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Location Data Knowledge Base

Data methodologies, and Release schedules.
The Australia and New Zealand Spatial Data includes analytics-ready data from TomTom as well as data-specific analysis tools to get the most from the packaged data. The documentation package includes –   Release notes Spatial products include documentation on drive time methodology and Alteryx map layers   Release Documentation download: http://downloads.alteryx.com/ReleaseDocumentation/Q32017_AUNZ_Spatial.zip
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The US Data package includes analytics-ready data from TomTom, Experian, Dun & Bradstreet and the US Census as well as data-specific analysis tools to get the most from the packaged data. The documentation package includes –   Release notes, variable list and change log Experian CAPE demographic data methodology document, Mosaic segment descriptions Experian ConsumerView Analytical file – user guide and penetration report Simmons overview D&B Analytical file - data description, SIC lookup code, penetration report Kalibrate Technologies traffic count overview and metadata Spatial products include documentation on drive time methodology and Alteryx map layers   Release Documentation download: http://downloads.alteryx.com/ReleaseDocumentation/Q22017_US_Data.zip
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The Canada Data package includes analytics-ready data from TomTom, Dun & Bradstreet and Statistics Canada as well as data-specific analysis tools to get the most from the packaged data. The documentation package includes –   Release notes, variable list and change log D&B Analytical file - data description, SIC lookup code, penetration report Spatial products include documentation on drive time methodology and Alteryx map layers   Release Documentation download: http://downloads.alteryx.com/ReleaseDocumentation/Q22017_CA_Data.zip
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The Canada Spatial Data includes analytics-ready data from TomTom as well as data-specific analysis tools to get the most from the packaged data. The documentation package includes –   Release notes, variable list and change log Spatial products include documentation on drive time methodology and Alteryx map layers   Release Documentation download: http://downloads.alteryx.com/ReleaseDocumentation/Q22017_CA_Spatial.zip
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The UK and Republic of Ireland (ROI) Spatial Data includes analytics-ready data from TomTom as well as data-specific analysis tools to get the most from the packaged data. The documentation package includes –   Release notes Spatial products include documentation on drive time methodology and Alteryx map layers   Release Documentation download: http://downloads.alteryx.com/ReleaseDocumentation/Q22017_UKROI_Spatial.zip
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The Brazil (BR) Spatial Data includes analytics-ready data from TomTom as well as data-specific analysis tools to get the most from the packaged data. The documentation package includes –   Release notes Spatial products include documentation on drive time methodology and Alteryx map layers   Release Documentation download: http://downloads.alteryx.com/ReleaseDocumentation/Q22017_BR_Spatial.zip
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The US Spatial Data includes analytics-ready data from TomTom and the US Census as well as data-specific analysis tools to get the most from the spatial data. The documentation package includes – Release notes, variable list and change log Spatial products include documentation on drive time methodology and Alteryx map layers   Release Documentation download: http://downloads.alteryx.com/ReleaseDocumentation/Q22017_US_Spatial.zip
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The Australia and New Zealand Spatial Data includes analytics-ready data from TomTom as well as data-specific analysis tools to get the most from the packaged data. The documentation package includes –   Release notes Spatial products include documentation on drive time methodology and Alteryx map layers   Release Documentation download: http://downloads.alteryx.com/ReleaseDocumentation/Q22017_AUNZ_Spatial.zip
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The Europe (EU) Spatial Data includes analytics-ready data from TomTom as well as data-specific analysis tools to get the most from the packaged data. The documentation package includes –   Release notes Spatial products include documentation on drive time methodology and Alteryx map layers Countries included in this install are:   Andorra Austria Belgium Croatia Czech Republic Denmark Finland France Germany Gibraltar (British Overseas Territories) Hungary Italy (including Vatican City) Liechtenstein Luxembourg Monaco Netherlands Norway Poland Portugal San Marino Slovakia Slovenia Spain Sweden Switzerland    Release Documentation download:  http://downloads.alteryx.com/ReleaseDocumentation/Q22017_EU_Spatial.zip
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Shipping and Gallery schedule for data delivered to licensees of Alteryx Designer with Data, Alteryx Designer with Spatial and CASS. 
