To learn more, visit the Databricks Security and Trust Center: https://www.databricks.com/trust

In this session, we will talk about the best practices for setting up Databricks to run at large enterprise scale with thousands of users, departmental security and governance, and end-to-end lineage from ingestion to BI tools. We’ll showcase the power of Unity Catalog and Databricks SQL as the core of your modern data stack and how to achieve both data, environment, and financial governance while empowering your users to quickly find and access the data they need.

Talk by: Siddharth Bhai, Paul Roome, Jeremy Lewallen, and Samrat Ray

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

In this session, we will discuss the foundational changes in the ecosystem, the implications of data insights on marketing, analytics, and measurement, and how companies are coming together to collaborate through data clean rooms in new and exciting ways to power mutually beneficial value for their businesses while preserving privacy and governance.

We will delve into the concept and key features of clean room technology and how they can be used to access more and better data for business intelligence (BI), machine learning (ML), and other data-driven initiatives. By examining real-world use cases of clean rooms in action, attendees will gain a clear understanding of the benefits they can bring to industries like CPG, retail, and media and entertainment. In addition, we will unpack the advantages of using Databricks as a clean room platform, specifically showcasing how interoperable clean rooms can be leveraged to enhance BI, ML and other compute scenarios. By the end of this session, you will be equipped with the knowledge and inspiration to explore how clean rooms can unlock new collaboration opportunities that drive better outcomes for your business and improved experiences for consumers.

Talk by: Matthew Karasick, and Anil Puliyeril

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

Data runs AT&T’s business, just like it runs most businesses these days. Data can lead to a greater understanding of a business and when translated correctly into information can provide human and business systems valuable insights to make better decisions. Unique to AT&T is the volume of data we support, how much of our work that is driven by AI and the scale at which data and AI drive value for our customers and stakeholders.

Our cloud migration journey includes making data and AI more accessible to employees throughout AT&T so they can use their deep business expertise to leverage data more easily and rapidly. We always had to balance this data democratization and desire for speed with keeping our data private and secure. We loved the open ecosystem model of Lakehouse that enables data, BI and ML tools to be seamlessly integrated on a single pane arena; it simplifies the architecture and reduces dependencies between technologies in the cloud. Being clear in our architecture guidelines and patterns was very important to us for our success.

We are seeing more interest from our business unit partners and continuing to build the AI capability AI as a service to support more citizen data scientists. To scale up our Lakehouse journey, we built a Databricks center of excellence (CoE) function in AT&T which today has approximately 1400+ active members, further concentrating existing expertise and resources in ML/AI discipline to collaborate on all things Databricks like technical support, trainings, FAQ’s and best practices to attain and sustain world-class performance and drive business value for AT&T. Join us to learn more about how we process and manage over 10 petabytes of our network Lakehouse with Delta Lake and Databricks.

Databricks Workflows provides unified orchestration for the Lakehouse. Since it was first announced last year, thousands of organizations have been leveraging Workflows for orchestrating lakehouse workloads such as ETL, BI dashboard refresh and ML model training.

In this session, the Workflows product team will cover and demo the latest features and capabilities of Databricks Workflows in the areas of workflow authoring, observability and more. This session will also include an outlook for future innovations you can expect to see in the coming months.

Talk by: Muhammad Bilal Aslam

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

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.

Spreadsheets have been the unsung heroes of the data world for many decades now. Yet, despite their ubiquity and importance, they've seen little disruption or evolution. The grid of cells we interact with today isn't far removed from the ones our predecessors used in the 1980s. However, the winds of change have started to blow. As we stand on the cusp of a new era in data and AI, the humble spreadsheet is poised for transformation. The coming changes could redefine how we interact with data, derive insights, and how we make decisions. The implications are vast given the popularity and dependence we have on spreadsheets, and the potential impacts could ripple through every corner of the professional world.  Hjalmar Gislason is the founder and CEO of GRID, with their main product being a smart spreadsheet with an interactive data visualization layer and integrated AI assistance. Hjalmar previously served as VP of Product Management at Qlik. He was the founder and CEO of DataMarket, founded in 2008 and sold to Qlik in 2014. A career data nerd and entrepreneur, GRID is Hjalmar’s fifth software startup as a founder.  In the episode, Richie and Hjalmar explore the integral role of spreadsheets in today's data-driven world, the limitations of traditional Business Intelligence tools, and the transformative potential of generative AI in the realm of spreadsheets.

