PR #174 includes the following changes:
- Addressed an issue in which some records in
zendesk__sla_policies
might erroneously have a nullsla_policy_name
due to system-generated millisecond-long gaps in timestamps. The package now compares timestamps to the nearestsecond
when selecting valid SLA policy names in int_zendesk__sla_policy_applied.
- Updated
consistency_sla_policies
andsla_count_match
data validation tests to account for the above change.
PR #171 includes the following changes:
- Support for schedule changes has been added. This feature is disabled by default since most users do not sync the required source
audit_table
. To enable this feature set the variableusing_schedule_histories
totrue
in yourdbt_project.yml
:
vars:
using_schedule_histories: true
- Schedule changes can now be extracted directly from the audit log, providing a view of schedule modifications over time.
- The
int_zendesk__schedule_spine
model is now able to incorporate these schedule changes, making it possible for downstream models to reflect the most up-to-date schedule data.- Note this is only in effect when
using_schedule_histories
is true.
- Note this is only in effect when
- This improves granularity for Zendesk metrics related to agent availability, SLA tracking, and time-based performance analysis.
dbt_zendesk_source changes (see the Release Notes for more details)
- Introduced the
stg_zendesk__audit_log
table for capturing schedule changes from Zendesk's audit log.- This model is disabled by default, to enable it set variable
using_schedule_histories
totrue
indbt_project.yml
.
- This model is disabled by default, to enable it set variable
- Holiday support: Users can now choose to disable holiday tracking, while continuing to use schedules, by setting variable
using_holidays
tofalse
indbt_project.yml
. - New intermediate models have been introduced to streamline both the readability and maintainability:
int_zendesk__timezone_daylight
: A utility model that maintains a record of daylight savings adjustments for each time zone.- materialization: ephemeral
int_zendesk__schedule_history
: Captures a full history of schedule changes for eachschedule_id
.- materialization: table (if enabled)
int_zendesk__schedule_timezones
: Merges schedule history with time zone shifts.- materialization: ephemeral
int_zendesk__schedule_holiday
: Identifies and calculates holiday periods for each schedule.- materialization: ephemeral
- Rebuilt logic in
int_zendesk__schedule_spine
to consolidate updates from the new intermediate models.
dbt_zendesk_source changes (see the Release Notes for more details)
- Updated the
stg_zendesk__schedule_holidays
model to allow users to disable holiday processing by setting variableusing_holidays
tofalse
.
- Resolved a bug in the
int_zendesk__schedule_spine
model where users experienced large gaps in non-holiday periods. The updated logic addresses this issue.
- Added the following DECISIONLOG entries:
- Entry addressing how multiple schedule changes in a single day are handled. Only the last change of the day is captured to align with day-based downstream logic.
- Entry to clarify backfilling of schedule history. The most recent schedule is sourced from
stg_zendesk__schedule
, while historical changes are managed separately, allowing users to disable the history feature if needed.
- Replaced instances of
dbt.date_trunc
withdbt_date.week_start
to standardize week start dates to Sunday across all warehouses, since our schedule logic relies on consistent weeks. - Replaced the deprecated
dbt.current_timestamp_backcompat()
function withdbt.current_timestamp()
to ensure all timestamps are captured in UTC. - Added seed data for
audit_log
to enhance integration testing capabilities. - Introduced new helper macros,
clean_data
andregex_extract
, to process complex text of the schedule changes extracted from audit logs. - Updated
int_zendesk__calendar_spine
logic to prevent errors during compilation before the first full run, ensuring a smoother development experience.
New model (#161)
- Addition of the
zendesk__document
model, designed to structure Zendesk textual data for vectorization and integration into NLP workflows. The model outputs a table with:document_id
: Corresponding to theticket_id
chunk_index
: For text segmentationchunk
: The text chunk itselfchunk_tokens_approximate
: Approximate token count for each segment
- This model is currently disabled by default. You may enable it by setting the
zendesk__unstructured_enabled
variable astrue
in yourdbt_project.yml
.- This model was developed with the limit of chunk sizes to approximately 5000 tokens for use with OpenAI, however you can change this limit by setting the variable
zendesk_max_tokens
in yourdbt_project.yml
. - See the README section Enabling the unstructured document model for NLP for more information.
- This model was developed with the limit of chunk sizes to approximately 5000 tokens for use with OpenAI, however you can change this limit by setting the variable
-
Incremental models running on BigQuery have had the
partition_by
logic adjusted to include a granularity of a month. This change only impacts BigQuery warehouses and was applied to avoid the commontoo many partitions
error some users have experienced when partitioning by day. Therefore, adjusting the partition to a month granularity will decrease the number of partitions created and allow for more performant querying and incremental loads. This change was applied to the following models (#165):int_zendesk__field_calendar_spine
int_zendesk__field_history_pivot
zendesk__ticket_field_history
-
In the dbt_zendesk_source v0.12.0 release, the field
_fivetran_deleted
was added to the following models for use inzendesk__document
model (#161):stg_zendesk__ticket
stg_zendesk__ticket_comment
stg_zendesk__user
- If you have already added
_fivetran_deleted
as a passthrough column via thezendesk__ticket_passthrough_columns
orzendesk__user_passthrough_columns
variable, you will need to remove or alias this field from the variable to avoid duplicate column errors.
