competitive job market. What this Book will help me do Create a powerful professional brand to optimize your resume and online presence. Master essential Power BI skills including data modeling, DAX programming, and visualization. Prepare effectively for interviews with industry-relevant questions, answers, and insights. Gain an edge in the market by understanding hiring procedures and negotiation tactics. Develop comprehensive analytics solutions exemplified with real-world case studies. Author(s) Sandielly Ortega Polanco, Gogula Aryalingam, and Abu Bakar Nisar Alvi bring years of collective experience in data analytics, Power BI, and career mentorship. Their insights are drawn from extensive professional practice and their passion for empowering future data analysts. Together, they provide an approachable and practical guide to securing roles in the competitive landscape of data analytics. Who is it for? This book is ideal for aspiring data analysts, business intelligence developers, or those shifting into Power BI roles who wish to enhance their knowledge and refine their strategies for interview success. It speaks to both newcomers to the field and seasoned professionals aiming to elevate their expertise.

In this episode of the Data Career Podcast, Avery interviews Ken Jee.

They delve into Ken's unique path into sports analytics, starting from his personal experience as a golfer and his curious inquiry that led to an internship and gradually crafted a niche in sports data science.

✉️ Discover what we wish we knew about landing the dream job

🤖 Data Analytics Answers At Your Finger Tips

Connect with Ken Jee

🤝 Follow on Linkedin

▶️ Ken Jee Official Youtube Channel

▶️ Ken's Nearest Neighbors Podcast

🏀 The Exponential Athlete Podcast

🤝 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:

(09:54) Deep Dive into Golf Analytics (18:16) Ken's Personal Journey into Sports Analytics (24:49) Breaking into Sports Analytics (29:16) The Power of Networking and Creating Opportunities

Connect with Avery:

📺 Subscribe on YouTube

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👔 Connect with me on LinkedIn

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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

This week on Experiencing Data, I chat with a new kindred spirit! Recently, I connected with Thabata Romanowski—better known as "T from Data Rocks NZ"—to discuss her experience applying UX design principles to modern analytical data products and dashboards. T walks us through her experience working as a data analyst in the mining sector, sharing the journey of how these experiences laid the foundation for her transition to data visualization. Now, she specializes in transforming complex, industry-specific data sets into intuitive, user-friendly visual representations, and addresses the challenges faced by the analytics teams she supports through her design business. T and I tackle common misconceptions about design in the analytics field, discuss how we communicate and educate non-designers on applying UX design principles to their dashboard and application design work, and address the problem with "pretty charts." We also explore some of the core ideas in T's Design Manifesto, including principles like being purposeful, context-sensitive, collaborative, and humanistic—all aimed at increasing user adoption and business value by improving UX.

Highlights/ Skip to:

I welcome T from Data Rocks NZ onto the show (00:00) T's transition from mining to leading an information design and data visualization consultancy. (01:43) T discusses the critical role of clear communication in data design solutions. (03:39) We address the misconceptions around the role of design in data analytics. (06:54)  T explains the importance of journey mapping in understanding users' needs. (15:25) We discuss the challenges of accurately capturing end-user needs. (19:00)  T and I discuss the importance of talking directly to end-users when developing data products. (25:56)  T shares her 'I like, I wish, I wonder' method for eliciting genuine user feedback. (33:03) T discusses her Data Design Manifesto for creating purposeful, context-aware, collaborative, and human-centered design principles in data. (36:37) We wrap up the conversation and share ways to connect with T. (40:49)

Quotes from Today’s Episode "It's not so much that people…don't know what design is, it's more that they understand it differently from what it can actually do..." - T from Data Rocks NZ (06:59) "I think [misconception about design in technology] is rooted mainly in the fact that data has been very tied to IT teams, to technology teams, and they’re not always up to what design actually does.” - T from Data Rocks NZ (07:42)  “If you strip design of function, it becomes art. So, it’s not art… it’s about being functional and being useful in helping people.” - T from Data Rocks NZ (09:06)

"It’s not that people don’t know, really, that the word design exists, or that design applies to analytics and whatnot; it’s more that they have this misunderstanding that it’s about making things look a certain way, when in fact... It’s about function. It’s about helping people do stuff better." - T from Data Rocks NZ (09:19) “Journey Mapping means that you have to talk to people...  Data is an inherently human thing. It is something that we create ourselves. So, it’s biased from the start. You can’t fully remove the human from the data" - T from Data Rocks NZ (15:36)  “The biggest part of your data product success…happens outside of your technology and outside of your actual analysis. It’s defining who your audience is, what the context of this audience is, and to which purpose do they need that product. - T from Data Rocks NZ (19:08) “[In UX research], a tight, empowered product team needs regular exposure to end customers; there’s nothing that can replace that." - Brian O'Neill (25:58)

“You have two sides [end-users and data team]  that are frustrated with the same thing. The side who asked wasn’t really sure what to ask. And then the data team gets frustrated because the users don’t know what they want…Nobody really understood what the problem is. There’s a lot of assumptions happening there. And this is one of the hardest things to let go.” - T from Data Rocks NZ (29:38) “No piece of data product exists in isolation, so understanding what people do with it… is really important.” - T from Data Rocks NZ (38:51)

Links Design Matters Newsletter: https://buttondown.email/datarocksnz  Website: https://www.datarocks.co.nz/ LinkedIn: https://www.linkedin.com/company/datarocksnz/ BlueSky: https://bsky.app/profile/datarocksnz.bsky.social Mastodon: https://me.dm/@datarocksnz

