AM1: Developing a Modern Enterprise Data Strategy

A modern enterprise data strategy is critical in the digital age, where depth of operational sophistication and management of scale can be existential problems for growing enterprises. Fundamentally, data should serve the strategic imperatives of a business - those key strategic aspirations that define the future vision for an organization. Big data and data science have great potential for accelerating business, but how do you take it beyond aspirations and into a strategy? How do you reconcile the business opportunity with the sea of possible solutions, and make it fit your needs?

In this tutorial, we explain how we work to solve real business challenges with data, and build a platform for the future.

Why Have A Data Strategy?
Connecting Data With Business
Devising A Data Strategy
The Data Value Chain
New Technology Potentials
Project Development Style

We will also review the options for big data architectures, explaining how the various parts of the Hadoop and big data ecosystem fit together in production to create a data platform supporting batch, interactive and real-time analytical workloads.

By tracing the flow of data from source to output, we'll explore the options and considerations for components, including:

Acquisition: from internal and external data sources
Ingestion: offline and real-time processing
Storage
Providing data services: exposing data to applications
Analytics: batch and interactive
Data management: data security, lineage, metadata and quality

Founder of the pioneering data conference, O'Reilly Strata, Edd is a respected voice in the worlds of data, open source and the web. Bringing together deep technical know-how with market understanding, Edd makes sense of information technology and its trajectory.

Colette Glaeser is a Principal Data Strategist at Silicon Valley Data Science. With a proven track record in applying analytics to provide a competitive advantage, Colette brings over 20 years of experience in driving business development, customer insight, operational analysis and continuous process improvement across a range of industries. She uses her full understanding of the types of business questions that surface in support of profitability growth initiatives as well as an arsenal of analytic tools, methods, and technologies to translate data into insights that are actionable.