To unlock all the competitive advantage Databricks offers your organization, you might need to update your strategy and methodology for the platform. With over 1,000+ Databricks projects completed globally in the last 18 months, we are going to share our insights on the best building blocks to target as you search for efficiency and competitive advantage.

These building blocks supporting this include enterprise metadata and data management services, data management foundation, and data services and products that enable business units to fully use their data and analytics at scale.

In this session, Avanade data leaders will highlight how Databricks’ modern data stack fits Azure PaaS and SaaS (such as Microsoft Fabric) ecosystem, how Unity catalog metadata supports automated data operations scenarios, and how we are helping clients measure modern analytics and governance business impact and value.

Talk by: Alan Grogan and Timur Mehmedbasic

Here’s more to explore: State of Data + AI Report: https://dbricks.co/44i2HBp Databricks named a Leader in 2022 Gartner® Magic QuadrantTM CDBMS: https://dbricks.co/3phw20d

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

ABN AMRO Bank is one of the top leading banks in the Netherlands. It is the third largest bank in the Netherlands by revenue and number of mortgages held within the Netherlands, and has top management support of the objective to become a fully data-driven bank. ABN AMRO started its data journey almost seven years ago and has built a data platform off-premises with Hadoop technologies. This data platform has been used by more than 200 data providers, 150 data consumers, and more than 3000 datasets.

To become a fully digital bank and address the limitation of the on-premises platform requires a future-proof data platform DIAL (digital integration and access layer). ABN AMRO decided to build an Azure cloud-native data platform with the help of Microsoft and Databricks. Last year this cloud-native platform was ready for our data providers and data consumers. Six months ago we started the journey of migrating all the content from the on-premises data platform to the Azure data platform, this was a very large-scale migration and was achieved in six months.

In this session, we will focus on three things: 1. The migration strategy going from on-premises to a cloud-native platform 2. Which Databricks solutions were used in the data platform 3. How the Databricks team assisted in the overall migration

Talk by: Rakesh Singh and Marcel Kramer

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

We designed a scalable Spark Streaming job to manage 100s of millions of prescription-related operations per day at an end-to-end SLA of a few minutes and a lookup time of one second using CosmosDB.

In this session, we will share not only the architecture, but the challenges and solutions to using the Spark Cosmos connector at scale. We will discuss usages of the Aggregator API, custom implementations of the CosmosDB connector, and the major roadblocks we encountered with the solutions we engineered. In addition, we collaborated closely with Cosmos development team at Microsoft and will share the new features which resulted. If you ever plan to use Spark with Cosmos, you won't want to miss these gotchas!

Talk by: Daniel Zafar

Here’s more to explore: Big Book of Data Engineering: 2nd Edition: https://dbricks.co/3XpPgNV The Data Team's Guide to the Databricks Lakehouse Platform: https://dbricks.co/46nuDpI

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

Every year, organizations lose millions of dollars due to equipment failure, unscheduled downtime, or unoptimized supply chains because business and operational data is not integrated. During this session you will hear from experts at Qlik and Databricks on how global luxury automotive manufacturers are accelerating the discovery and availability of complex data sets like SAP. Learn how Qlik, Microsoft, and Databricks together are delivering an integrated solution for global luxury automotive manufacturers that combines the automated data delivery capabilities of Qlik Data Integration with the agility and openness of the Databricks Lakehouse platform and AI on Azure Synpase.

We'll explore how to leverage the IT and OT data convergence to extract the full potential of business-critical SAP data, lower IT costs and deliver real-time prescriptive insights, at scale, for more resilient, predictable, and sustainable supply-chains. Learn how organizations can track and manage inventory levels, predict demand, optimize production and help their organizations identify opportunities for improvements.

