Está no ar, o Data Hackers News !! Os assuntos mais quentes da semana, com as principais notícias da área de Dados, IA e Tecnologia, que você também encontra na nossa Newsletter semanal, agora no Podcast do Data Hackers !!

Aperte o play e ouça agora, o Data Hackers News dessa semana !

Para saber tudo sobre o que está acontecendo na área de dados, se inscreva na Newsletter semanal:

⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.datahackers.news/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Conheça nossos comentaristas do Data Hackers News:

⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Monique Femme⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Paulo Vasconcellos

⁠Matérias/assuntos comentados:

⁠TikTok vai substituir funcionários por IA;

Meta demite funcionário por causa do vale-alimentação:

⁠OpenAI e Microsoft estariam revendo parceria;

Participe da Live - Potfólio de Dados

Envie seu portifólio para ser analisado ao vivo

Baixe o relatório completo do State of Data Brazil e os highlights da pesquisa :

Demais canais do Data Hackers:

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Está no ar, o Data Hackers News !! Os assuntos mais quentes da semana, com as principais notícias da área de Dados, IA e Tecnologia, que você também encontra na nossa Newsletter semanal, agora no Podcast do Data Hackers !!

Aperte o play e ouça agora, o Data Hackers News dessa semana !

Para saber tudo sobre o que está acontecendo na área de dados, se inscreva na Newsletter semanal:

⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.datahackers.news/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Conheça nossos comentaristas do Data Hackers News:

⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Monique Femme⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Paulo Vasconcellos

⁠Matérias/assuntos comentados:

State of Data Brazil está no Ar;

A treta da OpenAI e a Amazon;

Amazon vai demitir 14 mil gerentes;

Baixe o relatório completo do State of Data Brazil e os highlights da pesquisa :

Demais canais do Data Hackers:

⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Site⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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Access detailed content and examples on Azure SQL, a set of cloud services that allows for SQL Server to be deployed in the cloud. This book teaches the fundamentals of deployment, configuration, security, performance, and availability of Azure SQL from the perspective of these same tasks and capabilities in SQL Server. This distinct approach makes this book an ideal learning platform for readers familiar with SQL Server on-premises who want to migrate their skills toward providing cloud solutions to an enterprise market that is increasingly cloud-focused. If you know SQL Server, you will love this book. You will be able to take your existing knowledge of SQL Server and translate that knowledge into the world of cloud services from the Microsoft Azure platform, and in particular into Azure SQL. This book provides information never seen before about the history and architecture of Azure SQL. Author Bob Ward is a leading expert with access to and support from the Microsoft engineering team that built Azure SQL and related database cloud services. He presents powerful, behind-the-scenes insights into the workings of one of the most popular database cloud services in the industry. This book also brings you the latest innovations for Azure SQL including Azure Arc, Hyperscale, generative AI applications, Microsoft Copilots, and integration with the Microsoft Fabric. What You Will Learn Know the history of Azure SQL Deploy, configure, and connect to Azure SQL Choose the correct way to deploy SQL Server in Azure Migrate existing SQL Server instances to Azure SQL Monitor and tune Azure SQL’s performance to meet your needs Ensure your data and application are highly available Secure your data from attack and theft Learn the latest innovations for Azure SQL including Hyperscale Learn how to harness the power of AI for generative data-driven applications and Microsoft Copilots for assistance Learn how to integrate Azure SQL with the unified data platform, the Microsoft Fabric Who This Book Is For This book is designed to teach SQL Server in the Azure cloud to the SQL Server professional. Anyone who operates, manages, or develops applications for SQL Server will benefit from this book. Readers will be able to translate their current knowledge of SQL Server—especially of SQL Server 2019 and 2022—directly to Azure. This book is ideal for database professionals looking to remain relevant as their customer base moves into the cloud.

