The model for business intelligence is rapidly changing from hub and spoke to that of a data supply chain, as I pointed out in “Why Building A Distributed Data Supply Chain Is More Important Than Big Data”. More data, more apps, more forms of analytics will all put stress on the centralized model of the enterprise data warehouse and gradually create many different nodes for storing and processing data, all of which communicate with each other.
As more business incline to mobile, cloud and web for commerce, APIs allow a variety of devices to access the same power source and use it for any number of purposes. Apigee, the enterprise-grade API management platform, can be an effective platform that offer plug-and-play configurations on API creation. But these are complex problem that developers can’t build easily.
As more businesses have turned to the Web for commerce, application programming interfaces, or APIs, have grown tremendously in importance. APIs let developers tap into Web services easily, without re-coding their own applications to interact with those services.
API management tools like Apigee Enterprise can be effective platforms to do just that. They offer plug-and-play configurations that makes creating an API creation a GUI-based snap. But you know developers -- the urge to code can be hard to resist. Or there may be a complex problem that an API manager can't build easily.
Accessing a public API is like plugging an appliance into an electrical outlet. The outlet allows a variety of devices to access the same power source and use it for any number of purposes — public APIs do something similar with software and data. It’s a simple relationship that involves one company providing another company with easy access to its data in much the same way that a power company allows you to use its electricity to power the many electronic devices in your home.
FORTUNE -- The havoc the Internet has wrought on traditional business already dwarfs previous economic transformations, but we haven't seen anything yet.
Companies of all sizes and across all industries are now facing a massive digital disruption that will permeate their cores. Information technology has been working its way into business processes for decades, but this is different: The apps, data and APIs that are driving this digital transformation are not just enabling business; they are becoming its very fabric. Whether digital native or analog immigrant, today's digital pioneers recognize that an app strategy is the key to customer engagement, user experience and business success.
Many front-line federal workers have long expressed their frustrations about working in an agency or office culture that stifles innovation. But government is now entering a new era where feds no longer have to file a memo to their boss with a new idea, only to receive the dreaded response, "But we've always done it this way."
Enter the third phase of the Digital Government Strategy: where cultural walls are kicked down in favor of collaboration, interoperability and openness. This is happening as agencies open up their data through application programming interfaces, or APIs, not only to private sector entrepreneurs but also to their own front-line employees, Aneesh Chopra, former U.S. chief technology officer and now advisor on the board of API company Apigee, told Wired Workplace last week.
In the largest new downtown San Jose lease of the year, technology startup Apigee Inc. has signed a deal to lease 41,000 square feet at Equity Office’s 10 Almaden where it could employ upward of 250 people.
With all the emphasis these days that’s placed on combing through the piles of potentially invaluable data that resides within an enterprise, it’s possible for a business to lose sight of the need to turn the discoveries generated by data analysis into valuable actions.
Sure, insights and observations that arise from data analysis are interesting and compelling, but they really aren’t worth much unless they can be converted into some kind of business value, whether it’s, say, fine tuning the experience of customers who are considering abandoning your product or service, or modeling an abuse detection system to block traffic from malicious users.
In this customer-driven world, more and more businesses are relying on data to derive deep insights about the behavior and experience of end users with a business’ products. Yet end user logs, while interesting, often lack a 360-degree view of the “context” in which users consume a business’ products and services. The ability to analyze these logs in the relevant context is key to getting the maximum business value from big data analysis.
Basic contextual analysis requires a little TLC: Time, Location and Channel.
Here are some quick and easy steps from the guys at Apigee on turning your data science into a business science.
3 ways to turn data science into business science
Arm your data scientists with the business context
Ensure that your data scientists do not work in isolation and that they interface and work very closely with the business owner and the product managers. Data scientists need to understand the business drivers, business critical issues, and the enterprise and product strategy.