When discussing big data we tend to focus on the end state—the massive scale and variety of data. But big data is created one event at a time, whether from sensors, log files, or customer interactions. Historically, one of the obstacles to leveraging this data has been the processing time and effort to extract, transform, and load (ETL) the data into an analytical database, a warehouse, or, more recently, a big data platform for analysis.
Streaming makes it possible to better manage, analyze, and distribute events across locations and subscribers. Examples of data flow include web events, machine sensors, and biometric data. Operational agility requires flowing data to be quickly analyzed and understood in context, but this context could benefit from understanding long-term trends and patterns while also leveraging newly arriving data.
Jack Norris explores how companies from Altitude Digital to Uber are transforming their businesses, covering the types of applications leading companies are pursuing now, the importance of the data layer to business transformation, the role of streaming and importance of real-time processing, and how that relates to developers and their adoption of Agile approaches, such as microservices.
Jack Norris is the senior vice president of data and applications at MapR Technologies. Jack has a wide range of demonstrated successes, from defining new markets for small companies to increasing sales of new products for large public companies, in his 20 years spent in enterprise software marketing. Jack’s broad experience includes launching and establishing analytics, virtualization, and storage companies and leading marketing and business development for an early-stage cloud storage software provider. Jack has also held senior executive roles with EMC, Rainfinity, Brio Technology, SQRIBE, and Bain & Company. Jack has an MBA from UCLA’s Anderson School of Management and a BA in economics with honors and distinction from Stanford University.
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