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Question Why do values in the ConsumerView HH & Individual fields contradict the Household Composition Code?  Sometimes other field values in a CV household record don't support the description of the Household Composition value.  For example, there might be two adult females in a household record but the Household Composition is A (HH w/1 adult female).  Or another record has 2 adults with a Composition code of B (HH w/1 adult male).  Answer   The first thing to note is the ConsumerView file delivers 6 of up to 8 persons in a Living Unit.  Not every person is delivered which may impact the Household Composition Code.  Another consideration is the description does not define the exact makeup of the household.  For example, a Household Composition code of "A" (HH w/1 adult female) does not mean this household is exclusively made up of a single adult female.   Household Composition - This field is calculated based on gender and children present in the Living Unit.  On the Household Composition, Experian looks at everyone in the Living Unit provided to them and determines how many adults are present in each Living Unit, gender of those individuals and if children are present in that living unit, coding them according to the codes chart. * A = HH w/1 adult female (no adult male, no child) * B = HH w/1 adult male (no adlt F, no child) * C = HH w/1 adult female and 1 adult male (no child) * D = HH w/1 adult female, 1 adult male and children present * E = HH w/1 adult female and children present (no adult male) * F = HH w/1 adult male and children present (no adult female) * I = HH w/2 or more adult males and children present (This does not mean there is not an adult female present in the household) * J = HH w/2 or more adult females and children present (This does not mean there is not an adult male present in the household) * G = HH w/2 or more adult males (An adult female can also be present in household, no child)) * H = HH w/2 or more adult females (An adult male can also be present in household, no child) * U = Unable to code   Records coded with C and D are typically scenarios where there's a male and female with/without children.  I - H could be one of these situations below: 1.) Scenarios where an elderly parent living with their adult children. 2.) Roommates (both male and female, young and old) 3.) Scenarios where a married couple allows an in-law (the brother or sister of a spouse) to reside with them 4.) Scenarios where a relative (uncle, cousin, etc.) may live with their relatives 5.) College age children (ages 19+) living with parents.   When might the Household Composition value not match the houehold attributes?  In one scenario, 2 Adults in a household with a Code of "A," more than likely there are two female adults in the household. This could be a roommate situation, it could be a mother and older daughter. Only one female may be a PDM in a household. Because of this, the record would receive the Household Composition code of “A” meaning a household with one adult female even though there are two adult females present.    In the "Question" example of two adult females in a household record but the Household Composition is A (HH w/1 adult female), this household looks as if it is more likely two sisters residing together as the ages are close together. One is listed as the PDM, the other is listed as the other adult. The system assigned the living unit an A denoting the female PDM.   The second "Question" example of 2 adults with a Code of "B" may be a household with a parent living with adult child situation. The adult child is coded as the PDM and the other person is only an initial and coded as the other adult. The system assigned the living unit a B denoting the male PDM.   In situations where fields in specific records are questionable and need further validation, provide those records to data_products@alteryx.com explaining the issue.  Also include the vintage of the ConsumerView Household or Individual file.     Experian's ConsumerView file is built directly from hundreds of public and proprietary sources.  They employ rigorous data testing including applying proprietary models and algorithms to ensure only the most deliverable addresses and accurate data elements are on the ConsumerView database.  Attached to this article is an excellent User Guide for the ConsumerView dataset. This User Guide is also included in the US Data Bundle documentation.
