ABOUT THE TALK: Learn about "fun-sized companies" (SMB's, small startups, etc) and how to build a fully fledged MLOps platform from scratch using the best OSS tools out there in under a day.

This talk covers: -The main problems MLOps tries to solve -The most common tools being used & their drawbacks -OSS projects & tools that have been developed in the past 2-3 years and how do they solve some of the pain points of the prior tools -The realistic roadmap for companies that are forever “not-Google” scale but want to continue improving their data and ML maturity

ABOUT THE SPEAKER: Mikiko Bazeley is Head of MLOps at Featureform, a Virtual Feature Store. He has previously taken on engineer, data scientist, and data analyst roles for companies including Mailchimp (Intuit), Teladoc, Sunrun, Autodesk along with a handful of early stage startups.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil-ai

ABOUT THE TALK: Quarto is a multi-language, open-source toolkit for creating data-driven websites, reports, presentations, and scientific articles, built on Jupyter.

This talk teaches you how to use Quarto to publish Jupyter notebooks as production quality websites, books, blogs, presentations, PDFs, Office documents, and more. It covers how to publish notebooks within existing content management systems like Hugo, Docusaurus, and Confluence and also explore how Quarto works under the hood along with how the system can be extended to accommodate unique requirements and workflows.

ABOUT THE SPEAKER: J.J. Allaire is the founder of RStudio and the creator of the RStudio IDE. He is an author of several packages in the R Markdown publishing ecosystem and has also worked extensively on the R interfaces to Python and TensorFlow. J.J. is now leading the Quarto project, which is a new Jupyter-based scientific and technical publishing system.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil-ai

ABOUT THE TALK Learn all about cost and performance optimization in Snowflake. This talk deep dive's into Snowflake’s architecture & billing model, covering key concepts like virtual warehouses, micro-partitioning, the lifecycle of a query and Snowflake’s two-tiered cache. It then goes in depth on the most important optimization strategies, like virtual warehouse configuration, table clustering and query writing best practices. Throughout the talk, code snippets and other resources are shared to help you get the most out of Snowflake.

ABOUT THE SPEAKERS Niall Woodward and Ian Whitestone are the co-founders at SELECT, a tool to help Snowflake users optimize their Snowflake cost & performance.

Niall Woodward has been well known in the data community for creating and contributing to open source packages.

Ian Whitestone previously led data teams at Shopify and Capital One. At Shopify, Ian spearheaded the efforts to reduce their data warehouse spend by over 50%.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil-ai

ABOUT THE TALK: This talk explains what the control plane of data looks like and how it fits into the reference architecture for the deconstructed data stack: a data stack that includes operational data stores, streaming systems, transformation engines, BI tools, warehouses, ML tools and orchestrators.

It dives into the fundamental characteristics for a control plane:

Breadth (completeness) Latency (freshness) Scale Source of Truth Auditability

ABOUT THE SPEAKER: Shirshanka Das is the Co-founder and CEO of Acryl Data, the company which is commercializing the open source DataHub project, a real-time metadata platform used by LinkedIn, Stripe, Pinterest, Optum, Expedia and many others. Prior to founding Acryl, he was the overall architect for Big Data at LinkedIn from 2010 to 2020, and responsible for creating the metadata and data management strategy at the company.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil-ai

ABOUT THE TALK:

Statsig is a product observability platform that helps product teams move faster and make better decisions. Companies like Notion, Flipkart, Eventbrite, Ancestry, and Univision use it to release features, run experiments and measure impact.

In only two years, Statsig is supporting thousands of experiments across billions of users (unique company specific userIDs). In this session you will learn lessons on their company's growth.

ABOUT THE SPEAKER: Timothy Chan is an experienced data science professional, currently serving as the Data Science Lead at Statsig. Before joining Statsig, Timothy spent almost 5 years as a Data Scientist at Facebook (now Meta), where he was involved in projects across Facebook App and Reality Labs. His background includes working in biotech, researching treatments for diseases such as Alzheimer’s, Multiple Sclerosis, Lupus, and Cancer.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil

ABOUT THE TALK: Small data teams face supply and demand problems. Triaging and prioritizing data work can be overwhelming. But what if data consumers could create their own products with minimal training?

Learn how to empower data consumers without disrupting others. Discover lessons from an 'extreme' self-service analytics approach: best practices, fostering a data community, promoting SQL literacy, and establishing solid guard rails.

