Title: Fast Data: The Next Frontier of Big Data

Abstract: In the first stage of big data adoption, the focus was primarily on storing and analyzing massive amounts data. The focus was completely on volume. Currently, organizations have started to enter the second stage of big data: fast data. Fast data is about streaming massive amounts of data and analyzing that same data instantaneously. It’s the next frontier of big data. It’s especially the Internet of Things (IoT) that’s pushing fast data. The IoT is about connecting devices to devices across the Internet. The stream of data these intercommunicating devices can generate is massive. In these massive data streams valuable business insights can be hidden, deeply hidden.

The business value of fast datais in analyzing it. Unfortunately, analyzing fast data is not similar to analyzing enterprise data for which data warehouses can be developed and easy-to-use data visualization tools can be deployed. For example, fast data can be very cryptic data and to make sense of it, it has to be integrated with enterprise data residing in the enterprise data warehouse. Also, fast data has to be analyzed real-time, and sometimes even before it’s stored, and a reaction may be required instantly. It’s a new world. This keynote discusses the architectural aspects of fast data, guidelines on how to adopt fast data, and how to integrate fast data with existing business intelligence environments.

• How does fast data relate to the classic world of business intelligence and data warehousing?
• A new architecture is required for processing fast data
• Technologies involved in analyzing the fast data stream
• How to integrate fast data with data from the enterprise data warehouse
• The challenge of reacting real-time on incoming fast data
• What is the relationship between Big Data and the IoT?