This book covers modern data engineering functions and important Python libraries, to help you develop state-of-the-art ML pipelines and integration code. The book begins by explaining data analytics and transformation, delving into the Pandas library, its capabilities, and nuances. It then explores emerging libraries such as Polars and CuDF, providing insights into GPU-based computing and cutting-edge data manipulation techniques. The text discusses the importance of data validation in engineering processes, introducing tools such as Great Expectations and Pandera to ensure data quality and reliability. The book delves into API design and development, with a specific focus on leveraging the power of FastAPI. It covers authentication, authorization, and real-world applications, enabling you to construct efficient and secure APIs using FastAPI. Also explored is concurrency in data engineering, examining Dask's capabilities from basic setup to crafting advanced machine learning pipelines. The book includes development and delivery of data engineering pipelines using leading cloud platforms such as AWS, Google Cloud, and Microsoft Azure. The concluding chapters concentrate on real-time and streaming data engineering pipelines, emphasizing Apache Kafka and workflow orchestration in data engineering. Workflow tools such as Airflow and Prefect are introduced to seamlessly manage and automate complex data workflows. What sets this book apart is its blend of theoretical knowledge and practical application, a structured path from basic to advanced concepts, and insights into using state-of-the-art tools. With this book, you gain access to cutting-edge techniques and insights that are reshaping the industry. This book is not just an educational tool. It is a career catalyst, and an investment in your future as a data engineering expert, poised to meet the challenges of today's data-driven world. What You Will Learn Elevate your data wrangling jobs by utilizing the power of both CPU and GPU computing, and learn to process data using Pandas 2.0, Polars, and CuDF at unprecedented speeds Design data validation pipelines, construct efficient data service APIs, develop real-time streaming pipelines and master the art of workflow orchestration to streamline your engineering projects Leverage concurrent programming to develop machine learning pipelines and get hands-on experience in development and deployment of machine learning pipelines across AWS, GCP, and Azure Who This Book Is For Data analysts, data engineers, data scientists, machine learning engineers, and MLOps specialists

Every organization today is exploring generative AI to drive value and push their business forward. But a common pitfall is that AI strategies often don’t align with business objectives, leading companies to chase flashy tools rather than focusing on what truly matters. How can you avoid these traps and ensure your AI efforts are not only innovative but also aligned with real business value?  Leon Gordon, is a leader in data analytics and AI. A current Microsoft Data Platform MVP based in the UK, founder of Onyx Data. During the last decade, he has helped organizations improve their business performance, use data more intelligently, and understand the implications of new technologies such as artificial intelligence and big data. Leon is an Executive Contributor to Brainz Magazine, a Thought Leader in Data Science for the Global AI Hub, chair for the Microsoft Power BI – UK community group and the DataDNA data visualization community as well as an international speaker and advisor. In the episode, Adel and Leon explore aligning AI with business strategy, building AI use-cases, enterprise AI-agents, AI and data governance, data-driven decision making, key skills for cross-functional teams, AI for automation and augmentation, privacy and AI and much more.  Links Mentioned in the Show: Onyx DataConnect with LeonLeon’s Linkedin Course - How to Build and Execute a Successful Data StrategySkill Track: AI Business FundamentalsRelated Episode: Generative AI in the Enterprise with Steve Holden, Senior Vice President and Head of Single-Family Analytics at Fannie MaeRewatch sessions from RADAR: AI Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Kick off with insights from Michael Kophs as he shares how the Secure Future Initiative (SFI) is setting new security standards.

In today's data-centric business landscape, robust governance, comprehensive auditing, and resilient disaster recovery are paramount for ensuring data integrity, availability, and compliance. This session will explore best practices and advanced strategies for managing and securing your Power BI and Microsoft Fabric environments. Discover how to mitigate risks, optimize operational efficiency, and derive maximum value from your data assets.

Improve your data infrastructure with governance and security, using proven methods and best practices. Break down data silos, foster collaboration, and optimise data accessibility, empowering your business units with the data and technologies they need. Learn how AI improves efficiency and streamlines data product development. And see how Microsoft Fabric simplifies data estate modernization with a focus on unifying your data in an open and governed foundation.

Join us Join us for an engaging and insightful session as we delve into the innovative patterns of mesh, fabric, and knowledge hubs, all grounded in federated operating principles. We’ll explore the common pitfalls encountered on the data journey, key considerations for success, and how Microsoft’s cutting-edge solutions can drive your transformation forward. 

This book is a tutorial on MongoDB customized for developers working in Microsoft .NET 6, .NET 7, and beyond. It explains the differences between relational database systems and the document model supported by MongoDB, and shows how to build .NET applications that run against a MongoDB database, especially one in the cloud. Author Luce Carter kicks things off by teaching you how to determine when to use a document database versus a relational engine. After that, she walks you through building a Microsoft .NET project combining the MongoDB Atlas cloud database as a service solution with a .NET. application. In the process, you will learn how to create, read, update, and delete data in MongoDB from any .NET project. You will come away from this book with a solid understanding of MongoDB’s Developer Data Platform and how to use it from your .NET applications. You’ll be able to connect to MongoDB in the cloud and take advantage of the flexibility and scalability that MongoDB’s document storage model provides, and you’ll understand how to craft your applications to run using document storage and the MongoDB database engine. What You Will Learn Know when to use the MongoDB document model Build .NET applications that connect to MongoDB for data storage Create MongoDB clusters on the MongoDB Atlas cloud platform Store data in MongoDB Atlas Create, Read, Update, and Delete (CRUD) data from .NET Web API projects Test your CRUD endpoints using RESTful operations Validate schemas to help protect against breaking changes Who This Book Is For .NET developers who are looking for an alternative to relational databases, and those looking for a flexible and scalable document storage solution for use from .NET applications. Additionally, anyone wanting to learn MongoDB in the context of .NET and C# will benefit from this book.