ABOUT THE SPEAKER: Alice Leach is a Data Engineer at Whatnot Inc., a live stream platform and marketplace that enables collectors and enthusiasts to connect, buy, and sell verified products. She transitioned from academia to data in 2021, working first as a data scientist then data engineer. Her current work at Whatnot focuses on designing and building robust, self-service data workflows using a modern data stack.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil

ABOUT THE TALK: Got your Modern Data Stack setup, now what? A mature data practice goes beyond setting up the data pipeline, and ensures there are both systems and processes in place to make it easy for everyone to find and understand data.

Learn how Select Star enables data discovery, making knowledge searchable and understandable for all. Uncover best practices for setting up a data discovery portal as your single source of truth.

ABOUT THE SPEAKER: Alec Bialosky is currently the Director of Business Operations at Select Star where he spends the majority of his time working with prospects and customers to help them achieve their data discovery goals with Select Star.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/data...

ABOUT THE TALK: Data exchange is vital for business partnerships, but current practices are manual, prone to leaks, hard to validate, monitor, and audit.

Tune in to this talk for an overview of data sharing methods, security comparisons, simplicity, and speed. Discover best practices and solutions to overcome challenges.

ABOUT THE SPEAKER: Pardis Noorzad is CEO at General Folders. She led a data team at Twitter, covering a variety of consumer products. Pardis has also built products in growth stage fintech and digital health and early stage AI platform companies.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil

Wanna become a data analyst? Start here. This is the most upvoted post in the r/datanalysis history, full of advice and a roadmap to becoming a data analyst. Join me as I'm going to be diving into what their advice was and if I agree or disagree with it.

🌟 Join the data project club! “25OFF” to get 25% off (first 50 members).

📊 Come to my next free “How to Land Your First Data Job” training 🏫 Check out my 10-week data analytics bootcamp

Timestamps: (0:52) - Do I need a degree? (1:34) - Is Google Data Analytics Cert enough? (3:39) - Will my degree help me? (5:54) - What do I need to learn? (8:07) - Do certifications matter? (9:01) - Can I get a job right away? (10:36) - Is having a degree is enough? (11:41) - Build a strong foundation (11:58) - Get hands-on experience (12:21) - Build your network (12:40) - Should You Get a CS Degree? (13:09) - Should I learn Machine Learning (13:54) - Build a portfolio (14:31) - Create a personalized resume (14:51) - Practice every day (14:59) - Have the right attitude (15:20) - Applying for the jobs (16:13) - Be very patient

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 Datatopics is a podcast presented by Kevin Missoorten to talk about the fuzzy and misunderstood concepts in the world of data, analytics, and AI and get to the bottom of things.

In this episode, we'll be discussing a fascinating and rapidly growing technology called digital twins, which is changing the way we design, manufacture, and operate everything from tomato plants to complex machinery and even the world. Joining us as expert guests on this topic are Paulan Korenhof, Bart Meyers and Tim Leers. Together we explore the basics of digital twins: what are they and as of when do we speak of a digital twin and not just a digital model or digital shadow, when are they useful and when are they not or how mature is this field today?

We also don't shy away from more philosophical topics like the assemblage of the digital twin - where does it start and where does it end -, where is this field going, or the importance of the awareness of digital twin limitations by decision makers.

Datatopics is brought to you by Dataroots Music: The Gentlemen - DivKidThe thumbnail is generated by Midjourney

In this episode of Leaders of Analytics, I am joined by Ada Guan who is one of the most innovative minds in the field of credit decisioning. Ada is CEO and co-founder of Rich Data Co, a company that helps lenders make informed and accurate credit decisions by leveraging AI and machine learning. Listen in as Ada sheds light on the role that AI and machine learning can play in transforming the lending industry and what the future may hold for credit decisioning. In this episode, we'll discuss: Ada’s entrepreneurial journeyThe typical pain points lenders face and how RDC’s unique AI solution solves these problemsWhat makes RDC’s solution unique and why banks should buy rather than build themselvesHow to find product-market fit or an AI productThe additional benefits an AI solution brings over traditional credit scorecards or rules-based decisioning engines, and much more.Learn more about Rich Data Co here: https://www.richdataco.com/ Connect with Ada Guan on LinkedIn.

