Book Image

Cloud Analytics with Microsoft Azure - Second Edition

By : Has Altaiar, Jack Lee, Michael Peña
Book Image

Cloud Analytics with Microsoft Azure - Second Edition

By: Has Altaiar, Jack Lee, Michael Peña

Overview of this book

Cloud Analytics with Microsoft Azure serves as a comprehensive guide for big data analysis and processing using a range of Microsoft Azure features. This book covers everything you need to build your own data warehouse and learn numerous techniques to gain useful insights by analyzing big data. The book begins by introducing you to the power of data with big data analytics, the Internet of Things (IoT), machine learning, artificial intelligence, and DataOps. You will learn about cloud-scale analytics and the services Microsoft Azure offers to empower businesses to discover insights. You will also be introduced to the new features and functionalities added to the modern data warehouse. Finally, you will look at two real-world business use cases to demonstrate high-level solutions using Microsoft Azure. The aim of these use cases will be to illustrate how real-time data can be analyzed in Azure to derive meaningful insights and make business decisions. You will learn to build an end-to-end analytics pipeline on the cloud with machine learning and deep learning concepts. By the end of this book, you will be proficient in analyzing large amounts of data with Azure and using it effectively to benefit your organization.
Table of Contents (7 chapters)

The power of data

As a consumer, you have seen how the advent of data has influenced our activities in the daily grind. Most popular entertainment applications, such as YouTube, now provide a customized user experience with features such as video recommendations based on our interests and search history logging information. It is now child's play to discover new content that's similar to our preferred content, and also to find new and popular trending content.

Due to the major shift in wearable technology, it has also become possible to keep track of our health statistics by monitoring heart rates, blood pressure, and so on. These devices then formulate a tailored recommendation based on the averages of these statistics. But these personalized health stats are only a sample of the massive data collection happening every day on a global scale, to which we actively contribute.

Millions of people all over the world use social networking platforms and search engines every day. Internet giants such as Facebook, Instagram, and Google use clickstream data to come up with innovations and improve their services. Data collection is also carried out extensively under projects such as The Great Elephant Census and eBird that aim to boost wildlife conservation. Data-driven techniques have been adopted for tiger conservation projects in India. It even plays an invaluable role in global efforts to compile evidence, causes, and possible responses to climate change—to understand sea surface temperature, analyze natural calamities such as coastal flooding, and highlight global warming patterns in a collective effort to save the ecosystem.

Organizations such as Global Open Data for Agriculture and Nutrition (GODAN), which can be used by farmers, ranchers, and consumers alike, contribute to this tireless data collection as well.

Furthermore (as with the advent of wearable technology), data analysis is contributing to pioneering advancements in the healthcare sector. Patient datasets are analyzed to identify patterns and early symptoms of diseases in order to divine better solutions to known problems.

The scale of data being talked about here is massive—hence, the popular term big data is used to describe the harnessing power of this data at scale.

Note

You can read more about open data https://www.data.gov/.