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This question comes up frequently because some of the US Data and Spatial datasets are HUGE and we want to ensure there's enough hard drive space available.  To help users better anticipate hard drive requirements, file sizes are included on the installation media in the Documentation folder of the update in a Excel worksheet. The .xlsx is titled Alteryx Qx 201x Variable List and includes file sizes for the United States and Canada in a worksheet labeled File sizes.  File sizes reflect the installed file size.   If you have questions or comments about this table, send an email to products@alteryx.com. 
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Download and install instructions for the Spatial data installs.
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Download and install instructions for the Data (US) install on AWS3.
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Download and install instructions for the Data (US and Canada) data installs.
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We are trying to understand the difference between employees and daytime population.   It looks like some of the population may be double counted.  Can you explain what rows are used for the 2014 Total Daytime population #.      Methodologies are different for Employees and Daytime Population.   Employees & Establishments in Business Summary are sourced from the D&B Business list and summarized to a geographic level although delivered in the Experian CAPE release.  The employee counts are as accurate as the D&B employee value but are also subject to block centroid allocation used for population. Employment fields from the Occupation & Employment folder are based upon the American Community Survey, modeled to a current year value and are part of CAPE. Daytime Population is sourced from Experian and are compiled values using several CAPE fields.  The excerpt below is pulled from the Tech Overview delivered to clients.      Daytime PopulationDaytime Population – Current Year Estimates (CYE) The Daytime Population database is created using a variety of methodologies applicable for different subsets of the Total Daytime Population. These subsets are then added together to create the Total Daytime Population. The process starts by identifying key subsets of the residential population that are assumed to stay in or close to their home location during the day. In particular, the following subsets of population are assumed to remain in the same Block Group during the day as the Block Group in which they live (or reside): Residential Population : Children aged less than or equal to 2 Residential Population : Civilian aged 16+ population that are unemployed Residential Population : Civilian aged 16+ population that work at home Residential Population : Population aged 65+ who are retired Residential Population : Population aged 16+ who are homemakers Residential Population : Population aged 16+ who are in the Armed Forces All of the above variables can be directly obtained from previously calculated CAPE – Demographics – Current Year Estimate (CYE) residentially-based variables, except for the ‘Residential Population : Population aged 16+ who are homemakers’. This variable is calculated by applying suitable localized proportions to the existing ‘larger population’ variable of the ‘Civilian aged 16+ population who are ‘Not in Labor Force’. Applying these proportions determines the subset of this ‘larger population’ that are estimated to be homemakers. Once these initial subsets of Daytime Population who are assumed to stay in their residential Block Group during the daytime are defined and accounted for, then the daytime location of other population types are modelled. It is assumed that these remaining population types are much more likely to travel out of their residential Block Group to reach their typical daytime location than is the case for the population groups previously accounted for. However, flows from home address to daytime address that occur completely within the same Block Group are also possible for these types. First, the estimate of daytime population at place of work that has already been modelled for the Mosaic Workplace database is accounted for. This variable is: Daytime Population, Civilian 16+, at WorkplaceAfter the above, the main population groups left to be modelled are: Within the work to create Mosaic Workplace, this variable is estimated using Census Tract-to-Tract flows of workers from residence to workplace, and National Business Database data to update these flows and allocate them from Tract level to Block Group level. Daytime Population, Students : Prekindergarten to 8th grade Daytime Population, Students : 9th grade to 12th grade Daytime Population, Students : Post-secondary students Daytime Population: Any remaining Civilian aged 16+ population that are ‘Not in Labor Force’ and have not yet been accounted for. All of the three student populations are modelled using a variety of data from the National Center for Education Statistics (NCES) and also information from key institutions (i.e. universities/colleges) themselves. After making allowance for students registered at an institution but very unlikely to travel to that institution on a typical day (for example, students undertaking online courses), this information is compiled and modelled to create an initial estimate of the typical number