For those who celebrate or acknowledge it, Christmas is now in the rearview mirror. Father Time has a beard that reaches down to his toes, and he's ready to hand over the clock to an absolutely adorable little Baby Time when 2024 rolls in. That means it's time for our annual set of reflections on the analytics and data science industry. Somehow, the authoring of this description of the show was completely unaided by an LLM, although the show did include quite a bit of discussion around generative AI. It also included the announcement of a local LLM based on all of our podcast episodes to date (updated with each new episode going forward!), which you can try out here! The discussion was wide-ranging beyond AI: Google Analytics 4, Marketing Mix Modelling (MMM), the technical/engineering side of analytics versus the softer skills of creative analytical thought and engaging with stakeholders, and more, as well as a look ahead to 2024! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

There are a few caveats to using generative AI tools, those caveats have led to a few tips that have quickly become second nature to those that use LLMs like ChatGPT. The main one being: have the domain knowledge to validate the output in order to avoid hallucinations. Hallucinations are one of the weak spots for LLMs due to the nature of the way they are built, as they are trained to correlate data in order to predict what might come next in an incomplete sequence. Does this mean that we’ll always have to be wary of the output of AI products, with the expectation that there is no intelligent decision-making going on under the hood? Far from it. Causal AI is bound by reason—rather than looking at correlation, these exciting systems are able to focus on the underlying causal mechanisms and relationships. As the AI field rapidly evolves, Causal AI is an area of research that is likely to have a huge impact on a huge number of industries and problems.  Paul Hünermund is an Assistant Professor of Strategy and Innovation at Copenhagen Business School. In his research, Dr. Hünermund studies how firms can leverage new technologies in the space of machine learning and artificial intelligence such as Causal AI for value creation and competitive advantage. His work explores the potential for biases in organizational decision-making and ways for managers to counter them. It thereby sheds light on the origins of effective business strategies in markets characterized by a high degree of technological competition and the resulting implications for economic growth and environmental sustainability.  His work has been published in The Journal of Management Studies, the Econometrics Journal, Research Policy, Journal of Product Innovation Management, International Journal of Industrial Organization, MIT Sloan Management Review, and Harvard Business Review, among others.  In the full episode, Richie and Paul explore Causal AI, its differences when compared to other forms of AI, use cases of Causal AI in fields like drug development, marketing, manufacturing, and defense. They also discuss how Causal AI contributes to better decision-making, the role of domain experts in getting accurate results, what happens in the early stages of Causal AI adoption, exciting new developments within the Causal AI space and much more.  Links Mentioned in the Show: Causal Data Science in BusinessCausal AI by causaLensIntro to Causal AI Using the DoWhy Library in PythonLesson: Inference (causal) models

We talked about:

Dimitri’s background The first steps of transitioning into freelance Working with recruiters (contracting) Deciding on what to charge for your services Establishing your network Self-marketing Contracting vs freelancing Which channel is better for those starting out? Cutting out the middleman Where to look for clients and how to vet them The different way of getting into freelancing Going back to a full-time job after freelancing Common mistakes freelancers make Dimitri’s resource suggestions Reaching out to Dimitri

Links:

LinkedIn profile: http://www.linkedin.com/in/visnadi The DataFreelancer website: https://thedatafreelancer.com/

Free ML Engineering course: http://mlzoomcamp.com Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

