fleetside72 / pivot_scale

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worked on so far

setup

the basic assumption is a single sales table is available to work with that has a lot of related data that came from master data tables originally. the goal then is to break that back apart to whatever degree is necessary.

  • run schema.sql and perd.sql to setup basic tables
  • create a table fc.live as copied from target (will need to have columns version and iter added if not existing)
  • run target_info.sql to populate the fc.target_meta table that holds all the columns and their roles
  • fill in flags on table fc.target_meta to show how the data is related
  • run build_master_tables.sql to generate foreign key based master data

routes

  • all routes would be tied to an underlying sql that builds the incremental rows
  • that piece of sql will have to be build based on the particular sales layout
    • columns: a function to build the columns for each route
    • where a function to build the where clause will be required for each route
    • the result of above will get piped into a master function that build the final sql
    • the master function will need to be called to build the sql statements into files of the project

route baseline

  • forecast = baseline (copied verbatim from actuals and increment the dates) + diffs. if orders are canceled this will show up as differ to baseline
  • regular updates to baseline may be required to keep up with canceled/altered orders
  • copy some period of actual sales and increment all the dates to serve as a baseline forecast
  • join to period tables to populate season; requires variance number oof table joins, based on howmany date functions there are 🙄
  • some of the app parameters can be consolidated, the baseline period could be one large range potentially, instead of 2 stacked periods
  • setup something to fill in sql parameters to do testing on the function
  • update node to handle forecast name parameter
  • calc status is hard-coded right now in the json request -> probably needs to be manuall supplied up front

scale

  • need to add version columns to all CTE's
  • need to build log insert
  • Need to build where clause for scenario

running problem list

  • baseline route
    • problem: how will the incremented order season get updated, adding an interval won't work
      • a table fc.odate, has been built, but it is incomplete, a setup function filling in these date-keyed tables could be setup
      • if a table is date-keyed, fc.perd could be targeted to fill in the gaps by mapping the associated column names
    • problem: the target sales data has to map have concepts like order_date, and the application needs to know which col is order date
      • add column called application hook
    • there is not currently any initial grouping to limit excess data from all the document# scenarios
  • general
    • clean up SQL generation to prevent injection
    • how to handle a target value adjustment, which currency is it in?
    • the sales data has to have a column for module and change ID, live sales data isn't going to work well
      • need to target the live sales data, build build a whole new table to use it plus add version columns

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License:MIT License


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