Saturday, 2 April 2016

R2B2 tries out the Analyst software tool

Local and regional economic development requires an understanding of the particular attributes of localities within regions. This attention to differentiation implicates the need for relevant datasets and a wide range of data including population age groups, types of business activities, skill availability and various government services. Relevant data to answer questions about phenomena within the region can be challenging to access. With training and access provided by OMAFRA, the R2B2 project is looking at Analyst, a software tool developed by EMSI. The advantage of Analyst is summarized as follows:
“Historically, you’ve had two main options for accessing employment data in Canada. You can get solid, detailed geographic data from the census, which is released once every five years (and two years late), or you can go with high-level province data from the SEPH or the LFS, which gives you data for every year but provides no detailed regional information. [Analyst] solves the problem. Taking advantage of the strengths of these sources, we harmonize them to create a single, complete picture so you can look at detailed, up-to-date employment data. We present the forest and the trees—every year.” (EMSI Canada)
R2B2 research team member, Mamun Chowdury, participated in a two-day OMAFRA training workshop called “Foundations for Regional Economic Analysis” to learn more about the Analyst software tool which unifies labour market data collected regularly from all the major data sources within Canada including Canadian Business Patterns (CBP), 2001, 2006 and 2011 Census and National Health Survey, Survey of Economic Payroll and Hours (SEPH), Labour Force Surveys (CFS), Canadian Occupational Projection System (COPS), Postsecondary Student Information System (PSIS) and StatsCan’s main socio-economic database, CANSIM. Analyst gives users access to statistics on 305 industry classifications using the NAICS (North American Industry Classification System), 522 occupations from Statistics Canada’s NOC-S classification and 386 educational program types from the CIP (Classification of Instructional Programs) taxonomy.  

By trying out Analyst, we aim to identify local and regional socio-economic assets and liabilities that may be relevant to broadband demand and use. A key benefit of using Analyst appears to be that it helps to explore available data and relationships among the data quickly. This enables us to prioritize areas where we might dive deeper into our analysis or compare findings to project datasets. For more information see the OMAFRA webpage on Analyst:


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