This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
The population of intelligent IoT devices is exploding, and they are generating more telemetry than ever. The Microsoft Azure IoT ecosystem offers a rich set of capabilities for processing IoT telemetry, from its arrival in the cloud through its storage in databases and data lakes.
Examples include tracking a fleet of trucks, analyzing large numbers of banking transactions for potential fraud, managing logistics in the delivery of supplies after a disaster or during a pandemic, recommending products to ecommerce shoppers, and much more. Real-time digital twins are designed to be easy to develop and modify.
Examples include tracking a fleet of trucks, analyzing large numbers of banking transactions for potential fraud, managing logistics in the delivery of supplies after a disaster or during a pandemic, recommending products to ecommerce shoppers, and much more. Real-time digital twins are designed to be easy to develop and modify.
Whether it’s ecommerce shopping carts, financial trading data, IoT telemetry, or airline reservations, these data sets need fast, reliable access for large, mission-critical workloads. For more than a decade, in-memory data grids (IMDGs) have proven their usefulness for storing fast-changing data in enterprise applications.
Whether it’s ecommerce shopping carts, financial trading data, IoT telemetry, or airline reservations, these data sets need fast, reliable access for large, mission-critical workloads. For more than a decade, in-memory data grids (IMDGs) have proven their usefulness for storing fast-changing data in enterprise applications.
We organize all of the trending information in your field so you don't have to. Join 5,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content