Strata + Hadoop World Singapore 2016

We’ll be in Singapore this winter, talking about data strategy, and tools for your business. Let us know if you’ll be there, and we look forward to saying hi.

Tuesday, December 6

Big data and data science have great potential for accelerating business, but how do you reconcile the business opportunity with the sea of possible technical solutions? Fundamentally, data should serve the strategic imperatives of a business—those key strategic aspirations that define the future vision for an organization. A data strategy should guide your organization in two key areas—what actions your business should take to get started with data and where to start to realize the most value.

John Akred and Scott Kurth explain how to create a modern data strategy to power data-driven business.

Topics include:

• Why have a data strategy?
• Connecting data with business
• Devising a data strategy
• The data value chain
• New technology potentials
• Project development style
• Organizing to execute your strategy

Wednesday, December 7

Spark and Kafka are white-hot, but why does it matter? Some technologies cause more excitement than others, and at first the only people who understand why are the developers who use them. This talk provides a tour through the hottest emerging data technologies of 2016 and explains why they’re exciting, in the context of the new capabilities and economies they bring.

The secret power of big data technologies is that they promote flexible development patterns, ready to adapt to business needs, and economic scaling—but years of focusing on the label “big” has obscured much of the value to those approaching the topic. Skepticism and hype-fatigue are understandable reactions.
We’ll look at the excitement surrounding this year’s emerging platforms of choice, and explain where they fit into a complete data architecture, and what they have to offer in terms of new capabilities, efficiencies, and economy of use.

Among other topics, we’ll cover:

• Spark
• Kafka
• Notebooks
• Docker and containers
• the state of Hadoop
• big data in the cloud

This talk is intended for business leaders, and anybody who wants to articulate the value of technology to the business.

Come by John’s office hour to talk about data strategy and data valuation.

Data is difficult to value in large part because, economically, it does not adhere to the three main conditions of a traditional market system. In addition, traditional valuation methods of intangible assets do not apply to data valuation.

• Cost – data is often produced as a by-product of other business processes, making its cost hard to pin down
• Comparables – data varies greatly by content and quality so comparables are difficult to find
• Forecasts – the dominance of data aggregators and one-on-one deals in the buying and selling of data obscure the prices of any comparables that may actually exist in the market

While a traditional valuation of data’s value in general may not be applicable, I can think of data’s value in the context of specific uses and intentions within the organization. In this talk, I discuss and give several examples of how to use methods such as the Value of Information (VOI) framework and A/B testing to assess whether or not a third party data source should be purchased or continue to be purchased. I also show how mutual information (MI) can be used to assess value of a data source once it is in use within the organization.