Real-time Business Analytics for Big Data and for Cloud/SaaS Companies

Increasingly, businesses are being managed with more emphasis on insights from user/customer behavior. Applications are generating large numbers of events, leading to Big Data, which needs to be processed and analyzed quickly and efficiently in order for business users to use it to their advantage. Such analysis not only provides information necessary to provide products and services that users want but also provides a competitive edge to companies who incorporate customer behavior insights into their offerings. However, gaining deep insights into transactional, click-stream or other business data is not trivial. Further, critical elements of business analytics such as funnel analytics, user behavior analytics, user or product segmentation and aggregated analytics have traditionally needed significant consulting services, a highly iterative approach, and DBA skills to implement the solutions. Ideally, business users must be able to perform self-service analytics in real-time on live data which does not have to go through any manual interpretation. Data from all sources, streaming or Hadoop clusters, must be addressed in real-time and correlated for insights. Further, key attributes within the data must be automatically extracted and graphed in order to enable the user to analyze them across time and derive relationships between events. Bottom line, business analytics, a crucial part of an organization’s success, has to be made much simpler and made available to every business user. In this session we will discuss Big Data, real-time analytics, Hadoop analytics and data modeling. You will learn more about industry trends affecting you and your business from an analytics perspective, why traditional methods of addressing Big Data analytics are insufficient and increasingly failing, and the new approaches to solving business analytics challenges in a low-cost, self-service, interactive fashion. You will also learn about new technology trends that are enabling efficient analytics such as Hadoop, NoSQL, interactive analytics, dynamic OLAP, multi-dimensional analytics and complex event processing. Presented by: Karthik Kannan, co-founder and VP Products, Cetas

- by Karthik Kannan