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Azure for ISV E-book

This e-book is designed for growing technology companies wanting to understand and calculate the challenges, opportunities, and tradeoffs faced in building and scaling their software business.  This guide covers:  • How Azure’s capabilities and built-in services help level the playing field with enterprise competitors  • How both business and technical processes can be more efficient and affordable with Azure services  • Specific savings you could realize by leveraging the Azure Pricing Calculator to better predict costs 

Delta Lake on Azure Databricks

Delta Lake on Azure Databricks allows you to configure Delta Lake based on your workload patterns and has optimized layouts and indexes for fast interactive queries. Delta Lake is an open source storage layer that brings reliability to data lakes.  It provides ACID transactions, scalable metadata handling, and unifies streaming and batch data processing. Delta Lake runs on top of your existing data lake and is fully compatible with Apache Spark APIs.  

Standardizing the Machine Learning Lifecycle

Successfully building and deploying a machine-learning model can be difficult to do once. Enabling other data scientists (or yourself) to reproduce your pipeline, compare the results of different versions, track what’s running where, and redeploy and rollback updated models is much harder. In this eBook, we’ll explore what makes the ML lifecycle so challenging compared to the traditional software development lifecycle, and share how to address these challenges with Azure Databricks. 

8 Steps for a developer to Learn Apache Spark with Delta Lake

In this eBook, we expand, augment and curate on concepts initially published on KDnuggets. In addition, we augment the eBook with assets specific to Delta Lake and Apache Spark 2.x, written and presented by leading Spark contributors and members of Spark PMC including:  • Matei Zaharia, the creator of Spark  • Reynold Xin, chief architect  • Michael Armbrust, lead architect behind Spark SQL and Structured Streaming  • Joseph Bradley, one of the drivers behind Spark MLlib and SparkR  • Tathagata Das, lead developer for Structured Streaming 

Four real-life Machine Learning use cases

This guide walks you through four practical end-to-end machine-learning use cases on Azure Databricks:  • A loan risk analysis use case that covers importing and exploring data in Databricks, executing ETL and the ML pipeline, including model tuning with XGBoost Logistic Regression  • An advertising analytics and click prediction use case that includes collecting and exploring the advertising logs with Spark SQL and using PySpark for feature engineering and using GBTClassifier for model training and predicting the clicks  • A market basket analysis problem at scale, from ETL to data exploration using Spark SQL, and model training using FT-growth  • An example of suspicious behavior identification in videos, including a preprocessing step for creating image frames, transfer learning for featurization, and applying logistic regression to identify suspicious images in a video. 

Solving business needs with Delta Lake

Data professionals want to help their organizations innovate for competitive advantage by making the most of their data. Good quality, reliable data forms the foundation for success for such analytics and machine learning initiatives. 

Cloud Analytics with Microsoft Azure

Learn how to bring the limitless scale, powerful insights, unified experience, and cost-efficiency of Azure Synapse Analytics to your organization.  Get a practical, hands-on introduction to Azure Synapse Analytics in Cloud Analytics with Microsoft Azure. Discover how to drive deep insights from all your data and apply machine learning models to intelligent apps through step-by-step guidance and detailed business use cases. Explore how to work with a fully managed, integrated data analytics service that blends data warehousing, data integration, and big data processing with accelerated time to insight into a single service.  Learn how to: Provision Azure Data Factory, Azure Data Lake Storage, and Azure Synapse Analytics. Analyze structured data to gain meaningful insights. Model and visualize data using Power BI. Build an end-to-end analytics pipeline in the cloud.  Accelerate the delivery of business intelligence, artificial intelligence, machine learning, Internet of Things, and intelligent applications.

Four Ways to Maximize Your Business Intelligence Investments

Get real-world insights and drive more value from your business intelligence investments with a scalable and secure analytics solution that empowers everyone in your organization to achieve faster insights. Read the complimentary e-book Four Ways to Maximize Your Business Intelligence Investments to explore how four successful companies enabled corporate innovation by migrating data to the cloud. Discover how unifying data onto a single cloud-based platform improved data access and analytics, and learn how giving workers real-time access to self-service data analytics empowered them to make data-driven decisions. Get insights to help you: Drive down costs by spending less time managing infrastructure and siloed projects—and more time optimizing processes and creating positive change. Create business value with advanced analytics and predictive models that drive new opportunities. Accelerate time-to-insight for better understanding of your operations and customers as you navigate the new realities of business. Take the next step in your transformation with an analytics solution that delivers breakthrough performance, security, and speed. Analytics in Azure is up to 14 times faster and costs up to 94 percent less than other cloud providers.

Three Ways Analytics Can Help: Respond, Adapt, and Save

Analytics and AI are essential for helping businesses make informed decisions, especially as needs and priorities change rapidly. Learn how to securely manage and scale your organization’s analytics with speed and simplicity—and how to use insights to give your organization a distinct advantage when it comes to decision making. Read Three Ways Analytics Can Help: Respond, Adapt, and Save to discover how to quickly deliver insights from all your data more efficiently with a limitless analytics service that brings together data warehousing and big data analytics.  Learn how to: Use BI and AI capabilities in Azure Synapse to access enhanced reporting and dashboard functionality.  Make data accessible and deliver critical insights to more people across your organization—including data engineers, data scientists, IT professionals, business analysts, and executives. Safeguard your data with advanced security and privacy features. Get a limitless analytics service that’s up to 14 times faster at a 94 percent lower cost than other cloud providers.

Azure Serverless Computing Cookbook, Third Edition

Spend more time building great apps and less time managing server infrastructure. Get your solutions to market faster using Azure Functions, a fully managed compute platform for processing data, integrating systems, and building simple APIs and microservices. In this e-book you’ll find use cases, hands-on steps, and tutorials for quickly configuring your own serverless environments. Explore best practices for Functions, and learn how to:Develop event-based handlers on a serverless architecture.Test, troubleshoot, and monitor Azure functions.Automate administrative tasks from development through to deployment and maintenance.Integrate Functions with other Azure services.Build stateful serverless apps and self-healing jobs using Durable Functions.Download the 399-page serverless computing e-book and get access to dozens of step-by-step recipes for quickly building serverless apps.