Another jobs Friday, another strong jobs report. Dante DeAntonio joins the crew to break down the employment numbers and what they mean for the near-term outlook. The team also discusses the recent banking crisis, the looming debt limit x-date, and the most likely outcomes for both. And is someone using ChatGPT to cheat at the statistics game? For the full transcript, click here 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.

My wife and I just had our first baby. Everyone is doing well. So I’m taking the week off to spend time with my amazing family.

In the meantime, I would appreciate you leaving a rating for the podcast. The ratings & reviews help me stay motivated, as well as help others find the podcast. If you’re on Apple Podcasts, scroll to the bottom of the Data Career Podcast page and you’ll find the spot to leave a rating a review. If you’re on Spotify, you should see a rating with a star towards the top left of the page (below the podcast art). Click it and leave a rating. I’d love to hit 50 on each platform. Appreciate you listening & have a great week. 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 IBM® Redpaper™ publication is a comprehensive guide that covers the IBM Power System AC922 server (8335-GTH and 8335-GTX models). The Power AC922 server is the next generation of the IBM POWER® processor-based systems, which are designed for deep learning (DL) and artificial intelligence (AI), high-performance analytics, and high-performance computing (HPC). This paper introduces the major innovative Power AC922 server features and their relevant functions: Powerful IBM POWER9™ processors that offer up to 22 cores at up to 2.80 GHz (3.10 GHz turbo) performance with up to 2 TB of memory. IBM Coherent Accelerator Processor Interface (CAPI) 2.0, IBM OpenCAPI™, and second-generation NVIDIA NVLink 2.0 technology for exceptional processor to accelerator intercommunication. Up to six dedicated NVIDIA Tesla V100 graphics processing units (GPUs). This publication is for professionals who want to acquire a better understanding of IBM Power Systems™ products and is intended for the following audiences: Clients Sales and marketing professionals Technical support professionals IBM Business Partners Independent software vendors (ISVs) This paper expands the set of IBM Power Systems documentation by providing a desktop reference that offers a detailed technical description of the Power AC922 server. This paper does not replace the current marketing materials and configuration tools. It is intended as an extra source of information that, together with existing sources, can be used to enhance your knowledge of IBM server solutions.

Welcome to this step-by-step guide for Excel users, data analysts, and finance specialists. It is designed to take you through practical report and development scenarios, including both the approach and the technical challenges. This book will equip you with an understanding of the overall Power Platform use case for addressing common business challenges. While Power BI continues to be an excellent tool of choice in the BI space, Power Platform is the real game changer. Using an integrated architecture, a small team of citizen developers can build solutions for all kinds of business problems. For small businesses, Power Platform can be used to build bespoke CRM, Finance, and Warehouse management tools. For large businesses, it can be used to build an integration point for existing systems to simplify reporting, operation, and approval processes. The author has drawn on his15 years of hands-on analytics experience to help you pivot from the traditional Excel-based reporting environment. By using different business scenarios, this book provides you with clear reasons why a skill is important before you start to dive into the scenarios. You will use a fast prototyping approach to continue to build exciting reporting, automation, and application solutions and improve them while you acquire new skill sets. The book helps you get started quickly with Power BI. It covers data visualization, collaboration, and governance practices. You will learn about the most practical SQL challenges. And you will learn how to build applications in PowerApps and Power Automate. The book ends with an integrated solution framework that can be adapted to solve a wide range of complex business problems. What You Will Learn Develop reporting solutions and business applications Understand the Power Platform licensing and development environment Apply Data ETL and modeling in Power BI Use Data Storytelling and dashboard design to better visualize data Carry out data operations with SQL and SharePoint lists Develop useful applications using Power Apps Develop automated workflows using Power Automate Integrate solutions with Power BI, Power Apps, and Power Automate to build enterprise solutions Who This Book Is For Next-generation data specialists, including Excel-based users who want to learn Power BI and build internal apps; finance specialists who want to take a different approach to traditional accounting reports; and anyone who wants to enhance their skill set for the future job market.

Falling house prices and recent housing policy actions taken by the FHA and FHFA to address housing affordability are top of mind this week. Edward Pinto, Senior Fellow and the Director of the AEI Housing Center at the American Enterprise Institute joins to discuss. The team also provides their thoughts on weaker-than-expected GDP data. Is the weak GDP # good or bad for the economy? Marisa dominates the statistics game.  For more on Edward Pinto, click here For the full transcript, click here 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.

