Jeff Barnes

Real-Time Processing Using Azure Stream Analytics

This chapter examines the use of Microsoft Azure Streaming Analytics to create jobs to process the incoming data streams from various sensors, perform data transformations and enrichment, and finally, to provide output results into various data formats.

Security and Identity

This chapter reviews several key security topics including threat modeling, security protocols, encryption, and key management as well as managing user identities and supporting multi-tenancy in your solution.

Data Visualizations, Alerts, and Notifications with Power BI

This chapter explores the use of data visualizations, alerts, and notifications to help todays businesses provide useful communications to their employees and customers in order to successfully manage their operations in real time.

Advanced Analytics Using Machine Learning and R

This chapter explores the exciting new world of machine learning and predictive analytics. Machine learning is currently one of the most exciting technology topics in the IT industry today. With very good reason, as it being used across almost every major industry segment and vertical today.

Batch Processing with Data Factory and Data Lake Store

This chapter examines the use of Azure Data Factory and Azure Data Lake, including where, why, and how these technologies fit in the capabilities of a modern business running at Internet speed. It first covers the basic technical aspects and capabilities of Azure Data Factory and Azure Data Lake. Following that, the chapter implements three major pieces of functionality for the reference implementation:

Business in Real-Time

Every business today is going through a digital transformation due to disruptive forces in the market, from born-in-the-cloud competitors to the increasing demands of customers, partners, and employees to engage through modern digital experiences. They are evolving from relying only on historical data to learning to use both historical and real-time data to drive innovation, evolve business strategy, and automate critical business processes.

DevOps Using PowerShell, ARM, and VSTS

DevOps is best summed up as the union of people, processes, and tools (see Figure 2-1), an alignment of the development and operations teams, the automation of development, test and release processes and the selection of a consistent set of tools to facilitate automating the provision, build, test and release cycles. The goal of adopting a DevOps approach is to create a streamlined product development lifecycle that removes, to the greatest degree possible, errors that are introduced through manual steps, i.e., errors introduced through human error.

Device Management Using IoT Hub

Connecting people, places, and things to the cloud, while not trivial, may be one of the easier aspects of IoT as the techniques and protocols are very well defined. The real work begins when you have thousands, possibly millions, of devices connected to the cloud and you need to manage the day-to-day operations of this extremely distributed system. In addition to monitoring and managing the cloud services that are providing analytics, storage, dashboards, alerts, and notifications, you also need to monitor and manage your beacons, devices, and edge gateways.

Sensors, Devices, and Gateways

Chapters 2 and 3 focused on the core processes that must in place when embarking on an IoT and advanced analytics digital transformation journey, namely DevOps and Device Management. This chapter looks at the world of sensors, devices, and gateways. Although we won’t be able to cover all the possible permutations of hardware and software, we will touch upon some of the more common scenarios we encounter and how they relate and work together to create a consistent, secure, and reliable network of connected things.