Your company relies on data to succeed—data that traditionally comes from a business's transactional processes, pulled from the transaction systems through an extract-transform-load (ETL) process into a warehouse for reporting purposes. But this data flow is no longer sufficient given the growth of the internet of things (IOT), web commerce, and cybersecurity. How can your company keep up with today's increasing magnitude of data and insights? Organizations that can no longer rely on data generated by business processes are looking outside their workflow for information on customer behavior, retail patterns, and industry trends. In this report, author Christopher Gardner examines the challenges of building a framework that provides universal access to data. You will: Learn the advantages and challenges of universal data access, including data diversity, data volume, and the speed of analytic operations Discover how to build a framework for data diversity and universal access Learn common methods for improving database and performance SLAs Examine the organizational requirements that a fast universal data access platform must meet Explore a case study that demonstrates how components work together to form a multiaccess, high-volume, high-performance interface About the author: Christopher Gardner is the campus Tableau application administrator at the University of Michigan, controlling security, updates, and performance maintenance.
