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Big Data's mission is two-fold: 1) to apply cutting-edge data collection and analytics techniques to ensure the U.S. Census Bureau can maintain its high quality data products in a timely and efficient manner in the 21st Century; and 2) to create new products for public and business users. Our focus is on using data from both outside and inside the U.S. Census Bureau to improve current statistical products, provide new opportunities for research and innovation, and create new products and processes while reducing costs.
Big data is a term used to describe data sources that are fast-changing, large in both size and breadth of information, and come from sources other than surveys. Examples include retail and payroll transactions, satellite images, and "smart" devices. Big data also includes administrative data from federal, state, and local governments, as well as third party providers. Typically, big data is “found” or “observed”, in that it is collected passively as the digital exhausts of personal and commercial activities. Such seemingly disparate data sources and techniques can provide unique insights that were not easily observable previously. Combining big data from different sources for the U.S. Census Bureau’s research purposes and product development requires utilization of new techniques, including machine learning.
The U.S. Census Bureau is charged with gathering accurate information on the U.S. population and economy. By utilizing big data sources and techniques, we can use our existing data more efficiently, and generate new insights previously beyond the capabilities of both the government and private sector. Using the U.S. Census Bureau's unique position in the Federal Statistical System, big data allows us to combine and create data products from government agencies and private sources for the first time, creating a new wave of statistical products and economic insights. The use of big data sources and techniques allows us to generate more accurate, granular and timely statistics at lower costs, helping the U.S. Census Bureau transform itself into a statistical agency for the 21st Century.
Examples:
Working with partners inside and outside of the federal government, we are applying big data research techniques to:
Administrative Records
View information on Administrative Records for Research at the U.S. Census Bureau.
Behavioral Science Methods
The Center for Survey Measurement (CSM) conducts research on questionnaire design and evaluation.
Data Science
View information on Data Science for Research at the U.S. Census Bureau.
Disclosure Avoidance
Learn more about areas of statistical disclosure control, confidentiality, and disclosure limitation.
Federal Statistical Research Data Centers
The Federal Statistical System Research Data Centers are partnerships between federal statistical agencies and leading research institutions.
General Economic Research
View information on General Economic Research at the U.S. Census Bureau.
Mortality Disparities in American Communities (MDAC)
Research database on 2008 American Community Survey respondents and a follow-up of mortality outcomes through 2015.
Paradata
View information on Paradata for Research at the U.S. Census Bureau.
Statistical Research
CSRM conducts research on statistical design, modeling, and analysis methods for the Census Bureau's data collection, analysis, and dissemination programs.
Time Series and Seasonal Adjustment
Seasonal adjustment is the estimation of the seasonal component, followed by their removal from the time series.
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