The business of running businesses is getting a wake-up call. From flattened hierarchies to an explosion of information, Big Data is reinforcing some old business assumptions and upending others. If you’ve got a business degree, and you haven’t figured out how to apply Big Data to administration, you’re vulnerable. In this opening session, Strata chair Alistair Croll sets the stage for JumpStart with an overview of business in a data-driven economy.
by Nolan Goldberg
Emerging technologies – such as big data – can change both the scope and practical impact of the law. For example, a Court in California recently held for the first time that a zip code was personally identifiable information within the meaning of the state’s Song Beverly Credit Card Act. Prior case law treated zip codes as identifying only groups of people at best and therefore zip codes were not personally identifiable information and requesting zip codes at the point of sale did not appear to be prohibited. The California Court, however, was forced to depart from precedent after acknowledging that easily accessible de-anonymization technologies now enabled retailers to use zip codes to determine exact home addresses. Accordingly, the well established practice of asking for zip codes at points of purchase needed to stop (and a flood of new lawsuits followed). Putting the above example aside, Big Data technologies have the potential to require changes in important areas of the law, such as intellectual property, e-discovery, data ownership and privacy. This session will explore both the potential impact of big data on the law generally and some of the specific legal issues of concern when monetizing big data.
by Cathy O'Neil
Data management teams need strong cloud computing and database management skills, and proficiency with tools like Hadoop, mapreduce jobs and SQL queries. The analysts need to be deep thinkers and creative modelers with experience in machine learning and financial modeling—ideally both. Being model- and data-driven means overnight data-crunching to produce daily data reports, which often lead to more overnight questions. There are also inherent difficulties in talking to clients and internal stakeholders when inherently unstable data and statistics are key tools for decision-making.
From a process standpoint, we need start asking new kinds of questions that Big Data is opening up for the first time. Speaker Cathy O’Neill will use her unique experience in finance, which is the field that is the most developed in terms of modeling, to explain how she sees today’s business world as relatively unsophisticated and ””spoiled for data.”” She’ll explain various techniques that financial analysts employ to improve models, and reconsider the practice of A/B testing in a model-driven world.
The abundance of data made it easy to collect and analyze data from online user behavior and discussions. Although it is encouraging to see businesses using such data and making data-driven decisions, we often see decisions based on flawed analyses, or simply using data that measure the wrong things. Panos will illustrate cases, where simple reading of available data points into one conclusion, while a deeper study uncovers a different truth. Examples will be drawn from online reputation systems, online reviews, crowdsourcing, and other case studies.
Life is all about competition whether nation states, organisations or individuals. This competition invokes a process of evolution and whilst the future cannot be predicted with any certainty, patterns are emerging. Two of the latest patterns include the use of ecosystems in the warfare between organisations and how open source is increasingly becoming deployed as a tactical weapon. This talk will explore these patterns, the underlying process of evolution, the new management practices that are appearing and the importance of big data in this new environment.
Customers are the reason you’re in business. To earn their continued love and loyalty, you must strive to enhance their experiences across all touchpoints. To earn a larger share of their pocketbooks, you must also target them with offers that suit their specific profiles, needs, and propensities. To these ends, leading-edge organizations have implemented “next best action” (NBA) technologies, such as “Big Data” analytics, within their multichannel customer relationship management programs. In this session, Forrester senior analyst James Kobielus will provide a vision, case studies, ROI metrics, and guidance for business professionals evaluating applications of NBA in their organizations.
by DJ Patil
Given the importance of data to critical decision making, the demand for Data Scientists is at an all time high. Yet, what does it really mean to be a Data Scientist and to build a team of Data Scientists? It’s a new world with startups to well established organizations struggling daily to recruit and structure their teams to best leverage those that can extract valuable insights from data. Unfortunately most organizations don’t realize all the places where a good Data Science Team can make an impact. In this talk we’ll walk through different organizational structures, how to empower, and key technologies required to establish a great Data Science team.
Big Data is often seen as a disruptor. But for many established businesses, it’s a rejuvenator. In this closing panel, members of the Strata JumpStart faculty reflect on the day’s proceedings, and set the stage for turning Big Data tools into augmented workers, building businesses that blend the best of human and machine.
What does a data MBA do differently? Wrapping up JumpStart, we’ll consider where businesses can find the low-hanging fruit, and how corporate culture will change as analytical thinking becomes the norm rather than the exception. As we face the data imperative, we’ll look at what it means to run a data-driven organization from the boardroom to the mailroom.
19th September 2011