In this special guest feature, Michele Chambers, EVP Anaconda Business Unit & CMO, Continuum Analytics, discusses how in 2015, President Obama appointed DJ Patil as the first Chief Data Scientist and Deputy Chief Technology Officer for Data Policy to focus on using data to shape policies and practices, and how going forward it is important for all governments to understand that Data Science is crucial to all decision making. Michele is an entrepreneurial executive with over 25 years of industry experience. She has authored two books; Big Data Big Analytics, published by Wiley, and Modern Analytic Methodologies, published by Pearson FT Press. Prior to Continuum Analytics, Michele held executive leadership roles at database and analytic companies, IBM, Netezza, Revolution Analytics, MemSQL and RapidMiner. In her career, Michele has been responsible for strategy, sales, marketing, product management, channels and business development. She holds a B.S. in Computer Engineering from Nova Southeastern University and an M.B.A. from Duke University.
Data science has seen a seismic shift over the past five years. The data analytics market used to be ruled by proprietary, product-oriented solutions, locking users into a vendor’s “one size fits all” approach. This gave companies limited access and a limited understanding of the power their data held. The Open Data Science movement is changing that—it has unlocked a level of innovation and collaboration in data analytics that is now a driving force across every major industry. By empowering data scientists to think creatively and stay on the cutting edge of technology, modern analytics is building a community of visionaries who are solving the world’s biggest problems collaboratively with Open Data Science. And it’s not just our boardrooms and classrooms that are leveraging Open Data Science—it’s our government, too.
In 2013, President Obama launched Project Open Data, a sweeping open data policy within the government that encourages all departments, partners and the American public to see data as an asset, and to share it. This is how Data.gov was born, a sprawling database of minable data that is free, publically available and growing. The Obama administration has even created its own landing page called Open White House that offers extensive data to the public on White House activity and policies, from visitor records to the 2017 Budget.
To further the data science initiative, President Obama appointed well-known data scientist DJ Patil as the U.S.’s first Chief Data Scientist in 2015. The goal of this appointment was to instigate a shift to a more data-centric government and, ultimately, exploit the power of data to uncover insights and contribute to improving life for the American people. The Obama administration believes “responsible openness in government and data strengthens our democracy, fuels innovation and promotes efficiency, effectiveness and accountability.” Open Data Science should continue to play a key role in government, but the future remains unclear.
Leveraging data science in politics is not new. U.S. presidential campaigns have used data to properly allocate resources by identifying particular voter segments, collecting demographics, developing electoral maps, analyzing previous voter patterns and to gain insight into hot-button issues to determine a campaign focus. In fact, the effective use of big data analytics during both the 2008 and 2012 campaign seasons is largely cited by political analysts as one of the major reasons Barack Obama emerged a victor—both times.
On a micro level, Open Data Science is being used by government in the areas of healthcare, criminal and social justice and infrastructure planning, to name a few. One area of government that is harnessing the power of data science effectively is tax policy reform. The American Enterprise Institute’s (AEI) Open Source Policy Center (OSPC) is leading a tax policy reform initiative that created the open source platform, TaxBrain. TaxBrain allows users to simulate and study the effect of tax policy reform using open source economic models. It leverages a data set that mirrors the multivariate distribution of income, deduction and credit items from 2009, delineated to 2015-2026 levels in accordance with the spring 2016 Congressional Budget Office forecasts of macroeconomic aggregates. In plain English, using Open Data Science, policy makers and everyday people are able to analyze different tax policies effectively and transparently. This brings the public sector into the decision making process by giving them the tools needed to join the tax reform conversation.
For data scientists, TaxBrain is just one example of how open source can impact policy reform in the United States. By making tax reform data accessible, it democratizes a process that historically has been very complex and inaccessible to the public. But, the innovation doesn’t stop there. Harvard University has created a catalog of use cases where cities around the country have used data science to improve policies, offering data-driven solutions to everything from pothole maintenance to ambulance response times. This catalog is an open source tool for local governments everywhere to learn from, proving yet again that Open Data Science is needed at every level.
From national tax policies to local infrastructure, the opportunities for data science in government are infinite. This is particularly true as we move toward a world where data-driven decisions are a necessity in every sector, not a luxury. To stay on the cutting edge of technology, and to keep American government transparent, we need to continue what was started by DJ Patil no matter who is leading the country, weaving Open Data Science initiatives into our infrastructure, at every level.
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