Enterprise Dataversity 2016
Several of us will be in Chicago this year. Our talks are listed below, we look forward to chatting.
Monday, September 19
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.
- Modern Data Strategy
- Connecting Data with Business
- Devising A Data Strategy
- The Data Value Chain
- New Technology Potentials
- Project Development Style
What are the essential components of a data platform? This tutorial will explain how the various parts of the Hadoop, Spark 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
- Analytics: batch and interactive
- Providing data services: exposing data to applications
We’ll also give advice on:
- tool selection
- the function of the major Hadoop components and other big data
- technologies such as Spark and Kafka
- integration with legacy systems
Wednesday, September 21
Panel: At Least 20 Ways to Get Better at Data Strategy and Analytics
What value (and values) are you going to take back to work and put into practice next week? Which ideas are going to “stick” and make a difference to you, and to your organization? Reflecting on the past 3 days, our panelists will offer their “best of” advice and ideas from the presentations and we’ll invite you to share your own as well.
Thursday, September 22
Organizing around data is a concern for the whole business. The myth of the lone ranger data scientist is very much that: effectively leveraging data requires cross-functional collaboration, organizational adaptation, and an organizational understanding of what using data to create business value entails.
In this day-long tutorial, we will share our methods and observations from three years of effectively deploying data science in enterprise organizations. Attendees will learn how to build, run and get the most value from data science teams, and how to work with and plan for the needs of the business.
- Building the right culture
- Organizational concerns for data science
- Data science techniques for business
- Tools and platforms
- Managing and hiring data scientists
- Methods for running data science projects
- Deploying data science: from the lab to the factory