Talk by: Matthew Hayes and Bala Amavasai

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/databricksi

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

How can you maximize data collaboration across your organization without having to build integrations between individual applications, systems, and other data sources? Data collaboration architectures that don't depend on integrations aren't a new idea, but they've assumed greater urgency as organizations increasingly struggle to manage the ever-growing numbers of data sources that exist inside their IT estates. In this report, Cinchy cofounders Dan DeMers and Karanjot Jaswal show CIOs, CTOs, CDOs, and other IT leaders how to rethink their organization's approach to data architectures, data management, and data governance. You'll learn about different approaches to creating data platforms that liberate and autonomize data, enable agile data management, apply consistent data access controls, and maximize visibility without requiring application-specific integrations. With this report, you'll discover: Why data integration is often handled piecemeal—combining one app with another rather than integrating all apps together How data collaboration platforms enable data sharing across all apps, systems, and sources without application-specific integrations Four major platforms you can use to make data available to all applications and services: Cinchy, K2View, Microsoft Dataverse, and The Modern Data Company Principles and practices for deploying the data collaboration platform of your choice Dan DeMers is the CEO and cofounder of Cinchy. Karanjot Jaswal is cofounder and CTO of Cinchy.

This book provides detailed guidance around architecting and deploying Power BI reporting solutions, including help and best practices for sharing and security. You’ll find chapters on dataflows, shared datasets, composite model and DirectQuery connections to Power BI datasets, deployment pipelines, XMLA endpoints, and many other important features related to the overall Power BI architecture that are new since the first edition. You will gain an understanding of what functionality each of the Power BI components provide (such as Dataflow, Shared Dataset, Datamart, thin reports, and paginated reports), so that you can make an informed decision about what components to use in your solution. You will get to know the pros and cons of each component, and how they all work together within the larger Power BI architecture. Commonly encountered problems you will learn to handle include content unexpectedly changing while users are in the process of creating reports and building analyses, methods of sharing analyses that don’t cover all the requirements of your business or organization, and inconsistent security models. Detailed examples help you to understand and choose from among the different methods available for sharing and securing Power BI content so that only intended recipients can see it. The knowledge provided in this book will allow you to choose an architecture and deployment model that suits the needs of your organization. It will also help ensure that you do not spend your time maintaining your solution, but on using it for its intended purpose: gaining business value from mining and analyzing your organization’s data. What You Will Learn Architect Power BI solutions that are reliable and easy to maintain Create development templates and structures in support of reusability Set up and configure the Power BI gateway as a bridge between on-premises data sourcesand the Power BI cloud service Select a suitable connection type—Live Connection, DirectQuery, Scheduled Refresh, or Composite Model—for your use case Choose the right sharing method for how you are using Power BI in your organization Create and manage environments for development, testing, and production Secure your data using row-level and object-level security Save money by choosing the right licensing plan Who This Book Is For Data analysts and developers who are building reporting solutions around Power BI, as well as architects and managers who are responsible for the big picture of how Power BI meshes with an organization’s other systems, including database and data warehouse systems.

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

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.

Data and AI are advancing at an unprecedented rate—and while the jury is still out on achieving superintelligent AI systems, the idea of artificial intelligence that can understand and learn anything—an “artificial general intelligence”—is becoming more likely. What does the rise of AI mean for the future of software and work as we know it? How will AI help reinvent most of the ways we interact with the digital and physical world? Bob Muglia is a data technology investor and business executive, former CEO of Snowflake, and past president of Microsoft's Server and Tools Division. As a leader in data & AI, Bob focuses on how innovation and ethical values can merge to shape the data economy's future in the era of AI. He serves as a board director for emerging companies that seek to maximize the power of data to help solve some of the world's most challenging problems. In the episode, Richie and Bob explore the current era of AI and what it means for the future of software. Throughout the episode, they discuss how to approach driving value with large language models, the main challenges organizations face when deploying AI systems, the risks, and rewards of fine-tuning LLMs for specific use cases, what the next 12 to 18 months hold for the burgeoning AI ecosystem, the likelihood of superintelligence within our lifetimes, and more. Links from the show: The Datapreneurs by Bob Muglia and Steve HammThe Singularity is Near by Ray KurzweilIsaac AsimovSnowflakePineconeDocugamiOpenAI/GPT-4The Modern Data Stack