of students that spend the day at the location (or campus) of each institution. These figures are then calibrated so that the initial estimates of students who spend a typical day at the location of each institution, and those who stay within their residential Block Group during a typical day, are balanced to equal the national number of students within each category (i.e. Prekindergarten to 8th grade, 9th grade to 12th grade, Post-secondary students). Once all students have been accounted for, current estimates of each relevant daytime population sub-group are tallied and compared to the national estimate of ‘Residential Population: Civilian aged 16+ population that are Not in Labor Force’. The above work does not yet account for a proportion of this population group. The, as yet unaccounted for, proportion of this group is therefore calculated and assumed to spend a typical day within the Block Group in which they live. Having allocated all of the relevant subsets of residential population to either the Block Group in which they reside, or to another Block Group which they are estimated to travel to in order to spend a typical day, then the two final variables in the database are calculated: Daytime Population Aged 16+ Total Daytime Population (i.e. all ages)
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  Households or individuals may be excluded from the ConsumerView file for multiple reasons.  If an example list of names is provided to data_products@alteryx.com, they can be validated with Experian.  Otherwise, here are examples of exclusions: Households at addresses may be renters with no deed information available Household only has cell phones and is not in the phone book white pages Privacy - many people see to it their name is never on any kind of mailing list when doing business with companies Below is an excerpt on Experian's privacy & Compliance: Experian Marketing Services’ Approach to Privacy EMS is a steward of the information it collects, maintains, utilizes and shares.  Our stewardship is anchored in a values-based approach to privacy.  Our information values focus squarely upon the protection of information in our care and the safeguarding of consumer privacy through appropriate and responsible use.  For more information regarding our approach to privacy, please visit our web site at http://www.experian.com/privacy/index.html . Direct Marketing Association As a member and Board of Directors participant of the Direct Marketing Association (DMA), EMS drives the adoption of, and subsequently abides by, and encourages its clients to adhere to, the DMA’s Privacy Promise and Guidelines for Ethical Business Practices.  The Privacy Promise is a public assurance to American consumers that DMA members follow specific practices to protect consumer privacy.  Specifically, the Privacy Promise requires member companies to:   Provide notice of consumers’ ability to opt-out Honor consumer opt-out requests Maintain an in-house opt-out suppression file Use the DMA Preference Service suppression files (e.g., MPS, TPS, e-MPS) Promote industry-wide compliance with DMA self-regulatory guidelines  Why are some people not contained in the Experian ... For additional information, contact data_products@alteryx.com
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The Q3 2018 US Spatial package includes analytics-ready data from TomTom and the US Census as well as data-specific analysis tools to get the most from the spatial data. The documentation package attached includes –   Release notes, variable list and change log Spatial products include documentation on drive time methodology and Alteryx map layers   What's new in this release?   Sample workflows included with the data installs are now grouped within a top-level "Data Install Samples" category Annual updates for Places, Other Name Places, CBSAs, and CCDs/MCDs   Please download and extract the attached 'Q32018_US_Spatial.zip' for the complete documentation.
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The Q3 2018 Canada Data package includes analytics-ready data from TomTom, Dun & Bradstreet and Statistics Canada as well as data-specific analysis tools to get the most from the packaged data. The documentation package attached includes –   Release notes, variable list and change log D&B Analytical file - data description, SIC lookup code, penetration report Spatial products include documentation on drive time methodology and Alteryx map layers   What's new in this release?     1600+ Language Characteristics variables from the Statistics Canada 2016 Census regarding “mother tongue” and “language spoken at home” Business Summary built for Statistics Canada 2016 Dissemination Area inventory Sample workflows included with the data installs are now grouped within a top-level “Data Install Samples” category   Please download and extract the attached 'Q32018_CA_Data.zip' for the complete documentation.
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The Q3 2018 Australia & New Zealand Spatial package includes analytics-ready data from TomTom as well as data-specific analysis tools to get the most from the packaged data. The documentation package attached includes –   Release notes Spatial products include documentation on drive time methodology and Alteryx map layers   Please download and extract the attached 'Q32018_AUNZ_Spatial.zip' for the complete documentation.
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