Practice making sense of data with IBM’s SPSS Statistics software SPSS Statistics Workbook For Dummies gives you the practice you need to navigate the leading statistical software suite. Data management and analysis, advanced analytics, business intelligence—SPSS is a powerhouse of a research platform, and this book helps you master the fundamentals and analyze data more effectively. You’ll work through practice problems that help you understand the calculations you need to perform, complete predictive analyses, and produce informative graphs. This workbook gives you hands-on exercises to hone your statistical analysis skills with SPSS Statistics 28. Plus, explanations and insider tips help you navigate the software with ease. Practical and easy-to-understand, in classic Dummies style. Practice organizing, analyzing, and graphing data Learn to write, edit, and format SPSS syntax Explore the upgrades and features new to SPSS 28 Try your hand at advanced data analysis procedures For academics using SPSS for research, business analysts and market researchers looking to extract valuable insights from data, and anyone with a hankering for more stats practice.

An annual assessment of the positioning strategies of the leading 21 BI vendors finds a lack of differentiation that makes it difficult for buyers to compare products. In the BI market’s sea of sameness, Qlik is the only vendor that stands out with this clever, memorable position. Published at: https://www.eckerson.com/articles/independent-study-bi-vendor-messaging-shows-lack-of-differentiation

Paul Blankley and Ryan Janssen are the co-founders of Zenlytic. They started a BI company with an LLM-first approach (back before LLM's were insanely cool). We talk about the future of BI, and how LLM's will change the face of data and analytics.

Zenlytic: https://www.zenlytic.com/

Paul's LinkedIn: https://www.linkedin.com/in/paulblankley/

Ryan's LinkedIn: https://www.linkedin.com/in/janssenryan/

If you like this show, give it a 5-star rating on your favorite podcast platform.

Purchase Fundamentals of Data Engineering at your favorite bookseller.

Subscribe to my Substack: https://joereis.substack.com/

“Universal” semantic layer tools introduced in recent years promise to standardize business metrics across the data stack, and eliminate silos of metrics trapped in semantic layers that are limited to specific data sources or BI platforms. This post offers considerations for adopting a universal semantic layer. Published at: https://www.eckerson.com/articles/the-universal-semantic-layer-more-than-enough

Business Analytics, is driven by an increasing demand from the real world. This book reviews advances in data analytics and business intelligence that assists industries in problem-solving exercises, with a view to driving competitive advantage.

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

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

Listen to find out 👆

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

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

🏫 Check out my 10-week data analytics bootcamp

Connect with Avery:

📺 Subscribe on YouTube: youtube.com/c/AverySmithDataCareerJumpstart/videos

🎙 Listen to My Podcast: podcasts.apple.com/us/podcast/data-career-podcast/id1547386535

👔 Connect with me on LinkedIn: linkedin.com/in/averyjsmith/

📸 Instagram: instagram.com/datacareerjumpstart/

🎵 TikTok: tiktok.com/@verydata

Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!

To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more

If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.

👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa

Send us a text Want to be featured as a guest on Making Data Simple? Reach out to us at [[email protected]] and tell us why you should be next.

