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Study: Measuring investment in data, databases and data science

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Released: 2019-06-24

In 2002 and 2003 the Oakland Athletics surprised baseball aficionados by playing well enough to get into the playoffs despite the team having a budget far lower than many other teams in the league. Why? Because they had better data than all the other major league baseball teams. They were able to use these data to assess, draft and sign a group of players that formed a great team. In the 2019 NHL all-star game, players and pucks were fitted with sensors so coaches and fans could track their speed and maneuvering in real time.

Similarly, banks, retailers and other businesses routinely record the transactions of their clients in huge databases for use in marketing campaigns. Driverless cars, powered by data collected in an array of sensors, are becoming more of a reality every day. The number of companies collecting and using data to minimize costs, maximize sales and innovate is increasing, some say at an exponential rate.

Data, databases and data science have become increasingly important in the postwar period as the development and exploitation of digital storage and computation methods have improved dramatically. Millions of Canadians now have computers on their desks, in their laps, in their pockets and on their wrists. The appliances they use in everyday life—from cars, to refrigerators and stoves, to music players and cameras, to lights and thermostats—use digital technologies to facilitate, control and record their usage.

Many of the goods and services businesses and governments produce are much improved by incorporating digital features, and the processes they use to produce and market those products are benefiting greatly from digital automation. While productivity has no doubt grown rapidly through the adoption of digital methods, this progress has so far proven difficult to measure with precision.

While the proliferation and use of data is increasing, the value of this activity is not easily visible in the key economic indicators released by Statistics Canada. In the past, given the limited role data played in the economy, this 'data data gap' was not a priority. Today, with the pervasive and accelerating use of data, important elements of economic activity and growth may not be fully captured because of this gap.

To address this issue, Statistics Canada is leading the development of a conceptual framework for measuring the monetary value of data. The framework will help to answer important questions, such as "What is the production of 'data' in the economy?" and "What is the value of the stock of Canada's data holdings?"

A conceptual framework around data is needed, since data can be "anything and everything." This study, the first of its kind, explores the valuation of three types of data-related assets that have become increasingly important in the modern digital era. The three assets are derived, in a kind of hierarchical arrangement, from basic observations. When observations are captured in digital form, they become 'data'. When 'data', in turn, are organized in a well-structured, computerized form they become 'databases'. Finally, when 'databases' are used to explore a topic of interest by means of computerized transformation, analysis and modelling, the results become a type of intellectual property product (also referred to as research and development) called 'data science'.

A subsequent paper to be released on July 10, 2019, will offer the first-ever experimental estimates of the value of investment in data, databases and data science in Canada. It will serve as a benchmark for current and future refinements to improve measurements of the growing role data are playing in society and the economy.

  Note to readers

This study is an initial effort by Statistics Canada to define and measure the economic value of 'data' and its derivative products called 'databases' and 'data science'.

Data are defined as observations that have been converted into a digital form that can be stored, transmitted or processed and from which knowledge can be drawn. A database is an organized store of data that can be processed with the help of a computer. Data science is a form of research and development activity that involves transforming, analyzing and modelling the information in databases in order potentially to arrive at new findings that have economic value.


The document, "Measuring investment in data, databases and data science: Conceptual framework," which is part of Latest Developments in the Canadian Economic Accounts (Catalogue number13-605-X), is now available.

The Methodological Guide: Canadian System of Macroeconomic Accounts (Catalogue number13-607-X) is also available.

The User Guide: Canadian System of Macroeconomic Accounts (Catalogue number13-606-G) is also available.

Contact information

For more information, or to enquire about the concepts, methods or data quality of this release, contact us (toll-free 1-800-263-1136; 514-283-8300; or Media Relations (613-951-4636;

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