Order: Meta_Dates

What this view is for

Order.meta_dates provides the key lifecycle and delivery timing dates for customer orders.

Where:

  • Order.core_details defines what the order is
  • Order.meta_codes defines how it is classified

meta_dates explains when important order events occurred or are expected to occur.

This view is central to understanding order flow, conversion timing, and delivery expectations.


Level of detail (grain)

  • Multiple rows per order
  • One row per date attribute

This view is intentionally long and thin.
An order with several important dates will appear multiple times — once for each date type.


What you’ll find in this view

Each row represents a single date associated with an order, including:

  • OBJECT_SEQ – the paired company + order identifier
  • META_TYPE – the lifecycle context of the date
  • ATTRIBUTE – the specific event within that lifecycle
  • The date value itself

As with Busopp, the word “DATE” has been deliberately removed from attribute names.
In this context, every value is a date — clarity comes from meaning, not repetition.


Available date types

The following META_TYPE / ATTRIBUTE combinations are currently available:

META_TYPEATTRIBUTE
LIFECYCLEENTERED
LIFECYCLEWON
DELIVERYWANTED

META_TYPE provides the phase or context (lifecycle vs delivery), while ATTRIBUTE describes the specific event.


How to join this view

Every row includes OBJECT_SEQ, consistent with all Order views.

Always join Order.meta_dates to Order.core_details using OBJECT_SEQ.

This keeps timing aligned to the correct order and avoids accidental duplication.


Working with the long, thin date structure

As with other meta_* views, this table is designed for flexibility rather than immediate consumption.

In most reports, you’ll want to:

  1. Filter to the date types you need
  2. Create a combined attribute identifier
  3. Pivot to a wide, report-friendly shape

Creating a combined date attribute

Because META_TYPE provides essential context, it’s strongly recommended to create a combined attribute.

Example (Power Query):

= Table.AddColumn(
    Source,
    "DATE_ATTRIBUTE",
    each [META_TYPE] & "_" & [ATTRIBUTE],
    type text
)

This avoids ambiguity (for example, multiple “ENTERED” dates across domains) and makes shaping predictable.


Pivoting to a wide date table

Once the combined attribute exists, pivoting allows you to:

  • Turn each DATE_ATTRIBUTE into a column
  • Reduce each order to a single row
  • Work with explicit lifecycle and delivery dates in visuals and filters

This shape is especially useful for:

  • Time-based filtering
  • Delivery expectation analysis
  • Conversion and ageing metrics

How this view is commonly used

Order.meta_dates is typically used to:

  • Track when orders entered the system
  • Analyse the timing between opportunity win and order creation
  • Filter orders by expected delivery dates
  • Support pipeline ageing and fulfilment planning

It provides time context, not measures.


Things to watch out for

  • Be explicit about which date you are using in calculations
  • Avoid mixing lifecycle and delivery dates unintentionally
  • Don’t assume “WON” means the same thing in Busopp and Order — context matters

If a time-based measure feels unclear, revisit which META_TYPE + ATTRIBUTE is driving it.


Where this fits in a report build

A typical flow is:

  1. Start with Order.core_details
  2. Add Order.meta_dates for lifecycle and delivery timing
  3. Shape dates using a combined attribute and pivot if required
  4. Add meta_codes and item_values_lines for context and value

This keeps identity, timing, classification and value cleanly separated.


Key takeaway

Order.meta_dates gives you clear, contextual timing for customer orders.

The dates themselves are simple — their meaning comes from META_TYPE + ATTRIBUTE.
Shape it deliberately, pivot when useful, and order timing becomes far easier to reason about.

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