This episode features an engaging discussion between Raja Iqbal, Founder and CEO of Data Science Dojo, and Amr Awadallah, Founder and CEO of Vectara, the trusted GenAI Platform for All Builders. Raja sits down with Amr Awadallah, a visionary who has played a key role in shaping the world of technology. From his early days at Microsoft to his leadership roles at VMware and Vectara, Awadallah has been a driving force behind groundbreaking innovations in data, cloud computing, and artificial intelligence.This episode is a must-watch for anyone interested in a comprehensive outlook on AI's current state and future trajectory.

As AI becomes more accessible, a growing question is: should machine learning experts always be the ones training models, or is there a better way to leverage other subject matter experts in the business who know the use-case best? What if getting started building AI apps required no coding skills? As businesses look to implement AI at scale, what part can no-code AI apps play in getting projects off the ground, and how feasible are smaller, tailored solutions for  department specific use-cases? Birago Jones is the CEO at Pienso. Pienso is an AI platform that empowers subject matter experts in various enterprises, such as business analysts, to create and fine-tune AI models without coding skills. Prior to Pienso, Birago was a Venture Partner at Indicator Ventures and a Research Assistant at MIT Media Lab where he also founded the Media Lab Alumni Association. Karthik Dinakar is a computer scientist specializing in machine learning, natural language processing, and human-computer interaction. He is the Chief Technology Officer and co-founder at Pienso. Prior to founding Pienso, Karthik held positions at Microsoft and Deutsche Bank. Karthik holds a doctoral degree from MIT in Machine Learning. In the episode, Richie, Birago and Karthik explore why no-code AI apps are becoming more prominent, uses-cases of no-code AI apps, the steps involved in creating an LLM, the benefits of small tailored models, how no-code can impact workflows, cost in AI projects, AI interfaces and the rise of the chat interface, privacy and customization, excitement about the future of AI, and much more.  Links Mentioned in the Show: PiensoGoogle Gemini for BusinessConnect with Birago and KarthikAndreesen Horowitz Report: Navigating the High Cost of AI ComputeCourse: Artificial Intelligence (AI) StrategyRelated Episode: Designing AI Applications with Robb Wilson, Co-Founder & CEO at Onereach.aiRewatch sessions from RADAR: AI Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

The sheer volume of business data has reached an all-time high. Using visualizations to transform this data into useful and understandable information can facilitate better decision-making. This practical book shows data analysts as well as professionals in finance, sales, and marketing how to quickly create visualizations and build savvy dashboards. Alex Kolokolov from Data2Speak and Maxim Zelensky from Intelligent Business explain in simple and clear language how to create brilliant charts with Microsoft Power BI and follow best practices for corporate reporting. No technical background is required. Step-by-step guides help you set up any chart in a few clicks and avoid common mistakes. Also, experienced data analysts will find tips and tricks on how to enrich their reports with advanced visuals. This book helps you understand: The basic rules for classic charts that are used in 90% of business reports Exceptions to general rules based on real business cases Best practices for dashboard design How to properly set up interactions How to prepare data for advanced visuals How to avoid pitfalls with eye-catching charts

This comprehensive guide will teach you how to build an income statement semantic model, also known as the profit and loss (P&L) statement. Author Chris Barber— a business intelligence (BI) consultant, Microsoft MVP, and chartered accountant (ACMA, CGMA)—helps you master everything from designing conceptual models to building semantic models based on these designs. You will learn how to build a re-usable solution based on the trial balance and how to expand upon this to build enterprise-grade solutions. If you want to leverage the Microsoft BI platform to understand profit within your organization, this is the resource you need. What You Will Learn Modeling and the income statement: Learn what modelling the income statement entails, why it is important, and how income statements are constructed Calculating account balances: Learn how to optimally calculate account balances using a Star Schema Producing external income statement semantic models: Learn how to produce external income statement semantic models as they enable income statements to be analyzed from a range of perspectives and can be explored to reveal the underlying accounts and journal entries Producing internal income statement semantic models: Learn how to create multiple income statement layouts and further contextualize financial information by including percentages and non-financial information, and learn about the various security and self-service considerations Who This Book Is For Technical users (solution architects, Microsoft Fabric developers, Power BI developers) who require a comprehensive methodology for income statement semantic models because of the modeling complexities and knowledge needed of the accounting process; and finance (management accountants) who have hit the limits of Excel and have started using Power BI, but are unsure how income statement semantic models are built

