Opportunity Areas

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Data Analytics

Definition

Data science, analysis, management and policy, particularly in areas where data is sensitive (e.g. health care, national security) or new approaches are emerging (e.g. big data).

Overview

Data analytics – the analysis of large amounts of data to uncover patterns and correlations that give business insights such as customer preferences and market trends – can help organizations and firms raise productivity, improve decision making, and gain competitive advantage. Market research firm IDC estimates the global market for big data and business analytics hardware, software, and services will increase by over 50% to $203 billion in 2020.1 IT services and business services make up more than half of the data analytics market, while data analytics software makes up over a quarter.

Technology and policy have further created new streams of data to analyze. As electronic health records are increasingly used by healthcare organizations (spurred in part by regulation), they create new potential for insights from the data generated, leading to even greater demand for data analytics capabilities. In particular, financial sector, insurance, and health care IT are projected to require high levels of data analytics expertise. The precision medicine market, for example, is expected to top $88 billion by 2022, a significant portion of which will go not to life sciences firms but to technology brands such as IBM and Intel for analytics capabilities.2

Example Industries and Businesses

  • Electronic health record analysis
  • Financial predictive analytics
  • Credit data analysis

Example Worker Specialties and Skills

  • Data management and analytics
  • Data science and statistics
  • Research
  • Engineering and computer science
  • Machine learning
  • Post-secondary education
  • Business administration and development (e.g. sales)
  • Medical records and health information technicians
  • Computer user support specialists

Visit the initiatives page and filter Opportunity Area by “Data Analytics” to see initiatives related to this opportunity area.

DC’s Comparative Advantage

Based on our analysis and stakeholder interviews, DC has the following comparative advantages:

Existing Strength of Data Analytics Industry

The DC metro area has a number of leading data analytics firms focusing on business intelligence (helping organizations get insights and make more informed decision through analysis of their data). These firms include APT (business analytics software for large, consumer-facing businesses), Logi Analytics (interactive data visualization products for business intelligence and business analytics), and MicroStrategy (business intelligence analytics platform). With DC’s strong analytics base, there is opportunity to grow the healthcare IT and consulting base to respond to increasingly complex data needs.

Expertise in Meeting Demand for Big Data Analysis from Federal Agencies

The ability to extract insights from data is increasingly crucial to the way federal agencies work; DC’s proximity to government agencies thus puts data analytics firms near a major customer base. Fourteen major federal departments and agencies, as well as the District, now have Chief Data Officers, and federal spending on big data solutions (primarily services) is projected to increase from $1.95 billion in FY16 to $3.55 billion in FY21, an annual growth rate of 13%.3 Private sector federal contractors in the DC metro area have supplied much of the desired analytics capabilities. The DC metro area can build on this existing expertise in management of large data sets, as well as on extracting and applying insights from big data.

Intellectual Hub for Data Privacy and Other Data Policy Issues

Data privacy is a major issue for big data analytics. Companies that misuse data not only face regulatory consequences, but also consumer reluctance to entrust the firms with their data. The consequences are even starker when it comes to sensitive data about individuals such as personal health, tax, or financial data.4  Stakeholders commented that DC’s status as an intellectual hub for data policy issues and DC-area firms’ expertise in analyzing, handling, and protecting federal government and citizen data combine to make the District a natural center for data analytics of sensitive data. DC is also a center for the use of data to study policy, as seen in the creation of the Massive Data Institute at Georgetown’s McCourt School of Public Policy to study high-dimensional data and answer public policy questions.

Activating this Opportunity Area

Based on our analysis of this sector and stakeholder interviews, the following actions could help develop this opportunity area:

Expose and Train the Future Workforce on Data Analytics

There is a supply and demand imbalance in data scientists, particularly in experienced data scientists and statisticians who know how to uncover and solve complex problems for businesses and organizations.5 There are thus opportunities to increase exposure of DC residents and university students to data analytics as a potential career, and to provide them with experience working with data, including by making data sets available through the DC government’s open data initiatives.

Promote DC as a Thought Leader in Data Analytics

Given the District’s strengths in both data analytics and hosting conventions, it could attract more data-focused conferences to establish DC as a center for thought leadership in data analytics. The District could also convene and facilitate networks between government and private sector leaders in this space, as both types of organizations face similar challenges in analyzing data.

 

  1. IDC, Worldwide Semiannual Big Data and Analytics Spending Guide, October 2015. <https://www.idc.com/getdoc.jsp?containerId=prUS41826116>
  2. Research and Markets. Global Precision Medicine Market — Estimation & Forecast (2015-2022). November 2015. <http://www.researchandmarkets.com/research/lphfbf/global_precision>
  3. Rossino, Alexander. “Deltek sees continued growth in federal cloud and big data spending.” Deltek. 9 November 2016. < https://www.deltek.com/en/learn/blogs/b2g-essentials/2016/11/deltek-sees-continued-growth-in-federal-cloud-and-big-data-spending>.
  4. Reed, Tina. “The biodata gold rush” Washington Business Journal. 20 May 2016. < http://www.bizjournals.com/washington/print-edition/2016/05/20/the-biodata-gold-rush.html>
  5. Etkin, Scott. “Deloitte’s John Lucker on Analytics Trends.” Data Informed. 28 January 2016. <http://data-informed.com/deloittes-john-lucker-on-analytics-trends-2016/>