In a classic cart before the horse scenario, many companies have jumped at leveraging Generative AI and other AI technologies. However, most of those same companies haven't completed the core work of building a reliable & secure foundation that provides data accessibility, analytics speed, and ensures data quality. The resulting risk for leaders is overinvestment in AI programs that may not have accurate & secure data access, further exposing the business to harm. It is a case of slowing down to speed up - ensure the foundation is solid before you build the house. In this talk by Starburst CEO Justin Borgman, and Head of Partner Solutions Architecture, Data & Analytics - AI/ML, Subodh Kumar from AWS, you'll learn about the essential data foundations for AI success. The foundation, the plumbing, and the framing that will set businesses up for AI success.

Big Data Europe Onsite and online on 22-25 November in 2022 Learn more about the conference: https://bit.ly/3BlUk9q

Join our next Big Data Europe conference on 22-25 November in 2022 where you will be able to learn from global experts giving technical talks and hand-on workshops in the fields of Big Data, High Load, Data Science, Machine Learning and AI. This time, the conference will be held in a hybrid setting allowing you to attend workshops and listen to expert talks on-site or online.

Discussion on upgrading and tuning Grammarly's ML training platform to a scalable system. Topics include moving away from a custom architecture due to hardware shortages, key requirements and architectural challenges, MLOps best practices for scalability, and lessons learned from transitioning from a single-region AWS setup to a cross-region, multi-cloud cluster compute deployment.

In this session we will show how you can query, connect, and report on your data insights across clouds, including AWS and Azure, with BigQuery Omni and Looker. Reduce costly copying and customization and get answers quickly, so you can get back to work.

Click the blue “Learn more” button above to tap into special offers designed to help you implement what you are learning at Google Cloud Next 25.

Learn the fundamentals of DevOps best practices. You will become familiar with the core concepts needed to deploy cloud resources continuously. Walk through configuring Pulumi GitHub Actions to deploy AWS resources programmatically and accelerate your cloud projects with the skeleton code provided.

Learn the fundamentals of building and deploying containerized workloads using Pulumi to manage infrastructure, an introduction to Pulumi’s IaC platform and deployment on AWS. The workshop covers setting up an Amazon EKS cluster on AWS and deploying containerized workloads to the cluster; designed to help new users become familiar with core concepts for deploying Kubernetes clusters and workloads on AWS.

Hands-on building a serverless application using AWS Lambda and S3.

Guided exercises on provisioning, updating, and destroying AWS resources with Pulumi.

An introduction to Pulumi's programming model and how to use it to provision modern cloud infrastructure.

Learn and explore the capabilities of Microsoft Fabric, the latest evolution in cloud analytics suites. This book will help you understand how users can leverage Microsoft Office equivalent experience for performing data management and advanced analytics activity. The book starts with an overview of the analytics evolution from on premises to cloud infrastructure as a service (IaaS), platform as a service (PaaS), and now software as a service (SaaS version) and provides an introduction to Microsoft Fabric. You will learn how to provision Microsoft Fabric in your tenant along with the key capabilities of SaaS analytics products and the advantage of using Fabric in the enterprise analytics platform. OneLake and Lakehouse for data engineering is discussed as well as OneLake for data science. Author Ghosh teaches you about data warehouse offerings inside Microsoft Fabric and the new data integration experience which brings Azure Data Factory and Power Query Editor of Power BI together in a single platform. Also demonstrated is Real-Time Analytics in Fabric, including capabilities such as Kusto query and database. You will understand how the new event stream feature integrates with OneLake and other computations. You also will know how to configure the real-time alert capability in a zero code manner and go through the Power BI experience in the Fabric workspace. Fabric pricing and its licensing is also covered. After reading this book, you will understand the capabilities of Microsoft Fabric and its Integration with current and upcoming Azure OpenAI capabilities. What You Will Learn Build OneLake for all data like OneDrive for Microsoft Office Leverage shortcuts for cross-cloud data virtualization in Azure and AWS Understand upcoming OpenAI integration Discover new event streaming and Kusto query inside Fabric real-time analytics Utilize seamless tooling for machine learning and data science Who This Book Is For Citizen users and experts in the data engineering and data science fields, along with chief AI officers

Demonstrates resources provisioning life cycle on AWS with Pulumi.

Learn how to use TypeScript with Pulumi. Guided exercises introducing TypeScript usage with Pulumi.

Overview of Pulumi's programming model and core concepts.

An interactive workshop exploring the infrastructure and service architecture you need to scale AI applications in production, including infrastructure as code basics, provisioning AWS resources (ECS clusters, networking, messaging queues, and Amazon RDS Postgres), and managing Pinecone indexes.

