Many organizations rely on complex cloud data architectures that create silos between applications, users and data. This fragmentation makes it difficult to access accurate, up-to-date information for analytics, often resulting in the use of outdated data. Enter the lakehouse, a modern data architecture that unifies data, AI, and analytics in a single location.

This session explores why the lakehouse is the best data warehouse, featuring success stories, use cases and best practices from industry experts. You'll discover how to unify and govern business-critical data at scale to build a curated data lake for data warehousing, SQL and BI. Additionally, you'll learn how Databricks SQL can help lower costs and get started in seconds with on-demand, elastic SQL serverless warehouses, and how to empower analytics engineers and analysts to quickly find and share new insights using their preferred BI and SQL tools such as Fivetran, dbt, Tableau, or Power BI.

Talk by: Miranda Luna and Cyrielle Simeone

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

As the data landscape evolves, organizations are seeking innovative solutions that provide enhanced value and scalability without exploding costs. In this session, we will explore the exciting frontier of the Modern Data Stack on Databricks Lakehouse, a game-changing alternative to traditional Data Cloud offerings. Learn how Databricks Lakehouse empowers you to harness the full potential of Fivetran, dbt, and Tableau, while optimizing your data investments and delivering unmatched performance.

We will showcase real-world demos that highlight the seamless integration of these modern data tools on the Databricks Lakehouse platform, enabling you to unlock faster and more efficient insights. Witness firsthand how the synergy of Lakehouse and the Modern Data Stack outperforms traditional solutions, propelling your organization into the future of data-driven innovation. Don't miss this opportunity to revolutionize your data strategy and unleash unparalleled value with the lakehouse revolution.

Talk by: Kyle Hale and Roberto Salcido

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

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

Summary

Data has been one of the most substantial drivers of business and economic value for the past few decades. Bob Muglia has had a front-row seat to many of the major shifts driven by technology over his career. In his recent book "Datapreneurs" he reflects on the people and businesses that he has known and worked with and how they relied on data to deliver valuable services and drive meaningful change.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderStack Profiles. RudderStack Profiles takes the SaaS guesswork and SQL grunt work out of building complete customer profiles so you can quickly ship actionable, enriched data to every downstream team. You specify the customer traits, then Profiles runs the joins and computations for you to create complete customer profiles. Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstack Your host is Tobias Macey and today I'm interviewing Bob Muglia about his recent book about the idea of "Datapreneurs" and the role of data in the modern economy

Interview

Introduction How did you get involved in the area of data management? Can you describe what your concept of a "Datapreneur" is?

How is this distinct from the common idea of an entreprenur?

What do you see as the key inflection points in data technologies and their impacts on business capabilities over the past ~30 years? In your role as the CEO of Snowflake you had a first-row seat for the rise of the "modern data stack". What do you see as the main positive and negative impacts of that paradigm?

What are the key issues that are yet to be solved in that ecosmnjjystem?

For technologists who are thinking about launching new ventures, what are the key pieces of advice that you would like to share? What do you see as the short/medium/long-term impact of AI on the technical, business, and societal arenas? What are the most interesting, innovative, or unexpected ways that you have seen business leaders use data to drive their vision? What are the most interesting, unexpected, or challenging lessons that you have learned while working on the Datapreneurs book? What are your key predictions for the future impact of data on the technical/economic/business landscapes?

Contact Info

LinkedIn

Parting Question

From your perspective, what is the biggest gap in the tooling or technology for data management today?

Closing Announcements

Thank you for listening! Don't forget to check out our other shows. Podcast.init covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning. Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes. If you've learned something or tried out a project from the show then tell us about it! Email [email protected]) with your story. To help other people find the show please leave a review on Apple Podcasts and tell your friends and co-workers

Links

Datapreneurs Book SQL Server Snowflake Z80 Processor Navigational Database System R Redshift Microsoft Fabric Databricks Looker Fivetran

Podcast Episode

Databricks Unity Catalog RelationalAI 6th Normal Form Pinecone Vector DB

Podcast Episode

Perplexity AI

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA Sponsored By: Rudderstack:

Introducing RudderStack Profiles. RudderStack Profiles takes the SaaS guesswork and SQL grunt work out of building complete customer profiles so you can quickly ship actionable, enriched data to every downstream team. You specify the customer traits, then Profiles runs the joins and computations for you to create complete customer profiles. Get all of the details and try the new product today at dataengineeringpodcast.com/rudderstackSupport Data Engineering Podcast

