Learn to use analytics more effectively, convert data into value and facilitate smarter and better decision-making for your organization.

The group dives deep into the jobs report for May. They dissect the cross-currents in the numbers, and consider what the report means for financial markets, monetary policy and the macroeconomy. The economic fallout of the legislative deal to end the debt limit drama, including the end of the student loan payment moratorium, are also part of the discussion. And of course there is 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.

What does data engineer  @ShashankData  think about AI, Power BI & Cold Messaging?

Listen to find out 👆

Subscribe to Shashank's Channel: https://www.youtube.com/@ShashankData

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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

Send us a text 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.

Abstract Making Data Simple Podcast is hosted by Al Martin, VP, IBM Expert Services Delivery, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun. This week on Making Data Simple, we have Benn Stancil, Chief Analytics Officer + Founder @ Mode. Benn is an accomplished data analyst with deep expertise in collaborative Business Intelligence and Interactive Data Science. Benn is Co-founder, President, and Chief  Analytics Officer of Mode, an award-winning SaaS company that combines the best elements of Business Intelligence (ABI), Data Science (DS) and Machine Learning (ML) to empower data teams to answer impactful questions and collaborate on analysis across a range of business functions. Under Benn’s leadership, the Mode platform has evolved to enable data teams to explore, visualize, analyze and share data in a powerful end-to-end workflow. Prior to founding Mode, Benn served in senior Analytics positions at Microsoft and Yammer, and worked as a  researcher for the International Economics Program at the Carnegie Endowment for International Peace. Benn also served as an Undergraduate Research Fellow at Wake Forest University,  where he received his B.S. in Mathematics and Economics. Benn believes in fostering a shared sense of humility and gratitude.

Show Notes 1:22 – Benn’s history7:09 – Tell us how you got to where you are today9:14 – Tell us about Mode12:08 – What is your definition of the Chief Analytics Officer?21:53 – Why do we need another BI tool?24:09 – What’s your secret sauce?27:48 – Where did the name Mode come from?28:41 – How do we use Mode?31:08 – What is you goto market strategy? 32:38 – Any client references?34:58 – “The missing piece in the modern data stack” tell us about thisMode  Email: [email protected] [email protected] Twitter: benn stancil Connect with the Team Producer Kate Brown - LinkedIn. Host Al Martin - LinkedIn and Twitter.  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.

Microsoft Power BI Machine Learning and OpenAI offers a comprehensive exploration into advanced data analytics and artificial intelligence using Microsoft Power BI. Through hands-on, workshop-style examples, readers will discover the integration of machine learning models and OpenAI features to enhance business intelligence. This book provides practical examples, real-world scenarios, and step-by-step guidance. What this Book will help me do Learn to apply machine learning capabilities within Power BI to create predictive analytics Understand how to integrate OpenAI services to build enhanced analytics workflows Gain hands-on experience in using R and Python for advanced data visualization in Power BI Master the skills needed to build and deploy SaaS auto ML models within Power BI Leverage Power BI's AI visuals and features to elevate data storytelling Author(s) Greg Beaumont, an expert in data science and business intelligence, brings years of experience in Power BI and analytics to this book. With a focus on practical applications, Greg empowers readers to harness the power of AI and machine learning to elevate their data solutions. As a consultant and trainer, he shares his deep knowledge to help readers unlock the full potential of their tools. Who is it for? This book is ideal for data analysts, BI professionals, and data scientists who aim to integrate machine learning and OpenAI into their workflows. If you're familiar with Power BI's fundamentals and are eager to explore its advanced capabilities, this guide is tailored for you. Perfect for professionals looking to elevate their analytics to a new level, combining data science concepts with Power BI's features.

Today I’m chatting with Kyle Winterbottom, who is the owner of Orbition Group and an advisor/recruiter for companies who are hiring top talent in the data industry. Kyle and I discuss whether the concept of data products has meaningful value to companies, or if it’s in a hype cycle of sorts. Kyle then shares his views on what sets the idea of data products apart from other trends, the well-paid opportunities he sees opening up for product leaders in the data industry, and why he feels being able to increase user adoption and quantify the business impact of your work is also relevant in a candidate’s ability to negotiate higher pay. Kyle and I also discuss the strange tendency for companies to mistakenly prioritize technical skills for these roles, the overall job market for data product leaders, average compensation numbers, and what companies can do to attract this talent.

