Data is not just getting bigger, but it’s getting faster.
The convergence of many technologies, and trends: web apps, social networks, mobile devices, and now the Internet of Things, have dramatically increased the amount of digital information than ever before. This proliferation of data has also increased the pressure on data analytics infrastructure to enable actionable decisions for businesses at scale, and in real time.
How do you quickly ingest, and operationalize insights contained in sensor telemetry data, mobile app engagement taps, IT infrastructure logs, social media feeds, and more? Amazon Web Services delivers important building blocks to architect internet-scale big data solutions, while performing the heavy lifting of the IT infrastructure. Learn how you can leverage innovative new solutions like Amazon Kinesis, and Amazon Redshift that enable you to focus on your innovative ideas.
We will provide a review of the key AWS services, features, and benefits; discuss big data architectural design patterns that begin fusing together continuous streaming processing, massive scale data warehousing, and Hadoop based technologies as part of your big data infrastructure. We’ll make the theory, more practical by providing real life examples of how AWS customers are ingesting and analyzing their data in a variety of forms to deliver competitive advantage, increased efficiency and value to their customers.
Adi Krishnan is the Sr. Product Manager for Amazon Kinesis, a fully managed service for real-time processing of streaming data at massive scale. In this role he works closely with customers and partners, helps define product roadmap, and ensures Amazon Kinesis delivers value to customers. Prior to Amazon Web Services, Adi has held several product management roles at Microsoft where he worked on the Bing search engine, Windows Azure, and the High Performance Computing/ Technical Computing initiative.