Fivetran helps Enterprise and Commercial companies improve the efficiency of their data movement, infrastructure, and analysis by providing a secure, scalable platform for high-volume data movement. In this fireside chat, we will dive into the pain points that drove Catalyst, a cloud-based platform that helps software companies grow revenue with advanced insights and workflows that strengthen customer adoption, retention, expansion and advocacy, to begin their search for a partnership that would automate and simplify data management along with the pivotal success driven by the implementation of Fivetran and Databricks. 

Discover how together Fivetran and Databricks:

• Deliver scalable, real-time analytics to customers with minimal configuration and centralize customer data into customer success tools.
• Improve Catalyst’s visibility into customer health, opportunities, and risks across all teams.
• Turn data into revenue-driving insights around digital customer behavior with improved targeting and Ai/ Machine learning.
• Provide a robust and scalable data infrastructure that supports Catalyst’s growing data needs, with improvements in data availability, data quality, and overall efficiency in data operations.

Talk by: Edward Chiu and Lauren Schwartz

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

In this episode of Data Career Podcast, I explore Data Analytics vs Data Science, highlighting key differences and stress the fluidity between data science and analytics. Don't miss it!

📩 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: (00:56) - Predictive Analytics: Foreseeing the Future 🔮📈 (01:43) - Diagnostic Analytics: Unraveling "Why" 🕵️‍♂️🔍 (02:10) - Analytics in Book Sales 📚📊 (03:09) - Data Scientists: Masters of Prediction 🧠🎯 (03:56) - Decoding Data Analytics vs. Data Science 🗝️💻 (05:26) - Gateway to Success: Landing a Data Job 🚪💼

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

Learn how Rec Room, a fast-growing augmented and virtual reality software startup, is saving 50% of their engineering team's time by using Databricks and RudderStack to power real-time analytics and insights for their 85 million gaming customers.

In this session, you will walk through a step-by-step explanation of how Rec Room set up efficient processes for ingestion into their data lakehouse, transformation, reverse-ETL and product analytics. You will also see how Rec Room is using incremental materialization of tables to save costs and establish an uptime of close to 100%.

Talk by: Albert Hu and Lewis Mbae

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

Get ready to accelerate your data and AI collaboration game with the Databricks product team. Join us as we build the next generation of secure data collaboration capabilities on the lakehouse. Whether you're just starting your data sharing journey or exploring advanced data collaboration features like data cleanrooms, this session is tailor-made for you.

In this demo-packed session, you'll discover what’s new in Delta Sharing including dynamic and materialized views for sharing, sharing other assets such as notebooks, ML models, new Delta Sharing open source connectors for the tools of your choice, and updates to Databricks cleanroom. Learn how lakehouse is the perfect solution for your data and AI collaboration requirements, across clouds, regions and platforms and without any vendor lock-in. Plus, you'll get a peek into our upcoming roadmap. Ask any burning questions you have for our expert product team as they build a collaborative lakehouse for data, analytics and AI.

Talk by: Erika Ehrli, Kelly Albano, and Xiaotong Sun

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

The widely-adopted combination of Power BI and Databricks has been a game-changer in providing a comprehensive solution for modern data analytics. In this session, you’ll learn how self-service analytics combined with the Databricks Lakehouse Platform can allow users to make better-informed decisions by unlocking insights hidden in complex data. We’ll provide practical examples of how organizations have leveraged these technologies together to drive digital transformation, lower total cost of ownership (TCO), and increase revenue. By the end of the presentation and demo, you’ll understand how Power BI and Databricks can help drive real-time insights at scale for organizations in any industry.

Talk by: Bob Zhang and Mahesh Prakriya

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

Chesapeake Regional Information System for our Patients (CRISP), a nonprofit healthcare information exchange (HIE), initially partnered with Slalom to build a Databricks data lakehouse architecture in response to the analytics demands of the COVID-19 pandemic, since then they have expanded the platform to additional use cases. Recently they have worked together to engineer streaming data pipelines to process healthcare messages, such as HL7, to help CRISP become vendor independent.

This session will focus on the improvements CRISP has made to their data lakehouse platform to support streaming use cases and the impact these changes have had for the organization. We will touch on using Databricks Auto Loader to efficiently ingest incoming files, ensuring data quality with Delta Live Tables, and sharing data internally with a SQL warehouse, as well as some of the work CRISP has done to parse and standardize HL7 messages from hundreds of sources. These efforts have allowed CRISP to stream over 4 million messages daily in near real-time with the scalability it needs to continue to onboard new healthcare providers so it can continue to facilitate care and improve health outcomes.