Hear from two guests. First, Zaheera Valani (Sr Director, Engineering at Databricks) on data sharing and Databricks marketplace. Second guest, Taylor Brown (COO and co-founder, Fivetran), discusses cloud data platforms and automating data pulling from thousands of disparate data sources - how Fivetran and Databricks partner. Hosted by Holly Smith (Sr Resident Solutions Architect, Databricks) and Jimmy Obeyeni (Strategic Account Executive, 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

Summary

Business intelligence has gone through many generational shifts, but each generation has largely maintained the same workflow. Data analysts create reports that are used by the business to understand and direct the business, but the process is very labor and time intensive. The team at Omni have taken a new approach by automatically building models based on the queries that are executed. In this episode Chris Merrick shares how they manage integration and automation around the modeling layer and how it improves the organizational experience of business intelligence.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management Truly leveraging and benefiting from streaming data is hard - the data stack is costly, difficult to use and still has limitations. Materialize breaks down those barriers with a true cloud-native streaming database - not simply a database that connects to streaming systems. With a PostgreSQL-compatible interface, you can now work with real-time data using ANSI SQL including the ability to perform multi-way complex joins, which support stream-to-stream, stream-to-table, table-to-table, and more, all in standard SQL. Go to dataengineeringpodcast.com/materialize today and sign up for early access to get started. If you like what you see and want to help make it better, they're hiring across all functions! Your host is Tobias Macey and today I'm interviewing Chris Merrick about the Omni Analytics platform and how they are adding automatic data modeling to your business intelligence

Interview

Introduction How did you get involved in the area of data management? Can you describe what Omni Analytics is and the story behind it?

What are the core goals that you are trying to achieve with building Omni?

Business intelligence has gone through many evolutions. What are the unique capabilities that Omni Analytics offers over other players in the market?

What are the technical and organizational anti-patterns that typically grow up around BI systems?

What are the elements that contribute to BI being such a difficult product to use effectively in an organization?

Can you describe how you have implemented the Omni platform?

How have the design/scope/goals of the product changed since you first started working on it?

What does the workflow for a team using Omni look like?

What are some of the developments in the broader ecosystem that have made your work possible?

What are some of the positive and negative inspirations that you have drawn from the experience that you and your team-mates have gained in previous businesses?

What are the most interesting, innovative, or unexpected ways that you have seen Omni used?

What are the most interesting, unexpected, or challenging lessons that you have learned while working on Omni?

When is Omni the wrong choice?

What do you have planned for the future of Omni?

Contact Info

LinkedIn @cmerrick on Twitter

Parting Question

From your perspective, what is the biggest gap in the tooling or technology for data management today?

Closing Announcements

Thank you for listening! Don't forget to check out our other shows. Podcast.init covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning. Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes. If you've learned something or tried out a project from the show then tell us about it! Email [email protected]) with your story. To help other people find the show please leave a review on Apple Podcasts and tell your friends and co-workers

Links

Omni Analytics Stitch RJ Metrics Looker

Podcast Episode

Singer dbt

Podcast Episode

Teradata Fivetran Apache Arrow

Podcast Episode

DuckDB

Podcast Episode

BigQuery Snowflake

Podcast Episode

The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA Sponsored By: Materialize:

Looking for the simplest way to get the freshest data possible to your teams? Because let's face it: if real-time were easy, everyone would be using it. Look no further than Materialize, the streaming database you already know how to use.

Materialize’s PostgreSQL-compatible interface lets users leverage the tools they already use, with unsurpassed simplicity enabled by full ANSI SQL support. Delivered as a single platform with the separation of storage and compute, strict-serializability, active replication, horizontal scalability and workload isolation — Materialize is now the fastest way to build products with streaming data, drastically reducing the time, expertise, cost and maintenance traditionally associated with implementation of real-time features.

Sign up now for early access to Materialize and get started with the power of streaming data with the same simplicity and low implementation cost as batch cloud data warehouses.

Go to materialize.comSupport Data Engineering Podcast

Fivetran and dbt Cloud continue to gain traction and popularity among some of the most innovative companies, and for good reason. When combined, Fivetran and dbt Cloud provide an automated, performant, end-to-end ELT pipeline. Join our session where Nikolay Voronchikhin will walk us through Cisco’s journey to building a successful data stack with Fivetran and dbt Cloud. Discover best practices to maximize this powerful combination in your business.

