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Is your media library growing too fast for your staff to manage alone? Unfortunately, as content continually increases, the hours in a day remain the same (surprise!). This means we rarely have enough time or resources to manage content discoverability for our media libraries. But using an indexing solution that leverages artificial intelligence (AI), you can automate how you manage and index your media.
Azure is a rapidly growing cloud computing platform that provides an ever-expanding suite of cloud services. These include analytics, computing, database, mobile, networking, storage, and web services. Azure integrates tools, templates, and managed services that work together to help make it easier to build and manage enterprise, mobile, web, and Internet of Things (IoT) apps faster, using the tools, applications, and frameworks that customers choose. Azure is built on trust. The Azure approach to trust is based on the five foundational principles - Security, Compliance, Privacy, Resilience and Intellectual Property (IP) protection. A well-designed Azure application should focus on the five pillars of software quality.
Organizations rely on data science to support innovation, competitive advantage, and efficiency, and the data scientist role is vital to this practice. But to put data science into production at scale, you need skills and methods that go beyond the scope of the data scientist. The role of data engineer has emerged to ensure that predictive models are ready for production. The technological requirements of data science have also evolved. The cloud data warehouse has developed to address the scalability, availability, and budgetary issues that arise as the volume of data dramatically increases. Read The Scientist, the Engineer, and the Warehouse white paper to learn what it takes to put cloud analytics into practice.Understand the distinct roles of the data scientist vs. data engineer.Find out how these roles work together with a cloud data warehouse.Learn how Azure SQL Data Warehouse is uniquely suited to address the need for governance, manageability, and elasticity at any scale.See how SQL Data Warehouse fits into an effective architecture for cloud analytics.
The Payment Card Industry Data Security Standard (PCI DSS) is designed to prevent fraud using credit card information through increased controls around credit card data. Obtaining PCI DSS compliance is a requirement for all organizations that accept credit card payments, process credit card transactions or transmit or store credit card data. For organizations that have their own data centers, it can be a time consuming and costly process to become PCI compliant. Many organizations are not able to take on the responsibility of building a PCI-compliant environment and handle the daily responsibilities that come with being PCI compliant. Migrating to or building those environments in Microsoft Azure can drastically reduce the PCI-compliance responsibility that an organization must bear. The intent of this paper is to showcase how much easier PCI DSS compliance is to achieve when customers take advantage of Azure SQL Database.
Rending video for movies, high-end commercials and other effects-heavy productions require both flexibility and scalability to an infrastructure. Fortunately, the cloud has made pay-as-you-need-it render nodes a reality. In this white paper, we explore how to set up rendering workloads in Azure. You’ll learn how to: Build a hybrid rendering environment that takes advantage of existing NAS resources while leveraging Azure for peak production periods.Control costs.Leverage the cloud for collaboration. Confidently protect your assets. Optimize and adjust your cloud services and resources.
Continuous deployment of ADF to different environments such as DEV,QA, Prod leverage Azure DevOps.
Optimizing performance and ROI with Azure Cosmos DB
Passing Parameters between pipeline and activities and also between activities.
Navigating the dimensions of cloud security and following best practices in an ever-changing regulatory landscape is a tough job—and the stakes are high. Plus, the more complex your infrastructure is, the harder it is to stay compliant as regulations evolve. How do you balance the flexibility of a cloud data warehouse with the need to protect sensitive information? Help is here. In this white paper, Seven Key Principles of Cloud Security and Privacy, you’ll learn best practices for developing and implementing a comprehensive and sustainable security and privacy strategy. Topics include:The differences and similarities between security and privacy.Why security and privacy start at the platform level. Applying your security program evenly across your portfolio. Implementing security and privacy controls close to your data storage.Data resiliency and availability in the event of an adverse incident. Learn the fundamentals that will help you refine your policies and processes to better prepare for the most demanding privacy and security initiatives today, tomorrow, and beyond.