0:00 Opener 01:18- Ali Ghodsi, Databricks 06:53 - Satya Nadella, Microsoft 15:50 Ali Ghodsi, Databricks 20:40 Larry Feinsmith, JP Morgan Chase 41:09 Ali Ghodsi, Databricks 45:07 Matei Zaharia, Databricks 52:31 Weston Hutchins, Databricks 58:36 Ali Ghodsi, Databricks 1:02:05 Naveen Rao, MosaicML 1:12:15 Patrick Wendell, Databricks 1:27:57 Kasey Uhlenhuth, Databricks 1:39:18 Sai Pradhan Ravuru, Jetblue 01:47 Ali Ghodsi, Databricks 1:49:20 Reynold Xin, Databricks 2:05:07 Ali Ghodsi, Databricks 2:09:26 Matei Zaharia, Databricks 2:17:24 Caryl Yuhas, Databricks 2:24:12 Zaheera Valani, Databricks 2:39:55 Wassym Bensaid, Rivian

Panel con profesionales de Microsoft y estudiantes que comparten sus trayectorias y experiencias, con énfasis en el cambio de carrera hacia la tecnología.

Se você nunca participou de algum evento de tecnologia, que atire a primeira pedra. E neste episódio, além de abordar sobre os eventos mais emblemáticos que você já deve ter participado, nossos convidados contam pra gente a importância desses eventos e o poder das comunidades.

Para abordar sobre "Os Melhores Eventos de Tecnologia & Dados", nós da comunidade Data Hackers, chamamos dois especialista em comunidades e eventos de tecnologia, para contar pra gente quais são os aprendizados deste universo tão nostálgico.

Conheçam o Valter Pereira — Tech Community Manager na Hotmart ; e Monique Femme ( nossa mais nova integrante do grupo, que assume a posição de Head de Comunidade no Data Hackers), além de Professora do curso MBA em BI, Marketing Digital e Estratégia Data Driven da PUC-RS e Consultora Independente de Comunidades Digitais.

Conheçam nossos convidados:

Valter Pereira — Tech Community Manager na Hotmart Monique Femme — Professora do curso MBA em BI, Marketing Digital e Estratégia Data Driven da PUCRS / Consultora independente de Comunidades Digitais / Head de Comunidade do Data Hackers.

Links de referências:

Inscreva-se no Hot ‘N Code Conference (use cupom de desconto DATAHACKERS15) — 26,27,28 e 29 de Junho de 2023: https://campaign.hotmart.com/hotncode-conference?utm_medium=email&utm_source=instagram&utm_campaign=br_traffic_meetup_hiperlink_data-hackers Artigo Monique Femme — Acabou a Era dos Medianos: https://www.linkedin.com/pulse/acabou-era-dos-medianos-monique-femme/ Serie na Netflix — The Future — Life After Death ( O futuro — Vida após a Morte): https://www.netflix.com/br-en/title/81123425 Evento de Lançamento do Windows 95 da Microsoft, com Ballmer e Gates dançando: https://www.youtube.com/watch?v=lAkuJXGldrM&ab_channel=TheHirnheiner Lançamento do Iphone pela Apple com Steve Jobs: https://www.youtube.com/watch?v=9ou608QQRq8 Livro Manual Prático de Eventos — Gestão Estratégica Patrocínio e Sustentabilidade: https://www.google.com.br/books/edition/Manual_Pratico_de_Eventos/QmHjBwAAQBAJ?hl=pt-BR&gbpv=1&printsec=frontcover Relembre o evento PAPIS.IO Conheça o evento TDC (thedevconf) Conheça a Campus Party Brasil

Learn the basics of writing SQL scripts. Using Standard SQL as the starting point, this book teaches writing SQL in various popular dialects, including PostgreSQL, MySQL/MariaDB, Microsoft SQL Server, Oracle, and SQLite. The book starts with a general introduction to writing SQL and covers the basic concepts. Author Mark Simon then covers database principles, and how database tables are designed. He teaches you how to filter data using the WHERE clause, and you will work with NULL, numbers, dates, and strings. You will also understand sorting results using the ORDER BY clause, sorting by calculated columns, and limiting the number of results. By the end of the book, you will know how to insert and update data, and summarize data with aggregate functions and groups. Three appendices cover differences between SQL dialects, working with tables, and a crash course in PDO. What You Will Learn Filter, sort, andcalculate data Summarize data with aggregate functions Modify data with insert, update, and delete statements Study design principles in developing a database Who This Book Is For Developers and analysts working with SQL, as well as web developers who want a stronger understanding of working with databases

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.