Send us a text This week on Making Data Simple, Fred Joyal. Perhaps you've seen Fred on 1-800-DENTIST commercials. Now, he's turned marketing genius into the art of being BOLD.   Show Notes  02:20 Brand Fred Joyal 19:20 Monetization Strategy 20:58 Boldness is a Super Power 23:18 Just Show Up 26:15 Step Up with Exercises 27:00 Failure's are Steps Up, Take Another Swing 38:50 5 Steps to Lowering Anxiety 41:50 How to Better Network Find Fred Joyal @ https://fredjoyal.com/ LinkedIn: linkedin.com/in/fredjoyal Twitter: fredjoyal  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, WW VP Account Technical Leader IBM Technology Sales, 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 consequences of data not being easily accessible within an organization are profound. Good decision-making often relies on good information, and with crucial insights locked behind closed doors, decision-makers may have to rely on incomplete information, stifling their ability to innovate through a lack of comprehensive data access or an inability to leverage data to its full potential. The ramifications of this are not merely operational – they extend to the core of an organization's ability to thrive in the data-driven era. However, democratizing access to data is only the first hurdle in driving a data led organization, employees need to feel confident in their ability to use data, try new tools and adopt new processes. But who is best to show us the benefits of accessing and utilizing data currently, and the cultural benefits it can bring.  Lilac Schoenbeck is the Vice President of Strategic Initiatives at Rocket Software. Lilac has two decades of experience in enterprise software, data center technology and cloud, with wider experience in product marketing, pricing and packaging, corporate strategy, M&A integrations and product management. Lilac is passionate about delivering exceptional technology to IT teams that helps them drive value for their businesses.  In the episode, Richie and Lilac explore data democratization and the importance of having widespread data capabilities across an organization, common data problems that data democratization can solve, tooling to facilitate better access and use of data, tool and process adoption, confidence with data, good data culture, processes to encourage good data usage and much more.  Links mentioned in the show Rocket SoftwareWhat Does Democratizing Data Mean? Unlocking the Power of Data CulturesDemocratizing Data in Large Enterprises[Course] Introduction to Data Culture

Welcome back to another podcast episode of Data Unchained! Our guest today is Ariel Pohoryles, Head of Product Marketing at #Rivery. In this episode, Ariel and I dived into the evolution of the #data #market, interacting with data in SQL and Python, and the importance of full visibility of the entire #datapipeline.

marketing #datascience #datatools

Cyberpunk by jiglr | https://soundcloud.com/jiglrmusic Music promoted by https://www.free-stock-music.com Creative Commons Attribution 3.0 Unported License https://creativecommons.org/licenses/by/3.0/deed.en_US Hosted on Acast. See acast.com/privacy for more information.

The 2nd edition of Consumer Behaviour and Analytics provides a consumer behaviour textbook for the new marketing reality. In a world of Big Data, machine learning and artificial intelligence, this key text reviews the issues, research and concepts essential for navigating this new terrain.

Send us a text Welcome to the cozy corner of the tech world where ones and zeros mingle with casual chit-chat. Datatopics Unplugged is your go-to spot for relaxed discussions around tech, news, data, and society. Dive into conversations that should flow as smoothly as your morning coffee (but don't), where industry insights meet laid-back banter. Whether you're a data aficionado or just someone curious about the digital age, pull up a chair, relax, and let's get into the heart of data, unplugged style! In today's episode: Biz corner AI regulation race https://www.aisnakeoil.com/p/what-the-executive-order-means-forhttps://www.ft.com/content/e0574e79-d723-4d94-9681-fae22648e3adhttps://www.washingtonpost.com/technology/2023/10/25/artificial-intelligence-executive-order-biden/https://www.wired.com/story/joe-biden-wants-us-government-algorithms-tested-for-potential-harm-against-citizensTech corner Adoption of the business source license (BSL)https://www.hashicorp.com/blog/hashicorp-adopts-business-source-licensehttps://www.getdbt.com/blog/licensing-dbthttps://mariadb.com/bsl-faq-mariadb/https://github.com/MaterializeInc/materialize/blob/main/LICENSECompanies responding to HashiCorp's move to BSLhttps://spacelift.io/blog/spacelift-latest-statement-on-hashicorp-bslOpenTofu & HashiCorp's OSS workhttps://opentofu.org/https://medium.com/@andrewhertog/contributing-to-terraform-vs-opentofu-26779d480c7f?sk=5343d4a76b390833af621905c858777bCyber Resilience Act might kill open-source altogetherhttps://www.linuxfoundation.org/blog/understanding-the-cyber-resilience-acthttps://github.blog/2023-07-12-no-cyber-resilience-without-open-source-sustainability/https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex:52022PC0454OSS companies - is it a sustainable way of doing open source?https://bun.sh/blog/bun-v1.0https://astral.sh/https://pydantic.dev/https://duckdblabs.com/We haven't figured out OSS sustainability yet, but the BSL comes close.https://curl.se/docs/security.htmlhttps://xkcd.com/2347/Intro music courtesy of fesliyanst