One of the prerequisites for being able to do great data analyses is that the data is well structured and clean and high quality. For individual projects, this is often annoying to get right. On a corporate level, it’s often a huge blocker to productivity. And then there’s healthcare data. When you consider all the healthcare records across the USA, or any other country for that matter, there are so many data formats created by so many different organizations, it’s frankly a horrendous mess. This is a big problem because there’s a treasure trove of data that researchers and analysts can’t make use of to answer questions about which medical interventions work or not. Bad data is holding back progress on improving everyone’s health. Terry Myerson is the CEO and Co-Founder of Truveta. Truveta enables scientifically rigorous research on more than 18% of the clinical care in the U.S. from a growing collective of more than 30 health systems. Previously, Terry enjoyed a 21-year career at Microsoft. As Executive Vice President, he led the development of Windows, Surface, Xbox, and the early days of Office 365, while serving on the Senior Leadership Team of the company. Prior to Microsoft, he co-founded Intersé, one of the earliest Internet companies, which Microsoft acquired in 1997.​ In the episode, Richie and Terry explore the current state of health records, challenges when working with health records, data challenges including privacy and accessibility, data silos and fragmentation, AI and NLP for fragmented data, regulatory grade AI, ongoing data integration efforts in healthcare, the future of healthcare and much more.  Links Mentioned in the Show: TruvetaConnect with TerryHIPAACourse - Introduction to Data PrivacyRelated Episode: Using AI to Improve Data Quality in HealthcareRewatch sessions from RADAR: AI Edition New to DataCamp? Learn on the go using the DataCamp mobile app Empower your business with world-class data and AI skills with DataCamp for business

Microsoft Excel is the most widely used data analysis tool on the planet, but somehow it doesn't get the love it deserves.   In this episode, Sonali and Chris talk about how they leverage Excel in their data roles at prominent companies, and share practical tips you can use to add more value to your own organization.   You'll leave the show with an insider's look at where Excel can make a big impact, and actionable advice about what to learn next to take your game to the next level.   What You'll Learn: What makes Excel the most versatile tool used by data professionals How Chris and Sonali are leveraging Excel to drive value at their organizations Tips for where to focus to get the most out of Excel   Register for free to be part of the next live session: https://bit.ly/3XB3A8b   About our guests: Sonali Kumar works as a Data Analyst specializing in HR Analytics. She is also a podcast host of "Success Beyond Our Greatest Fears." Follow Sonali on LinkedIn  

Chris French is a Data Advisor, LinkedIn Learning Instructor, and founder of DataFrenchy Academy Follow Chris on LinkedIn   Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter

Microsoft Power BI Performance Best Practices is your comprehensive guide to designing, optimizing, and scaling Power BI solutions. By understanding data modeling, DAX formulation, and report design, you will be able to enhance the efficiency and performance of your Power BI systems, ensuring that they meet the demands of modern data-driven decision-making. What this Book will help me do Understand and apply techniques for high-efficient data modeling to enhance Power BI performance and manage large datasets. Identify and resolve performance bottlenecks in Power BI reports and dashboards using tools like DAX Studio and VertiPaq Analyzer. Implement governance and monitoring strategies for Power BI performance to ensure robust and scalable systems. Gain expertise in leveraging Power BI Premium and Azure for handling larger scale data and integrations. Adopt best practices for designing, implementing row-level security, and optimizing queries for efficient operations. Author(s) Thomas LeBlanc and Bhavik Merchant are experienced professionals in the field of Business Intelligence and Power BI. Thomas brings over 30 years of IT expertise as a Business Intelligence Architect, ensuring practical and effective solutions for BI challenges. Bhavik is a recognized expert in enterprise-grade Power BI implementation. Together, they share actionable insights and strategies to make Power BI solutions advanced and highly performant. Who is it for? This book is ideal for data analysts, BI developers, and data professionals seeking to elevate their Power BI implementations. If you are proficient with the essentials of Power BI and aim to excel in optimizing its performance and scalability, this book will guide you to achieve those goals efficiently and effectively.

Dive into the world of data analysis with the Polars Cookbook. This book, ideal for data professionals, covers practical recipes to manipulate, transform, and analyze data using the Python Polars library. You'll learn both the fundamentals and advanced techniques to build efficient and scalable data workflows. What this Book will help me do Master the basics of Python Polars including installation and setup. Perform complex data manipulation like pivoting, grouping, and joining. Handle large-scale time series data for accurate analysis. Understand data integration with libraries like pandas and numpy. Optimize workflows for both on-premise and cloud environments. Author(s) Yuki Kakegawa is an experienced data analytics consultant who has collaborated with companies such as Microsoft and Stanford Health Care. His passion for data led him to create this detailed guide on Polars. His expertise ensures you gain real-world, actionable insights from every chapter. Who is it for? This book is perfect for data analysts, engineers, and scientists eager to enhance their efficiency with Python Polars. If you are familiar with Python and tools like pandas but are new to Polars, this book will upskill you. Whether handling big data or optimizing code for performance, the Polars Cookbook has the guidance you need to succeed.