Ensuring the success of your big data implementation isn’t just as simple as buying a bunch of hardware and deploying Hadoop. Whether you are implementing big data for analytics, governance, data rationalization, or some other purpose, our goal is to help you understand how to overcome the wide variety of challenges involved in making big data work in your environment.
Failure to automate data ingestion has torpedoed many big data initiatives. The business impact is delayed delivery of data-driven applications, a loss of confidence in data completeness and quality and perceived failure of your data lake project.
Drawing upon customer examples, Kirit Basu from StreamSets and Mike Ferguson from Intelligent Business Solutions will discuss the current best practices for creating a data ingestion architecture that is efficient for developers, transparent for operators and agile in the face of evolving big data sources, infrastructure and deployment models.