Talk by: Andy Hanks and Chris Mantz

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

Get ready to take a deep dive into Unity Catalog and explore how it can simplify data, analytics and AI governance across multiple clouds. In this session, take a deep dive into Unity Catalog and the expert Databricks team will guide you through a hands-on demo, showcasing the latest features and best practices for data governance. You'll learn how to master Unity Catalog and gain a practical understanding of how it can streamline your analytics and AI initiatives. Whether you're migrating from Hive Metastore or just looking to expand your knowledge of Unity Catalog, this session is for you. Join us for a practical, hands-on deep dive into Unity Catalog and learn how to achieve seamless data governance while following best practices for data, analytics and AI governance.

Talk by: Zeashan Pappa and Ifigeneia Derekli

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksin

Data engineering is a requirement for any data, analytics or AI workload. With the increased complexity of data pipelines, the need to handle real-time streaming data and the challenges of orchestrating reliable pipelines, data engineers require the best tools to help them achieve their goals. The Databricks Lakehouse Platform offers a unified platform to ingest, transform and orchestrate data and simplifies the task of building reliable ETL pipelines.

This session will provide an introductory overview of the end-to-end data engineering capabilities of the platform, including Delta Live Tables and Databricks Workflows. We’ll see how these capabilities come together to provide a complete data engineering solution and how they are used in the real world by organizations leveraging the lakehouse turning raw data into insights.

Talk by: Jibreal Hamenoo and Ori Zohar

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

Join Databricks' Distinguished Principal Engineer Michael Armbrust for a technical deep dive into how Delta Live Tables (DLT) reduces the complexity of data transformation and ETL. Learn what’s new; what’s coming; and how to easily master the ins-and-outs of DLT.

Michael will describe and demonstrate:

• What’s new in Delta Live Tables (DLT) - Enzyme, Enhanced Autoscaling, and more
• How to easily create and maintain your DLT pipelines
• How to monitor pipeline operations
• How to optimize data for analytics and ML
• Sneak Peek into the DLT roadmap

Talk by: Michael Armbrust

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

Join the Unity Catalog product team and dive into the cutting-edge world of data, analytics and AI governance. With Unity Catalog’s unified governance solution for data, analytics, and AI on any cloud, you’ll discover the latest and greatest enhancements we’re shipping, including fine-grained governance with row/column filtering, new enhancements with automated data lineage and governance for ML assets.

In this demo-packed session, You’ll learn how new capabilities in Unity Catalog can further simplify your data governance and accelerated analytics and AI initiatives. Plus, get an exclusive sneak peek at our upcoming roadmap. And don’t forget, you’ll have the chance to ask the product teams themselves any burning questions you have about the best governance solution for the lakehouse. Don’t miss out on this exciting opportunity to level up your data game with Unity Catalog.

Talk by: Paul Roome

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

The explosive growth in volume and varieties of data generated by the seemingly endless arrays of digital systems and applications is rapidly elevating the importance of being able to utilize data; in fact, data analytic literacy is becoming as important now, at the onset of the Digital Era, as rudimentary literacy and numeracy were throughout the Industrial Era. And yet, what constitutes data analytic literacy is poorly understood. To some, data analytic literacy is the ability to use basic statistics, to others it is data science ‘light’, and to still others it is just general familiarity with common data analytic outcomes. Exploring the scope and the structure of rudimentary data analytic competencies is at the core of this book which takes the perspective that data analytics is a new and distinct domain of knowledge and practice. It offers application-minded framing of rudimentary data analytic competencies built around conceptually sound and practically meaningful processes and mechanics of systematically transforming messy and heterogeneous data into informative insights. Data Analytic Literacy is meant to offer an easy-to-follow overview of the critical elements of the reasoning behind basic data manipulation and analysis approaches and steps, coupled with the commonly used data analytic and data communication techniques and tools. It offers an all-inclusive guide to developing basic data analytic competencies.

With the rapid rise of graph databases, organizations are now implementing advanced analytics and machine learning solutions to help drive business outcomes. This practical guide shows data scientists, data engineers, architects, and business analysts how to get started with a graph database using TigerGraph, one of the leading graph database models available. You'll explore a three-stage approach to deriving value from connected data: connect, analyze, and learn. Victor Lee, Phuc Kien Nguyen, and Alexander Thomas present real use cases covering several contemporary business needs. By diving into hands-on exercises using TigerGraph Cloud, you'll quickly become proficient at designing and managing advanced analytics and machine learning solutions for your organization. Use graph thinking to connect, analyze, and learn from data for advanced analytics and machine learning Learn how graph analytics and machine learning can deliver key business insights and outcomes Use five core categories of graph algorithms to drive advanced analytics and machine learning Deliver a real-time 360-degree view of core business entities, including customer, product, service, supplier, and citizen Discover insights from connected data through machine learning and advanced analytics

Mark and Cris take stock of the economy’s performance so far this year, and consider what surprised them (think the job market), what they got right (think weaker house prices), and what they got wrong (think the banking crisis). They also look forward and discuss what people are overly considered about, and what they should be more worried about.  Where’s Marisa? 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.