Expert Data Modeling with Power BI, Second Edition, serves as your comprehensive guide to mastering data modeling using Power BI. With clear explanations, actionable examples, and a focus on hands-on learning, this book takes you through the concepts and advanced techniques that will enable you to build high-performing data models tailored to real-world requirements. What this Book will help me do Master time intelligence and virtual tables in DAX to enhance your data models. Understand best practices for creating efficient Star Schemas and preparing data in Power Query. Deploy advanced modeling techniques such as calculation groups, aggregations, and incremental refresh. Manage complex data models and streamline them to improve performance. Leverage data marts and data flows within Power BI for modularity and scalability. Author(s) Soheil Bakhshi is a seasoned expert in data visualization and analytics with extensive experience in leveraging Power BI for business intelligence solutions. Passionate about educating others, he combines practical insights and technical knowledge to make learning accessible and effective. His approachable writing style reflects his commitment to helping readers succeed. Who is it for? This book is ideal for business intelligence professionals, data analysts, or report developers with basic knowledge of Power BI and experience with Star Schema concepts. Whether you're looking to refine your data modeling skills or expand your expertise in advanced features, this guide aims to help you achieve your goals efficiently.

Stop being left behind by not building data project.

It can be intimidating to build a real-world data project alone.

But why be alone when you can be with us in the Data Project Club?

Come join me talking about cool Data Project Club, that can help you show your skills, build your project and expand your data network.

🌟 Join the data project club!

“25OFF” to get 25% off (first 50 members).

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

🏫 Check out my 10-week data analytics bootcamp

Timestamps:

(1:00) - Projects Are The Cheat Code

(1:55) - Why data project are your career accelerator?

(3:37) - Show Your Skills > Tell Your Skills

(3:43) - Doing data projects is FUN!!!

(4:37) - Come join The Data Project Club

(5:51) - Practice. Build Connect.

(7:01) - My Bootcamp

(7:30) - Data Project Club Perks

(10:48) - Data Project Club Tiers

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

ABOUT THE TALK: Hamilton is a novel open-source framework for developing and maintaining scalable feature engineering dataflows.

We introduce the framework, discuss its motivations and initial successes at Stitch Fix, showcase its lightweight data lineage and catalog abilities, and share recent extensions that seamlessly integrate it with distributed compute offerings, such as Dask, Ray, and Spark.

ABOUT THE SPEAKER: Elijah Ben Izzy has always enjoyed working at the intersection of math and engineering. He has more recently focused on building tools to make data scientists and researchers more productive.

He built infrastructure to help quantitative researchers efficiently turn ideas into production trading models at Two Sigma and ran the Model Lifecycle team at Stitch Fix.

He is now the CTO at DAGWorks, which aims to solve the problem of building and maintaining complex ETLs for machine learning.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil-ai/

The modern data stack has evolved rapidly in the past decade. Yet, as enterprises migrate vast amounts of data from on-premises platforms to the cloud, data teams continue to face limitations executing data transformation at scale. Data transformation is an integral part of the analytics workflow--but it's also the most time-consuming, expensive, and error-prone part of the process. In this report, Satish Jayanthi and Armon Petrossian examine key concepts that will enable you to automate data transformation at scale. IT decision makers, CTOs, and data team leaders will explore ways to democratize data transformation by shifting from activity-oriented to outcome-oriented teams--from manufacturing-line assembly to an approach that lets even junior analysts implement data with only a brief code review. With this insightful report, you will: Learn how successful data systems rely on simplicity, flexibility, user-friendliness, and a metadata-first approach Adopt a product-first mindset (data as a product, or DaaP) for developing data resources that focus on discoverability, understanding, trust, and exploration Build a transformation platform that delivers the most value, using a column-first approach Use data architecture as a service (DAaaS) to help teams build and maintain their own data infrastructure as they work collaboratively About the authors: Armon Petrossian is CEO and cofounder of Coalesce. Previously, he was part of the founding team at WhereScape in North America, where he served as national sales manager for almost a decade. Satish Jayanthi is CTO and cofounder of Coalesce. Prior to that, he was senior solutions architect at WhereScape, where he met his cofounder Armon.