Discover how to implement a modern data mesh architecture using Microsoft Azure's Cloud Adoption Framework. In this book, you'll learn the strategies to decentralize data while maintaining strong governance, turning your current analytics struggles into scalable and streamlined processes. Unlock the potential of data mesh to achieve advanced and democratized analytics platforms. What this Book will help me do Learn to decentralize data governance and integrate data domains effectively. Master strategies for building and implementing data contracts suited to your organization's needs. Explore how to design a landing zone for a data mesh using Azure's Cloud Adoption Framework. Understand how to apply key architecture patterns for analytics, including AI and machine learning. Gain the knowledge to scale analytics frameworks using modern cloud-based platforms. Author(s) None Deswandikar is a seasoned data architect with extensive experience in implementing cutting-edge data solutions in the cloud. With a passion for simplifying complex data strategies, None brings real-world customer experiences into practical guidance. This book reflects None's dedication to helping organizations achieve their data goals with clarity and effectiveness. Who is it for? This book is ideal for chief data officers, data architects, and engineers seeking to transform data analytics frameworks to accommodate advanced workloads. Especially useful for professionals aiming to implement cloud-based data mesh solutions, it assumes familiarity with centralized data systems, data lakes, and data integration techniques. If modernizing your organization's data strategy appeals to you, this book is for you.

In "Extending Power BI with Python and R," you'll learn how to enhance your Power BI reports and analyses by leveraging the advanced analytical capabilities of Python and R. From working with large datasets to creating sophisticated visuals, this book provides practical instructions on powerful techniques that unlock new possibilities in Power BI. What this Book will help me do Configure and optimize Python and R integration in Power BI for enhanced performance. Implement advanced data transformation techniques to overcome Power BI limitations. Develop advanced visualizations using the Grammar of Graphics in Python and R. Analyze data leveraging powerful Python and R algorithms, including machine learning models. Secure your Power BI data with anonymization and pseudonymization techniques. Author(s) None Zavarella is a data analytics expert with years of practical experience in business intelligence and data analytics. With a passion for enhancing data tools with programming languages like Python and R, they bring practical knowledge and technical acumen to this comprehensive resource. They aim to make complex concepts approachable to their readers. Who is it for? This book is aimed at professionals such as business analysts, business intelligence specialists, and data scientists who leverage Power BI for their data solutions. Readers should have a working knowledge of Power BI basics and a desire to extend its capabilities. A familiarity with Python and R programming basics is also beneficial for following the advanced techniques presented.

Dive into the comprehensive world of data transformation with "The Definitive Guide to Power Query (M)". This book empowers you with the knowledge and skills necessary to effectively utilize Power Query for complex data transformation tasks. You will develop expertise in practical techniques, advanced M language concepts, and optimization strategies. What this Book will help me do Understand the fundamentals of Power Query and its functionalities. Learn to perform complex data transformations using various Power Query functions. Gain insight into advanced M language structures such as custom functions and nested expressions. Develop skills in error handling and debugging to streamline your data processes. Master performance optimization techniques for efficient data handling with Power Query. Author(s) Gregory Deckler, Rick de Groot, and Melissa de Korte are seasoned professionals in business intelligence and data analytics. With years of experience using Power Query, they bring a wealth of knowledge and practical insight into tackling real-world data problems. Their combined expertise ensures a clear and immersive learning experience for readers, guiding them through fundamental to advanced topics. Who is it for? This book is ideal for business analysts, data professionals, and power users who wish to advance their data transformation capabilities. If you're someone with foundational experience in Power Query looking to become proficient or an industry professional aiming to optimize workflows, this book is tailored to suit your goals.

In this episode of the Data Career Podcast, Avery interviews Eric Cuentas, a chemical engineer who turned into a data analyst and career coach.

They discuss obstacles when pursuing career goals and highlight the importance of determining genuine motivations to align with prospective roles.

They also discuss practical ways to overcome fear in the career transition process, emphasising the essentiality of consistent networking and the crucial role of resumes in the job application process.

✉️ Discover what we wish we knew about landing the dream job

🤖 Data Analytics Answers At Your Finger Tips

Connect with Erick Cuentas:

🤝 Connect on Linkedin

🤝 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:

(04:36) - Eric's Unique Career Journey (10:01) - Overcoming Fear in Career Transition (24:34) - The Importance of Job Titles in Career Progression (26:09) - The Job Search Process: Common Mistakes (28:15) - The Reality of Job Rejections (31:37) - The Impact of Networking in Job Search (37:41) - The Impact of Consistent LinkedIn Engagement

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 This is one of my favorite episodes with Nancy Hensley, when she was CMO at Stats Perform.  I've got to get back to my bracket!

Money Ball is back! Nancy Hensley, Chief Marketing Officer for Stats Perform, gives us the latest on data analytics in sports. If you like sports don't listen unless you have time to be entertained.   Show Notes   ·      04:09 What does Money Ball look like now? ·      07:30 Mrs Chicago's personal update ·      08:40 Fan website: The Analyst ·      11:16 Stats Perform for the rest of us ·      17:25 Sports tech competitors ·      18:34 Monetizing data. $115M for NFL data! What? ·      27:44 Broadcaster and Pressbox Linkedin: https://www.linkedin.com/in/nancyhensley/   Website: https://statsperform.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. 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.