Check the slides here: https://docs.google.com/presentation/d/1-rPuzq0om7ePXXcXFd4lBi72L5svZHNjkx0RWLGgUo8/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

for a few use cases like static and passive data catalogs. However, active metadata can be the key to unlock a variety of use cases, acting as the glue that binds together our diverse modern data stacks (e.g. dbt, Snowflake, Fivetran, Databricks, Looker, and Tableau) and diverse teams (e.g. analytics engineers, data analysts, data engineers, and business users)! At Atlan, we’ve worked closely with modern data teams like WeWork, Plaid, PayU, SnapCommerce, and Bestow. In this session, we’ll lay out all our learnings about how real-life data teams are using metadata to drive powerful use cases like column-level lineage, programmatic governance, root cause analysis, proactive upstream alerts, dynamic pipeline optimization, cost optimization, data deprecation, automated quality control, metrics management, and more. P.S. We’ll also reveal how active metadata and the dbt Semantic Layer can work together to transform the way your team works with metrics!

Check the slides here: https://docs.google.com/presentation/d/1xrC9yhHOQ00qWt-gVlgbakRELg2FzEPt-RwMsUWzdZA/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Welcome to the dbt Package show! Have you ever wondered how Fivetran approaches building dbt packages? Well, put on your aprons, because the Fivetran team is going to give you a glimpse at their recipe for building packages with dbt from 0 release to implementation. Sheri Nguyen of Fivetran will show you:

• How they leverage the dbt Community to get the right ingredients for our packages and plan our roadmap for end state package models

• Their methodologies and standards for preparing ingredients for our data models to provide flexibility for all our users

• How they combine everything together and cook up our models for our dbt packages

Finally, after all the cooking is done, the best part is sharing what you've made with your friends and family. Sheri will also show you how different companies use our various packages and how you can contribute! This talk will benefit those who want to leverage Fivetran's dbt packages, understand why we apply certain modeling practices, and understand how we continually iterate on these packages. Additionally, this session will be beneficial for those who also want to be dbt package maintainers and understand how they can contribute future packages.

Check the slides here: https://docs.google.com/presentation/d/1QKvnxnfRBrZKOnBGwXkLnc-EjLS4S3mbSe59kjHhMos/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Let’s get down to business! Most business users don't want to be bogged down in the data modeling and complexities that us data folk work so hard to accomplish and overcome. Instead, business users and leadership members want the dashboards and numbers they care about. In this session, Matthew Hoss (Element Biosciences) shares his four-step approach to modeling and creating turnkey cost dashboards, all sitting on top of a Netsuite/Fivetran/Snowflake/dbt/Tableau data stack, that help business users get the answers they need, quickly.

Check the slides here: https://docs.google.com/presentation/d/1VVZwm2Kloy1aeewqbB--7WfxIifnpIZflx9V8Q2N-x0/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.

Summary Data integration from source systems to their downstream destinations is the foundational step for any data product. With the increasing expecation for information to be instantly accessible, it drives the need for reliable change data capture. The team at Fivetran have recently introduced that functionality to power real-time data products. In this episode Mark Van de Wiel explains how they integrated CDC functionality into their existing product, discusses the nuances of different approaches to change data capture from various sources.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. Go to dataengineeringpodcast.com/linode today and get a $100 credit to launch a database, create a Kubernetes cluster, or take advantage of all of their other services. And don’t forget to thank them for their continued support of this show! You wake up to a Slack message from your CEO, who’s upset because the company’s revenue dashboard is broken. You’re told to fix it before this morning’s board meeting, which is just minutes away. Enter Metaplane, the industry’s only self-serve data observability tool. In just a few clicks, you identify the issue’s root cause, conduct an impact analysis⁠—and save the day. Data leaders at Imperfect Foods, Drift, and Vendr love Metaplane because it helps them catch, investigate, and fix data quality issues before their stakeholders ever notice they exist. Setup takes 30 minutes. You can literally get up and running with Metaplane by the end of this podcast. Sign up for a free-forever plan at dataengineeringpodcast.com/metaplane, or try out their most advanced features with a 14-day free trial. Mention the podcast to get a free "In Data We Trust World Tour" t-shirt. RudderStack helps you build a customer data platform on your warehouse or data lake. Instead of trapping data in a black box, they enable you to easily collect customer data from the entire stack and build an identity graph on your warehouse, giving you full visibility and control. Their SDKs make event streaming from any app or website easy, and their state-of-the-art reverse ETL pipelines enable you to send enriched data to any cloud tool. Sign up free… or just get the free t-shirt for being a listener of the Data Engineering Podcast at dataengineeringpodcast.com/rudder. Data teams are increasingly under pressure to deliver. According to a recent survey by Ascend.io, 95% in fact reported being at or over capacity. With 72% of data experts reporting demands on their team going up faster than they can hire, it’s no surprise they are increasingly turning to automation. In fact, while only 3.5% report having current investments in automation, 85% of data teams plan on investing in automation in the next 12 months. 85%!!! That’s where our friends at Ascend.io come in. The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java. Ascend automates workloads on Snowflake, Databricks, BigQuery, and open source Spark, and can be deployed in AWS, Azure, or GCP. Go to dataengineeringpodcast.com/ascend and sign up for a free trial. If you’re a data engineering podcast listener, you get credits worth $5,000 when you become a customer. Your host is Tobias Macey and today I’m interviewing Mark Van de Wiel about Fivetran’s implementation of chang

