Epilogue: The Future of Political Data Science
The 2016 election cycle will be remembered for many things, but for those who work in politics, it may be best remembered as the year that political data reached maturity. For years, much of the “old guard” of political strategists resisted the growing influence of data and analytics, preferring to stick with a more traditional formula: instinct and experience built up over time. This conflict persisted even as the 2008 and 2012 presidential races showed the advantages data can provide, particularly when one campaign has a distinct technological edge. In 2016, though, it’s clear that this fight is all but over, and the data side has won.
When it comes to technology, political data science is likely to follow a similar trajectory to the one playing out in the broader field of data science. If anything, the political field is particularly well-suited to rapid adoption of new technologies, since the election cycle allows for many organizations to completely overhaul their technology every 2 to 4 years. Though physical hardware is still used by many organizations, the adoption of cloud platforms like Amazon Web Services and Microsoft Azure has quickly become mainstream. Along the same lines, while commercial data analysis software such as Stata and SPSS was once standard, most organizations are now relying mainly on open source tools like Python and R. And as the scale of our datasets grows, traditional relational databases such as MySQL and Microsoft SQL Server are being replaced with distributed platforms such as HP Vertica, Amazon Redshift, and the Hadoop ecosystem.
For novice and veteran data scientists alike, working in politics is a great opportunity to quickly build skills working with some of the most advanced technology and techniques available. While it’s probably too late for readers to become part of a campaign this year, you don’t need to wait until 2020 to get involved. In 2017, there will be elections for governor and state legislature in both Virginia and New Jersey, mayoral races in many cities including New York, Los Angeles, Seattle, and Boston, and a variety of other local contests throughout the country. And in 2018, voters will elect 36 governors, 33 US senators, and all 435 members of the US House of Representatives. So even after the presidential race is over, the field of political data science will continue to grow and evolve for many years to come.