Highlights/ Skip to:

Kyle introduces himself and his company, Orbition Group (01:02) Why Brian invited Kyle on the show to discuss the recruitment of technical talent for data & analytics teams (02:00) Kyle shares what’s causing companies to build out data product teams (04:49) The reason why viewing data as a product seems to be driving better adoption in Kyle’s view (07:22) Does Kyle feel that the concept of data products is mostly hype or meaningful? (11:26) The different levels of maturity Kyle sees in organizations that are approaching him for help hiring data product talent, and how soft skills are often overlooked (15:37) Kyle’s views on who is successfully landing data product manager roles and how that’s starting to change (23:20) What Kyle’s observations are on the salary bands for data product manager roles and the type of money people can make in this space (25:41) Brian and Kyle discuss how the skills of DPMs can help these leaders improve earning potential (30:30) Kyle’s observations and advice to companies seeking to improve the data product talent they attract (38:12) How listeners can learn more about Kyle and Orbition Group (47:55)

Quotes from Today’s Episode “I think data products, obviously, there’s starting to get a bit of hype around it, which I’ve got no doubt will start to lead organizations to look down that route, just because they see and hear about other organizations doing it. ... [but] what it’s helping organizations to do is to drive adoption.” — Kyle Winterbottom (05:45)

“I think we’re at a point now where it’s becoming more and more clear, day by day, week by week, the there’s more to [the data industry] than just the building of stuff.” – Kyle Winterbottom (12:56)

“The whole soft skills piece is becoming absolutely integral because it’s become—you know, it’s night and day now, between the people that are really investing in themselves in that area and how quickly they’re progressing in their career because of that. But yeah, most organizations don’t even think about that.” – Kyle Winterbottom (18:49)

“I think nine times out of ten, most businesses overestimate the importance of the technical stuff practically in every role. … Even data analysts, data scientists, all they’re bothered about is the tech stack that they’ve used, [but] there’s a lot more to it than just the tech that they use.” – Kyle Winterbottom (22:56)

“There’s probably a big opportunity for really good product people to move into the data space because it’s going to be well paid with lots of opportunity. [It’s] quite an interesting space.” – Kyle Winterbottom (24:05)

“As soon as you get to a point where if you can help to drive adoption and then you can quantify the commercial benefit of that adoption to the organization, that probably puts you up near the top in terms of percentile of being important to a data organization.” – Kyle Winterbottom (32:21)

“We’re forever talking in our industry about the importance of storytelling. Yeah, I’ve never seen a business once tell a good story about how good it is to work for them, specifically in regards to their data analytics team and telling a story about that.” – Kyle Winterbottom (39:37)

Links Kyle’s LinkedIn: https://www.linkedin.com/in/kylewinterbottom/ Orbition Group: https://www.orbitiongroup.com

Ben Harris, former Assistant Secretary for Economic Policy at the US Treasury, summarizes the latest proposal for raising the debt ceiling. An acceptable deal seems to be within reach but remains politically uncertain even as the x-date draws near.  What are the alternatives if no deal is reached?  And what could be the consequences for bondholders, Social Security recipients, and other stakeholders?  Ben joins Mark and Cris in a round of the Inside Economics Statistics Game and provides his views on the future of retirement financing. For more on Ben Harris, 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.

Will AI replace data analyst? Is it going to happen? Has it already happened?

In this episode, I wanted to dig into if I actually think that's going to be the case.

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

🏫 Check out my 10-week data analytics bootcamp

Timestamps:

(01:00) - Brace yourself: AI has ARRIVED! 🤖

(01:44) - Is your data analyst job in jeopardy? AI vs. Human Skills 💼

(02:54) - The art of data analysis using AI 🚀

(03:29) - AI is just a tool 🧮

(04:01) - AI is just like Google 🔓

(05:55) - Job Security? Get good at AI 🌟

(07:18) - Humans make decisions ✨

(08:00) - Join the Ultimate Data Bootcamp! 📚💪

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

This episode of Leaders of Analytics features Dhiraj Rajaram, the Founder of global decision sciences company Mu Sigma. Mu Sigma serves more than 140 of the Fortune 500 and the company’s mission is to simplify complex problems through the science of decisions. Dhiraj shares his views on problem-solving in business, and how Mu Sigma's three core beliefs have been instrumental in the company's success. At Mu Sigma, they believe in "Learning over Knowing", "Extreme Experimentation", and "The New IP". Their data-driven decision-making approach has helped solve some of the toughest business challenges and has set them apart from the competition. As an entrepreneur or business leader, you'll gain valuable insights into using data to solve complex issues, as well as an insider's perspective on Dhiraj's entrepreneurial journey. In this episode we discuss: Dhiraj’s entrepreneurial journey from a one-man band to leading thousands of employeesThe critical moments that led Dhiraj to become a founder and the key elements of entrepreneurial successMu Sigma’s unique recruitment and training strategyWhat you can learn from Mu Sigma’s three core beliefsHow to make better decisions for your organisation, and much more.Mu Sigma's website Connect with Dhiraj on Linkedin.

Richard Branch, Chief Economist for Dodge Data & Analytics, joins the podcast to share his insights on all things construction. Construction is the most interest rate sensitive sector of the economy, yet despite the near unprecedented tightening in monetary policy, it is holding its’ own.  What gives?  The group also digs deep into the different parts of the construction sector, from the struggling office market to the surge in public infrastructure. For more on Richard Branch, 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.

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ABOUT THE TALK: In this talk, Dan Selans shows you how we developed a schema discovery process that is able to automatically evolve schemas in a complex distributed system that is processing upwards of a 100,000 messages per second.

He dives deep into the details of schema versioning, detecting schema conflicts, compatibility and normalization, all without the use of any batching processes.

He shows how they developed a schema discovery process that is able to automatically evolve schemas in a complex distributed system that is processing upwards of a 100,000 messages per second. He also details how to detect schema drift, determine compatibility and ultimately how to do all of this, without having to involve batching.

ABOUT THE SPEAKER: Daniel Selans is the co-founder and CTO of Streamdal.com, a streaming data performance monitoring company. Dan previously wrote software at companies such as InVisionApp, New Relic and DigitalOcean and before that, spent over 10 years doing integration and R&D work at data centers.

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

Your dream data job might be closer than you realize. Don't overlook the hidden gem right in front of you: internal positions. Landing an internal job is easier than going through the external route.

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

Timestamps: (0:00) - The Best Place to Land Your First Job (2:58) - How I Landed My First Data Job (7:11) - Your Company Has a Data Team? (10:22) - Network Inside Your Company (12:54) - Use data at your current position (14:01) - Attend Data Events

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: What are the latest trends and buzzwords in Data?

Barry McCordel welcomes panelists from Hex, DBT Labs and West Marin Data to discuss their thoughts on the latest trends and buzzwords in Data.

Learn about the latest in the world of streaming, data teams doing more with less, data meshes, innovations in different kids of SQL plus more!

ABOUT THE SPEAKERS: Julia Schottenstein is the Product Manager at dbt labs. Prior to this, she worked in Venture Capital as a Principal at NEA.

Drew Banin is the co-founder of dbt labs. He has built event collection systems that scaled to billions of events per month, implemented Markov-based marketing attribution models on millions of dollars of marketing spend, and dreams in NetworkX graphs.

Barry McCardel is the CEO and co-founder of Hex. He previously worked at TrialSpark leading operation and Palantir Technologies where he led teams at the intersection of product development and real-world impact.

Pedram Navid is the Founder of West Marin Data. In his role he helps startups implement their data stack. He also supports them with product, marketing and community-building.

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

Over the past 10 years, data analytics and data visualization have become essential components of an enterprise information strategy. And yet, the adoption of data analytics has remained remarkably static, reaching no more than 30% of potential users. This book explores the most important techniques for taking that adoption further: embedding analytics into the workflow of our everyday operations. Authors Donald Farmer and Jim Horbury show business users how to improve decision making without becoming analytics specialists. You'll explore different techniques for exchanging data, insights, and events between analytics platforms and hosting applications. You'll also examine issues including data governance and regulatory compliance and learn best practices for deploying and managing embedded analytics at scale. Learn how data analytics improves business decision making and performance Explore advantages and disadvantages of different embedded analytics platforms Develop a strategy for embedded analytics in an organization or product Define the architecture of an embedded solution Select vendors, platforms, and tools to implement your architecture Hire or train developers and architects to build the embedded solutions you need Understand how embedded analytics interacts with traditional analytics

Mark and team do a deep dive into the inflation numbers and consider prospects that inflation will continue to moderate. After the statistics game, they turn to their latest research considering the economic fallout of what could happen if lawmakers fail to increase the debt limit in time. It isn’t pretty. For more on the debt limit breach scenarios, 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.

Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

ABOUT THE TALK: In this lightning talk, Emma Tang shares learnings from Stripe’s early efforts to tackle data correctness. As a financial technology company, data correctness is paramount to the operation of the company. This low tolerance for data inaccuracy poses unique constraints to how infrastructure is designed. Emma shares strategies as well as the trade-offs made in order to achieve this high level of correctness.

ABOUT THE SPEAKER: Emma Tang led Big Data Infrastructure at Stripe helping the company build and scale data infrastructure systems to support the 14x revenue growth and 6x headcount growth during her time there.

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: Modern data stacks focus on the most common use-cases and dashboards, but what about all the ad-hoc requests that come? The current tool set fails to allow data analysts to iterate easily with stakeholders. In this talk, we will discuss that without an ad-hoc layer, data analysts are left to answer questions with hacky live SQL or have every request go through the resource-intensive and expensive production processes and workflows.

An ad-hoc layer solves this by allowing data analysts to answer data questions, change their mind, and deliver data dumps or simple analyses incredibly fast and reliably. Allowing them to prioritize putting it into production only if it needs to be reused.

ABOUT THE SPEAKER: Ahmed Elsamadisi is the founder and CEO of Narrator. Narrator enables companies to make better decisions by providing them with the ability to answer any question in under 10 minutes. Ahmed started his career building algorithms for self-driving cars and human-robot interaction. He then joined Raytheon to develop AI algorithms for missile defense, focusing on tracking and discrimination. In 2015, Ahmed joined WeWork as the first hire on their data team. He built their data engineering infrastructure and grew the team of data engineers and analysts.

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: Whether consulting or working as an employee there are certain tools, patterns and practices many of us would like to disappear in the next few years. Many of them delay projects, frustrate data engineers and yet we continue to rely on them. Whether it be transferring data via SFTP or joining teams without coding standards, some companies, even those that may be considered cutting edge, still have these patterns.

In this talk Ben Rogojan explores some of these tools, patterns and practices as well as why he hopes he doesn’t see them around in a few years.

ABOUT THE SPEAKER: Ben Rogojan has spent his career focused on helping companies develop end-to-end data solutions that are simple and maintainable. He has worked in various industries such as healthcare, finance, and e-commerce. In addition, he has worked for companies including Facebook as a data engineer. Using his broad experiences he has helped companies develop, improve, modernize, and migrate their data infrastructure.

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: After two years, three rounds of funding, and hundreds of new employees — Whatnot’s modern data stack has come from not existing to processing tens of millions of events across hundreds of different event types each day.

How does their small (but mighty!) team keep up? This talk explores data contracts — it covers the use of Interface Definition Language (Protobuf) to serve as the source of truth for event definitions, govern event construction in production, automatically generate DBT models in the data warehouse.

ABOUT THE SPEAKER: Zack Klein is a software engineer at Whatnot, where he thoroughly enjoys building data products and narrowly avoiding breaking production each day. Previously, he worked on big data platforms at Blackstone and HBO.

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: Incident management is a key practice used by DevOps and SRE teams to keep software reliable—but it's still uncommon among data teams! Datadog says incident management can "streamline their response procedures, reducing mean time to repair (MTTR) and minimizing any impact on end users."

In this talk, Kyle Kirwan, co-founder of data observability company Bigeye, will explain the basics of incident management and how data teams can use it to reduce disruptions to analytics and machine learning applications.

ABOUT THE SPEAKER: Kyle Kirwan is the co-founder and CEO of Bigeye. He began his career as a data scientist, went on to lead the development of Uber's internal data catalog/lineage/quality tools, and now helps data teams use data observability to improve pipeline reliability and data quality.

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/