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

Show Notes 1:22 – Benn’s history7:09 – Tell us how you got to where you are today9:14 – Tell us about Mode12:08 – What is your definition of the Chief Analytics Officer?21:53 – Why do we need another BI tool?24:09 – What’s your secret sauce?27:48 – Where did the name Mode come from?28:41 – How do we use Mode?31:08 – What is you goto market strategy? 32:38 – Any client references?34:58 – “The missing piece in the modern data stack” tell us about thisMode  Email: [email protected] [email protected] Twitter: benn stancil Connect with the Team Producer Kate Brown - LinkedIn. Host Al Martin - LinkedIn and Twitter.  Want to be featured as a guest on Making Data Simple? Reach out to us at [email protected] and tell us why you should be next. The Making Data Simple Podcast is hosted by Al Martin, WW VP Technical Sales, IBM, where we explore trending technologies, business innovation, and leadership ... while keeping it simple & fun.

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

ABOUT THE TALK: Building data tools requires us to not only think about the data team, but also about the people that the data team is serving: business users, or "non-data team people".

This talk will go over how it's super important to consider these two personas when building data tools, but it can also be a bit complicated. We will talk through a few principles we can use to build data products that are great for everyone (not just the data team!)

ABOUT THE SPEAKER: As a product manager with a background in data science, Katie Hindson loves building data products. Currently, she's working at Lightdash, an open-source BI tool that instantly turns your dbt project into a full-stack BI platform. Katie is really interested in the interaction between data teams, their tools, and the rest of the company - because the best data teams are the ones that can help everyone at the company make better decisions, faster.

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: Dashboards sit at the end of a long chain of ever-changing data dependencies. And, it is a very visual process – it is hard to tell if a dashboard is correct without an end user looking at the rendered result. This all adds up to a development process that can be slow and error-prone.

“DataOps” is a new set of code-based patterns and practices that aim to address these challenges. In this talk, Dan Eisenberg does a deep dive on these approaches and demonstrate some ways to integrate DataOps into the BI development lifecycle at Glean.

ABOUT THE SPEAKER: Dan Eisenberg is the VP of Technology at Glean.io, a platform for data visualization and collaboration. Prior to Glean, he was a Senior Director of Engineering at Flatiron Health, where his teams designed and built systems for abstracting data from unstructured medical records at scale.

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: This talk explains what the control plane of data looks like and how it fits into the reference architecture for the deconstructed data stack: a data stack that includes operational data stores, streaming systems, transformation engines, BI tools, warehouses, ML tools and orchestrators.

It dives into the fundamental characteristics for a control plane:

Breadth (completeness) Latency (freshness) Scale Source of Truth Auditability

ABOUT THE SPEAKER: Shirshanka Das is the Co-founder and CEO of Acryl Data, the company which is commercializing the open source DataHub project, a real-time metadata platform used by LinkedIn, Stripe, Pinterest, Optum, Expedia and many others. Prior to founding Acryl, he was the overall architect for Big Data at LinkedIn from 2010 to 2020, and responsible for creating the metadata and data management strategy at the company.

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

Learn the most important SQL skills and apply them in your job—quickly and efficiently! SQL (Structured Query Language) is the modern language that almost every relational database system supports for adding data, retrieving data, and modifying data in a database. Although basic visual tools are available to help end-users input common commands, data scientists, business intelligence analysts, Cloud engineers, Machine Learning programmers, and other professionals routinely need to query a database using SQL. Job Ready SQL provides you with the foundational skills necessary to work with data of any kind. Offering a straightforward ‘learn-by-doing’ approach, this concise and highly practical guide teaches you all the basics of SQL so you can apply your knowledge in real-world environments immediately. Throughout the book, each lesson includes clear explanations of key concepts and hands-on exercises that mirror real-world SQL tasks. Teaches the basics of SQL database creation and management using easy-to-understand language Helps readers develop an understanding of fundamental concepts and more advanced applications such as data engineering and data science Discusses the key types of SQL commands, including Data Definition Language (DDL) commands and Data Manipulation Language (DML) commands Includes useful reference information on querying SQL-based databases Job Ready SQL is a must-have resource for students and working professionals looking to quickly get up to speed with SQL and take their relational database skills to the next level.