It’s no surprise that creating developer-friendly APIs is a daunting task: from strategizing on evangelism techniques to the differences between the enterprise and open web, there are many ways to succeed, and at the same time — many ways to fail.
Steve Marx (developer advocate at Dropbox) will moderate a panel consisting of Jason Harmon (platform architect at Paypal), Neil Mansilla (director of platform and partnerships at Mashery), Michael Harkey (platform business development at Foursquare) and Dan Martin (VP of OpenAPI community and platform at MasterCard) will join together to explore the best ways to create user-friendly APIs, taking into consideration the various elements that go into building applications and evaluating the developer experience as a whole. With over 50 years of combined experience in the developer community this panel of experts has the background and expertise across industries to dig into the myriad tools it takes to be successful and the various approaches to API strategies — sharing real-world examples that bring to life the development experience.
The line between operational and analytic applications is an arbitrary division driven by limitations in legacy database and data-warehousing systems. Many people have extensive experience modeling data for Relational Database Systems (RDBMS). But in the modern world, NoSQL databases support a variety of native data types, such as XML, RDF, JSON, text and binary, and allow mixing and matching these within a database to provide flexibility and agility.
How do you move from an RDBMS view of the data world to a NoSQL view in order to leverage modern data models in your applications? Today, if you have data that’s useful, you build an application or put it in a data warehouse to unlock its value. Application by application, our data centers have become more and more complex. Bringing the value back to the data itself, rather than the application it’s built on, creates the data-centered data center; rather than an application-centric database.
In this session, David Gorbet, VP of Engineering at MarkLogic, will discuss:
How a data-centered data center can generate immediate returns
How to break down the barrier between operational and analytic data stores and applications.
Different data modeling techniques for XML, RDF and JSON
How to handle thousands of queries in sub-seconds on any combination of storage technology
IoT is quickly evolving beyond being synonymous with sensor-driven data and becoming socially engaging. There is an overwhelming influx of human information generated in our daily lives that remain untapped and underutilized. Conversations that we have online and offline, pictures that we take, tweets that we post – this human information is often neglected due to the difficulty of understanding or harnessing it, yet it makes up the vast majority of all information that exists. Imagine a sound system that automatically plays music based on the mood conveyed in your tweets, or a Nerf gun that only targets people on your naughty list. Now you can automate extraction of human information and easily access functionalities such as OCR, speech-to-text, face recognition, sentiment analysis or categorization through a simple call of an API to unlock the full potential of the Internet of Things. Join us for this engaging session as we discuss the opportunities of leveraging APIs that can harness human information.
The growth of data volume, velocity, and variety dramatically increases the potential for data breaches and violations of privacy. As companies continue to rely on innovative technology to improve their analytic efficiency, they are simultaneously exposing more data. Whether due to human error or unethical practices, this increase in exposure is concerning in both the private and public sectors. If users and companies can’t trust third parties to securely manage their data, the scalability, utility, and longevity of these these third parties will be undermined.
During the past decade, businesses have been implementing IoT applications by connecting devices/“things” on their internal network (InTRAnet) to provide better customer service, reduce costs and more. These businesses are converting the vast amounts of data generated into actionable insights by applying advanced analytics technologies designed specifically to handle the requirements of Real-time Big Data analytics.
With more and more devices being connected to the InTERnet, the opportunity for additional value is growing rapidly as the projected number devices connected broadly across all of IoT grows exponentially.
To truly take advantage of the massive amounts of real-time data in the emerging IoT world, we need to transform our thinking, processes, and infrastructure to act in seconds...not hours and days.
This presentation will discuss the opportunities, challenges, and solutions related to analyzing large amounts of IOT data.