Send us a text In this podcast we introduce you to the wonders of Airbyte with Frederik de Smedt. Airbyte is an open-source data pipeline platform that serves as an alternative to Stitch data and Fivetran.

Check out more about Airbyte here: GithubOfficial websiteTour de Tools is brought to you by Dataroots Music from Uppbeat (free for Creators!)thumbnail: the official logo of airbyte

The time and attention of skilled engineers are some of the most constrained, valuable resources at Red Digital, a marketing agency embedded within Red Ventures. Acknowledging that constraint, the team at Red Digital has taken a deliberate, product-first approach to modernize and democratize their data platform. With the help of modern tools like Databricks, Fivetran, dbt, Monte Carlo, and Airflow, Red Digital has increased its development velocity and the size of the available talent pool to continue to grow the business.

This talk will walk through some of the key challenges, decisions, and solutions that the Red Digital team has made to build a suite of parallel data stacks capable of supporting its growing business.

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

With serverless SQL compute and built-in governance, Databricks SQL lets every analyst and analytics engineer easily ingest, transform, and query the freshest data directly on your data lake, using their tools of choice like Fivetran, dbt, PowerBI or Tableau, and standard SQL. There is no need to move data to another system. All this takes place at virtually any scale, at a fraction of the cost of traditional cloud data warehouses. Join this session for a deep dive into how Databricks SQL works under the hood, and see a live end-to-end demo of the data and analytics on Databricks from data ingestion, transformation, and consumption, using the modern data stack along with Databricks SQL.

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

Most organizations routinely operate their business with complex cloud data architectures that silo applications, users and data. As a result, there is no single source of truth of data for analytics, and most analysis is performed with stale data. To solve these challenges, the lakehouse has emerged as the new standard for data architecture, with the promise to unify data, AI and analytic workloads in one place. In this session, we will cover why the data lakehouse is the next best data warehouse. You will hear from the experts success stories, use cases, and best practices learned from the field and discover how the data lakehouse ingests, stores and governs business-critical data at scale to build a curated data lake for data warehousing, SQL and BI workloads. You will also learn how Databricks SQL can help you lower costs and get started in seconds with instant, elastic SQL serverless compute, and how to empower every analytics engineers and analysts to quickly find and share new insights using their favorite BI and SQL tools, like Fivetran, dbt, Tableau or PowerBI.

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

Welcome data teams and executives in Media and Entertainment! This year’s Data + AI Summit is jam-packed with talks, demos and discussions focused on how organizations are using data to personalize, monetize and innovate the audience experience. To help you take full advantage of the Communications, Media & Entertainment experience at Summit, we’ve curated all the programs in one place.

Highlights at this year’s Summit:

Communications, Media & Entertainment Forum: Our capstone event for the industry at Summit featuring fireside chats and panel discussions with HBO, Warner Bros. Discovery, LaLiga, and Condé Nast followed by networking. More details in the agenda below. Industry Lounge: Stop by our lounge located outside the Expo floor to meet with Databricks’ industry experts and see solutions from our partners including Cognizant, Fivetran, Labelbox, and Lovelytics. Session Talks: Over 10 technical talks on topics including Telecommunication Data Lake Management at AT&T, Data-driven Futbol Analysis from LaLiga, Improving Recommendations with Graph Neural Networks from Condé Nast, Tools for Assisted Spark Version Migrations at Netflix, Real-Time Cost Reduction Monitoring and Alerting with HuuugeGames and much more.

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

This talk tells the story of how we have approached data and analytics as a startup at Preset and how the need for a data orchestrator grew over time. Our stack is (loosely) Fivetran/Segment/dbt/BigQuery/Hightouch, and we finally got to a place where we suffer quite a bit from not having an orchestrator and are bringing in Airflow to address our orchestration needs. This talk is about how startups approach solving data challenges, the shifting role of the orchestrator in the modern data stack, and the growing need for an orchestrator as your data platform becomes more complex.