Visualize Complex Processes with Microsoft Visio is your go-to guide for learning how to effectively create and use process flow diagrams. By using Visio's built-in templates and features, this book enables you to document business processes and workflows clearly and professionally, ensuring better understanding and communication. What this Book will help me do Understand how to select and use flowchart types for visually communicating processes. Learn to navigate Visio's interface and features to efficiently create diagrams. Master integrating process flows with data and other M365 apps for added insights. Discover how to securely store and share diagrams for collaboration. Gain skills to customize templates and create diagrams that meet professional standards. Author(s) David Parker and Senaj Lelic are seasoned experts in business process visualization and Microsoft Visio. They bring years of experience in designing complex workflows and teaching professionals how to use Visio effectively. Their approachable writing style ensures clear guidance, empowering readers to achieve practical outcomes. Who is it for? This book is tailored for managers, analysts, and designers seeking to improve their skills in process visualization. Beginner Visio users will find step-by-step instructions valuable, while advanced users can explore tips for customization and integration. If you aim to enhance clarity in communications through professional diagrams, this book is for you.

ABOUT THE TALK: A thoughtful discussion between AI heavyweights on what to expect in this present age of AI. The moderator will draw on their own personal experience and insight to serve up some awesome queries (#wired).

ABOUT THE SPEAKERS: Gregory Larson is the VP of Engineering at Jasper. He joined the company to build out the organization and invest in making AI a part of every creative's workflow.

In past positions Greg was the head of engineering at Divvy Pay and ObservePoint, and he led development and AI projects at Adobe, Jive/LogMeIn, and Microsoft.

Idan Gazit is a Senior Director of Research at GitHub Next, leading the Developer Experiences team. He is a hybrid designer-developer, and can usually be found geeking out about the Web, data visualization, typography, and color

Barry McCardel is the CEO and co-founder of Hex. In past positions Barry has worked at TrialSpark and Palantir Technologies.

George Mathew is the Managing Director at Insight Partners focused on venture stage investments in AI, ML, Analytics, and Data companies as they are establishing product/market Fit.

He brings 20+ years of experience developing high-growth technology startups including most recently being CEO of Kespry.

Sean Owen is the Principal Specialist for Data Science and ML at Databricks.

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: In this talk, Fedor Zhdanov explains how to combat the concept of drift in ML with crowdsourcing. He shows you how to build complex drift-monitoring systems and human-in-the-loop ML models that can be fully automated. He also shares how this has led him and his team to start building so-called “adaptive ML models”. Learn what they are and how to build and maintain them.

ABOUT THE SPEAKER: Fedor Zhdanov is the Head of AI at Toloka, who had previous roles as Principal Applied Scientist at AWS, Microsoft and Amazon. Fedor has been creating products with R&D in Machine Learning for the last 18+ years. For the last 6 years, he has been focusing on connecting ML and humans in human-in-the-loop processes. His ventures are focused on building responsible state of the art AI-first business solutions with human oversight.

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: In Data Science, the small piece of code that you want to test also needs to take in data, training a model, or evaluating a model, but all of these steps are complicated and consist of many smaller units.

Learn from Dr. Nile Wilson her Software Engineering best practices for testing Data Science Code and some of the common scenarios for data, such as mocking calls or mocking data.

ABOUT THE SPEAKER: Dr. Nile Wilson is a Data Scientist 2 in Industry Solutions Engineering at Microsoft, focused on developing and implementing Machine Learning solutions for enterprise customers. She has worked with interdisciplinary teams across various industries to develop production-ready data science solutions to drive business impact.

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/