We talked about:

Lera’s background Lera’s move from Ukraine to Germany The transition from Marketing to Product Ownership The importance of communication and one-on-ones The role of Product Owner Utilizing Scrum as a Product Owner Building teams and cross-functionality Lera’s experience learning about search The importance of having both technical knowledge and business context Open developer positions at AUTODOC What experience Lera came to AUTODOC with How marketing skills helped Lera in her current role Lera’s resource recommendations Everything is possible

Links:

Post: https://www.linkedin.com/posts/leracaiman_elasticsearch-ecommerce-activity-7106615081588674560-5WQO

Free ML Engineering course: http://mlzoomcamp.com Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

In the dbt Labs on dbt series, you get a behind-the-scenes look at how dbt Labs uses data. Learn how dbt Labs thinks about the role of data, how data developers collaborate with business leaders, and the technical decisions we’ve made in our own dbt project.

In this session, Mark Matteucci, Enterprise Systems Architect at dbt Labs, and Mary Wleklinski, Senior Director of Revenue Marketing at dbt Labs share the rising importance of data in a challenging economic environment. You'll learn about a variety of dbt use cases across finance, G&A, and marketing and how we use data to solve tough business challenges. Learn about dbt Labs' journey and leave with ideas that you can implement in your dbt project today.

Register for Coalesce at https://coalesce.getdbt.com

Marketing is a well-established field, yet there is still a massive gulf between CEO and CMO expectations. If CMOs are still trying to get traction with their CEOs, what hope do Chief Data Officers have? I rant about this.

WSJ article: Divide Between CMOs and CEOs is Growing: https://www.wsj.com/articles/divide-between-cmos-and-ceos-is-growing-research-finds-a73374f4?st=bcayeo7wc9j18fd&reflink=desktopwebshare_permalink

In the dbt Labs on dbt series, get a behind-the-scenes look at how dbt Labs uses data. You’ll learn how dbt Labs thinks about the role of data, how data developers collaborate with business leaders, and the technical decisions we’ve made in our own dbt project.

In this session, Danny Lambert, Director of Marketing Operations at dbt Labs, shares how he partnered with marketing leaders and the data team to deliver clean, simple reporting that help everyone from campaign managers to the executive team make better decisions about marketing spend and optimization. Jakki Jakaj, Associate Manager of Integrated Marketing at dbt Labs, shares how her team uses this data every day to optimize marketing campaigns

Register for Coalesce at https://coalesce.getdbt.com/

On today’s episode, we’re joined by Lee Blakemore, Chief Executive Officer of Introhive, the leading Client Intelligence Platform. We talk about:  Building a culture that’s data-oriented & encouraging autonomy Resisting unproductive fads, such as pushing for metrics that don't correlate to profit & revenueBeing pragmatic – without killing opportunitiesAmusing anecdotes about the early cloud daysIf startups should invest more in marketing or sales

Every data team knows the importance of partnering with stakeholders across the business. In this session, Deputy's director of data shares how his team improved data modeling speed and accuracy, which led to more effective growth marketing initiatives and better sales conversion rates—which were essential for sourcing and forecasting new business.

Speaker: Huss Afzal, Data Director, Deputy

Register for Coalesce at https://coalesce.getdbt.com

Join Avery Smith with special guest Tim Beecher to discuss his incredible journey from a locksmith to a successful data analyst in this inspiring episode of the Data Career Podcast.