Anna Nerezova is a Digital Marketing and Cloud Transformation Consultant with 15 years of experience in data, analytics and optimization. She has built innovative solutions using Google Cloud to solve problems in the media and entertainment, tech, health and non-profit industries Anna is a Google Cloud Engineer Scholar, and is on the 100 Women in Analytics list by Google Analytics. She is also a Google Developer Group NYC lead and a mentor for the Northeast, and a proud Women Techmakers Ambassador.

Anna is passionate about using the latest AI/ML technologies to provide solutions and bring growth and better experience for all users. She is a strong advocate for diversity and inclusion, and is committed to helping underrepresented groups become entrepreneurs and financially independent.

🕵️‍♂️ Curious about the mysterious hiring process of a data career? Find out how Megan McGuire narrows down candidates and assesses skills in the podcast. Get insider knowledge on code assessments, interviews, and what it takes to land the dream data role! 💪📈

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

🏫 Check out my 10-week data analytics bootcamp

Timestamps:

(02:14) - The Value of Junior Analysts

(12:12) - Curiosity and Problem Solving in Data Analytics

(21:46) - Be the perfect candidate for specific company rather than a pretty good candidate

(24:15) - How drive, experience and upskilling set up interviewee success

(28:59) - Show off your skills with your Tableau Public or GitHub Profile

(36:53) - Rejections aren't necessarily your fault

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

Hear from two guests. First, Simon Whiteley (co-owner, Advancing Analytics) on his reaction to industry announcements, where he sees the industry heading, and an introduction to his community at Advancing Analytics. Second guest, Matteo Quattrocchi (Director - Policy, EMEA at BSA | The Software Alliance) on the current state of AI policies - by international governments, global committees, and individual companies.. Hosted by Ari Kaplan (Head of Evangelism, Databricks) and Pearl Ubaru (Sr Technical Marketing Engineer, Databricks)

Hear from three guests. Harrison Chase (CEO, LangChain) and Nicolas Palaez (Sr. Technical Marketing Manager, Databricks) on LLMs and generative AI. Third guest, Drew Banin (co-founder, dbt Labs), discusses analytics engineering workflow with his company dbt Labs, how he started the company, and how they provide value with the Databricks partnership. Hosted by Ari Kaplan (Head of Evangelism, Databricks) and Pearl Ubaru (Sr Technical Marketing Engineer, Databricks)

Connect with us: Website: https://databricks.com Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/databricks Instagram: https://www.instagram.com/databricksinc Facebook: https://www.facebook.com/databricksinc

The stellar June CPI inflation report is top of mind for Mark, Cris and Bernard.  The report arguably couldn’t have been better, as the conversation makes clear.  The podcast then turns to a discussion of whether the worst is over for the troubled single family housing market with Lance Lambert, the real estate editor for Fortune. No one has a better pulse of the market than Lance. For more on Lance Lambert, click here or follow him on twitter @NewsLambert 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.

In this episode, Marijn Markus & I talked about what it is ACTUALLY like being in the data field, how he transitioned from social science to data science, & discuss some real-world data use cases.

Marijn also shared his experience managing data teams, what makes a good junior hire, why you might not need machine learning, & much, much more.

You don’t want to miss this episode!

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

🏫 Check out my 10-week data analytics bootcamp

Connect with Marijn: https://www.linkedin.com/in/marijnmarkus/

Timestamps:

(4:40) - Diverse backgrounds matter for programming and stats! (17:42) - Model explanations matter for business (21:00)- The real reason why generative AI became big in December (25:24) - Focus on what you know, not what you don't know (30:14) - You can't control the interview session? Think again!

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

Bob Muglia likely needs no introduction. The former CEO of Snowflake led the company during its early, transformational years after a long career at Microsoft and Juniper.  Bob recently released the book The Datapreneurs about the arc of innovation in the data industry, starting with the first relational databases all the way to the present craze of LLMs and beyond. In this conversation with Tristan and Julia, Bob shares insights into the future of data engineering and its potential business impact while offering a glimpse into his professional journey.  For full show notes and to read 6+ 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.