Você já deve ter ouvido, sobre o lançamento da nova Cloud Publica e Brasileira, que movimentou muitos rumores no mercado de tecnologia. E atendo a pedidos da comunidade, agora você tem a chance de conhecer as estratégias, e um pouco mais, sobre a Magalu Cloud.

Neste episódio do Data Hackers — a maior comunidade de AI e Data Science do Brasil-, chamamos o Vaner Vendramini — Field CTO na Magalu Cloud, para desmitificar tudo que está por de trás deste lançamento da primeira Cloud Brasileira em Hiperscala, da Magalu. 

Lembrando que você pode encontrar todos os podcasts da comunidade Data Hackers no Spotify, iTunes, Google Podcast, Castbox e muitas outras plataformas. Caso queira, você também pode ouvir o episódio aqui no post mesmo!

Conheça nosso convidado:

Vaner Vendramini — Field CTO na Magalu Cloud

Nossa Bancada Data Hackers:

Monique Femme — Head of Community Management na Data Hackers Allan Senne — Co-founder da Data Hackers e Co-Founder & CTO at Dadosfera.

Paulo Vasconcellos — Co-founder da Data Hackers e Principal Data Scientist na Hotmart. Gabriel Lages — Co-founder da Data Hackers e Data & Analytics Sr. Director na Hotmart.

Falamos no episódioLinks de referências:

Sobre o evento de lançamento da Magalu Cloud: https://www.magazineluiza.com.br/blog-da-lu/c/dl/dldc/magalu-cloud-a-nuvem-do-magazine-luiza/12434/ Cloud Alema citada pelo Vaner: https://www.stackit.de/en/ Estudo da McKinsey sobre o mercado de cloud Computing em 2030: https://www.mckinsey.com/br/our-insights/all-insights/computacao-em-nuvem-2030 Progressão do market sharing de Cloud, de 2018 até 2021, da digital cloud training: https://digitalcloud.training/comparison-of-aws-vs-azure-vs-google/ Página de parceiros da Magalu Cloud: https://magalu.cloud/solucoes/

Hands-on guidance on provisioning and managing EKS clusters in AWS using Pulumi.

Practical guidance on provisioning, updating, and destroying AWS resources using Pulumi during the IaC workshop.

Design and architect new generation cloud-based data warehouses using Azure and AWS. This book provides an in-depth understanding of how to build modern cloud-native data warehouses, as well as their history and evolution. The book starts by covering foundational data warehouse concepts, and introduces modern features such as distributed processing, big data storage, data streaming, and processing data on the cloud. You will gain an understanding of the synergy, relevance, and usage data warehousing standard practices in the modern world of distributed data processing. The authors walk you through the essential concepts of Data Mesh, Data Lake, Lakehouse, and Delta Lake. And they demonstrate the services and offerings available on Azure and AWS that deal with data orchestration, data democratization, data governance, data security, and business intelligence. After completing this book, you will be ready to design and architect enterprise-grade, cloud-based modern data warehouses using industry best practices and guidelines. What You Will Learn Understand the core concepts underlying modern data warehouses Design and build cloud-native data warehousesGain a practical approach to architecting and building data warehouses on Azure and AWS Implement modern data warehousing components such as Data Mesh, Data Lake, Delta Lake, and Lakehouse Process data through pandas and evaluate your model’s performance using metrics such as F1-score, precision, and recall Apply deep learning to supervised, semi-supervised, and unsupervised anomaly detection tasks for tabular datasets and time series applications Who This Book Is For Experienced developers, cloud architects, and technology enthusiasts looking to build cloud-based modern data warehouses using Azure and AWS

What does it take to go from an idea in a notebook to an application handling real-world traffic? The Pinecone and Pulumi teams will explore the infrastructure and service architecture you need in order to scale AI apps in production. We will delve into deploying high-volume AI systems through scalable microservices, efficient data processing, and seamless synchronization between user interfaces and databases. We will examine the nuances of containerization for enhanced portability and Infrastructure as Code (IaC) for streamlined cloud deployments. The workshop will also discuss industry best practices in scalability and security for production-grade AI systems in a cloud-native landscape. This workshop is designed to help developers and engineers gain valuable insights and practical strategies for evolving AI applications into resilient and efficient cloud-native solutions.

Vladyslav Tripatkhi will discuss an approach that enables engineers to provision cloud workloads without requiring the involvement of the Cloud Infra team: what self-service looks like, what internally developed applications we use to achieve it, how we incentivize engineers to use our offerings, and how we deal with AWS instance capacity limits.