Discover how Tim's determination, networking skills, and project-based learning led him to a fulfilling career and learn valuable tips on how to make a similar transformation in your life.

Don't miss this opportunity to gain insights and practical advice from Tim's experiences - tune in now!

💼 Connect with Tim Beecher 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:

(09:27) - Why data analytics

(10:18) - Get paid to learn data

(24:14) - Using your network to land a job

(36:04) - Day in the life as a Marketing Data analyst

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

TOCA Football, the largest operator of indoor soccer centers in North America, leverages accurate data to power analytics for over 30 training centers, providing everything from operational insights for executives to ball-by-ball analysis.

In 2020, the team adopted a cloud-native data stack with dbt to scale analytics enablement for the go-to-market org, including the company’s finance, strategy, operations, and marketing teams. By 2022, their lean team of four was struggling to gain visibility into the health and performance of their dbt models. So, what was the TOCA team to do? Two words: data observability.

In this talk, Sam Cvetkovski, Director, Data & Analytics discusses how TOCA built their larger data observability strategy to reduce model bloat, increase data accuracy, and boost stakeholder satisfaction with their team’s data products. She shares her biggest “aha!” moments, key challenges, and best practices for teams getting started on their dbt reliability journeys.

Speakers: Sam Cvetkovski, Director, Data & Analytics, TOCA Football; Barr Moses, Co-Founder & CEO, Monte Carlo

Register for Coalesce at https://coalesce.getdbt.com

During the data team's short tenure (2.5 years) at ClickUp, they have built and scaled a fully modern data stack and implemented a warehouse-first data strategy. ClickUp's data is comprised of thousands of dbt models and upstream/downstream integrations with nearly every software at ClickUp. ClickUp uses dbt Cloud and Snowflake to power dozens of downstream systems with audience creation, marketing optimization, predictive customer lifecycle ML, a PLG/PLS motion, and much more. This session covers the foundational principles ClickUp follows and how warehouse-first thinking has unlocked tremendous value for ClickUp.

Speakers: Marc Stone, Head of Data, ClickUp

Register for Coalesce at https://coalesce.getdbt.com

Leveraging the power of RudderStack and dbt, Canadian Football League’s (CFL) data team abstracts the complexity of data in the warehouse and provides their marketing team with highly targeted audiences across a large variety of platforms and data sources. During this session we’ll hear how CFL went from manually sharing CSV files to modeling targeted segments, directly focused on OKRs, in their warehouse.

Speakers: Eric Dodds, Head of Product Marketing, RudderStack; Dave Musambi, Sr. Director, Business Intelligence, Canadian Football League

Register for Coalesce at https://coalesce.getdbt.com

No one believes the marketing attribution model. Companies want clarity about how to attract and land high value customers. It’s easy to get lost trying to build an attribution model that reflects reality without lying or oversimplification. What if there was a better way? This session helps any analyst, analytics engineer, or marketing professional that has ever had to grapple with attribution or conversion analytics.

Speaker: Amanda Fioritto, Analytics Engineer, Hex

Register for Coalesce at https://coalesce.getdbt.com

In the dbt Labs on dbt series, you get a behind-the-scenes look at how dbt Labs uses data. You’ll learn how dbt Labs thinks about the role of data, how data developers collaborate with business leaders, and the technical decisions we’ve made in our own dbt project.

In this session, Brandon Thomson, Analytics Lead at dbt Labs, digs deeper into the technical details of the Campaign 360, a powerful marketing analytics asset used by every member of the marketing team. You'll learn about the technical decisions made during the build of this product and explore the finished asset.

Join this session to learn about dbt Labs' journey and leave with ideas that you can implement in your dbt project today.

Speaker: Brandon Thomson, Analytics Lead, dbt Labs

Register for Coalesce at https://coalesce.getdbt.com