31526 Guts, Glory, and APIs
30796 Apigee to Join Google
26341 APIs Aren't Enough
25386 Thank you . . .
20216 Monopoly Goes Cashless
19796 Nissan Leaf's Naked APIs
18971 Yes, APIs Are That Big
18376 Modernize SOA with APIs
18321 Go Small or Go Home
17001 Apigee Edge Microgateway
15766 Microservices at Amazon
14936 API Management isn't SOA
14801 Why Telstra Loves APIs
14786 Why Web APIs Won
13721 Swagger's Future
13576 Demo: Apigee Edge
12506 API Mistakes to Avoid
12426 In Search of CDOs
11956 store locator webcast
12196 The API Facade: Overview
11681 Managing Big Data
12026 Data Analytics & APIs
12206 The Anatomy of Apps
by Yong Kim Feb 27, 2015
I just successfully built my first event sequence-based predictive model! Here’s why I consider this a big deal. I started my professional journey in predictive analytics in 2000 (right after helping Bank of... Read more
Efficiently leveraging event sequence patterns requires a process that can create not only a graph data structure of millions of events, but also an efficient algorithm that can query and find patterns that exist across this high dimensional, sparsely populated space.
by Olaf Domis Feb 04, 2015
Machine learning, big data, and API technologies have drastically reduced the complexity of building context-aware apps. But all these advances also mean that these apps require a new approach to system architecture. In... Read more
In this webcast, Apigee's Greg Brail and Alan Ho discuss new architectural styels for building context-aware apps.
by Sridar Rajesh Jan 29, 2015
Every experience we have with our customers is a learning experience; we benefit and learn, and, in turn, fine tune our offerings. In the first post in this series, we examined a recent customer security breach, how... Read more
Every experience we have with our customers is a learning experience; we benefit and learn, and, in turn, fine tune our offerings. In this post, we’ll take a look at how we prepare for and handle high-volume customer events, the kind that are particularly common among retailers during the holiday shopping season.
by Joy and Sanjeev Jan 22, 2015
Engaging with customers via the web, mobile devices, CRM systems, and product purchases or consumption generates a wealth of time-stamped data that’s both structured and unstructured. Drawing insights from these digital... Read more
This post is the first in a series about technologies that analyze time-stamped event data from multiple channels. Here, we’ll focus on descriptive analytics, and the challenge of creating “customer journeys”—sequences of interactions between a customer and a business, spanning channels and devices.
by Apigee Product Team Dec 11, 2014
It gives us great pleasure to announce the latest release of Apigee Insights. Building on our previous release, which offered big improvements to self-service and customer journey analytics, the December release is all... Read more
It gives us great pleasure to announce the latest release of Apigee Insights. Building on our previous release, which offered big improvements to self-service and customer journey analytics, the December release is all about enabling developers to build predictive APIs.
by alex Dec 02, 2014
So now you’ve done it. You went and built yourself an API with Apigee-127. All that’s left is to put it out there in the wild and let the requests flow, right? In a perfect world, sure. In a perfect world, a developer... Read more
In a perfect world, a developer would never load test against your API, traffic would never unexpectedly spike from an app gone awry, and it would be unheard of for a malicious user to DDoS your API. Alas, this world is far from perfect. So let’s talk about API management, in particular applying an API request quota.
by Olaf Domis Nov 20, 2014
Traditional approaches to analyzing customer behavior graphs and event sequences require data simplifications, generalizations, and segmentations that severely degrade prediction accuracy and can lead to the loss of... Read more
In this webcast, Apigee’s Joy Thomas and Sanjeev Srivastav explore the superiority of new methods of behavior graph analysis over the simplifications required for traditional data storage and classical predictive algorithms. Read more...