- Fixed an issue in the
zendesk__sla_policies
model where tickets that were opened and solved outside of scheduled hours were not being reported, specifically for the metricsrequester_wait_time
andagent_work_time
. - Fixed an issue in the
zendesk__ticket_metrics
model where certain tickets had miscalculated metrics.- Resolved by adjusting the join logic in models
int_zendesk__ticket_work_time_business
,int_zendesk__ticket_first_resolution_time_business
, andint_zendesk__ticket_full_resolution_time_business
. (#167)
- Resolved by adjusting the join logic in models
- Added integrity validations:
- Modified the
consistency_sla_policy_count
validation test to group byticket_id
for more accurate testing. (#165) - Updated casting in joins from timestamps to dates so that the whole day is considered. This produces more accurate results. (#164, #156, #167)
- Reduced the weeks looking ahead from 208 to 52 to improve performance, as tracking ticket SLAs beyond one year was unnecessary. (#156, #167)
- Updated seed files to reflect a real world ticket field history update scenario. (#165)
Although this update is not a breaking change, it will likely impact the output of the zendesk__sla_policies
and zendesk__sla_metrics
models. PR #154 includes the following changes:
- Addresses the potential issue where the
first_reply_time_business_minutes
metric within thezendesk__ticket_metrics
model would incorrectly calculate the elapsed time when daylight savings occurred. This change involved adjusting a join to reference the difference of two dates as opposed to timestamps. This more accurately applies a cutoff event during daylight savings. - Introduction of an additional condition within the
filtered_reply_times
cte of theint_zendesk__reply_time_combined
model to ensure tickets replied to before any schedule begins and no business minutes have been spent is reserved for only the first day the ticket is open. Previously, this condition could be met on days other than the first. This would potentially result in duplicates ofsla_event_id
's further downstream in thezendesk__sla_policies
model.
- Addition of integrity and consistency validation tests within integration tests for the
zendesk__sla_policies
andzendesk__ticket_metrics
models.
Although this update is not a breaking change, it will significantly impact the output of the zendesk__sla_policies
model. PR #146 includes the following changes:
- Fixes the issue of potential duplicate
sla_event_id
's occurring in thezendesk__sla_policies
model.- This involved updating the
int_zendesk__schedule_spine
which was previously outputting overlapping schedule windows, to account for when holidays transcended a given schedule week. - This also involved updating the
int_zendesk__reply_time_business_hours
model, in which two different versions of a schedule could exist due to daylight savings time.
- This involved updating the
- Improved performance by adjusting the
int_zendesk__reply_time_business_hours
model to only perform the weeks cartesian join on tickets that require the further look into the future.- Previously the
int_zendesk__reply_time_business_hours
would perform a cartesian join on all tickets to calculate weeks into the future. This was required to accurately calculatesla_elapsed_time
for tickets with first replies far into the future. However, this was only necessary for a handful of tickets. Therefore, this has been adjusted to accurately only calculate the future weeks as far as either the first reply time or first solved time.
- Previously the
- Addition of the reference to the Fivetran prebuilt Zendesk Streamlit report in the README.
- Updates DECISIONLOG to include a note that the generated time series for ticket SLA policies is limited to a year into the future to maintain performance.
PR #136 includes the following changes:
- Converted the
sla_elapsed_time
metric within thezendesk__sla_policies
model to be reported in minutes to the second as opposed to just the nearest rounded minute. This ensures more accurate reporting. - Adjusted the
next_reply_time
SLA elapsed time metric calculation within thezendesk__sla_policies
model to also take into consideration the ticket solved event as a valid SLA event. Previously if a reply time SLA was attached to a ticket and there was no reply, but the ticket was closed then the SLA would be breached. This update ensures a closed event serves as a route for the SLA to be achieved or breached. - Updated the
int_zendesk__reply_time_combined
model to additionally account for the following business hour scenarios as they were erroneously being filtered out in previous versions of the package:- A ticket is first replied to outside SLA schedules
- A ticket has not yet received an agent reply
- Overhauled the logic used within the
int_zendesk__reply_time_combined
model to calculatesla_breach_at
within thezendesk__sla_policies
and upstream models for reply time SLAs. It was found this field was inconsistent with the actual breach/achieve time of an SLA. The overhaul should now ensure reply time SLA is accurate to either be the time of the SLA breach or achieve event.- In particular, for first and next reply time SLAs the
sla_breach_at
will be the time of the breach if the SLA was breached or the time the SLA was achieved if it was not breached.
- In particular, for first and next reply time SLAs the
- Modified the logic that matches schedule weeks within the
int_zendesk__reply_time_combined
model when calculating reply time business metrics. Previously long running SLAs would be excluded from the final model, now all reply time business SLAs regardless of sla elapsed duration will be included in the endzendesk__sla_policies
model. - Included additional logic within the
int_zendesk__ticket_schedules
model to more accurately select the active default schedule used when calculating the business metrics for the downstreamzendesk__ticket_metrics
andzendesk__sla_policies
models.- Previously the model could possibly select a deleted schedule. This update ensures only an active schedule is selected.
- Updated "Zendesk" references within the README to now refer to "Zendesk Support" in order to more accurately reflect the name of the Fivetran Zendesk Support Connector.
- Added new entries to the DECISIONLOG to highlight nuances and opinionated stances this package uses when calculating business metrics and
first_reply_time
SLAs.
PR #128 includes the following changes:
- The
int_zendesk__schedule_spine
model was updated to properly account for schedules that recognized daylight savings time (DST) at one point in time, and then stopped recognizing it at a later date.- For example, the Hong Kong timezone originally recognized DST, but then stopped in 1979. The previous versions of this package only recorded the schedule business hours until 1979. This update addresses this bug.
- Please note, this update will only effect users leveraging schedules.
- Included auto-releaser GitHub Actions workflow to automate future releases.
- Updated the maintainer PR template to resemble the most up to date format.
- Included a
quickstart.yml
file to allow for automated Quickstart data model deployments.
- We have changed our identifier logic in the initial Zendesk source package to account for
group
being both a Snowflake reserved word and a source table. Givendbt_zendesk_source
is a dependency for this package, Snowflake users will want to execute adbt run --full-refresh
before using the new version of the package. PR #42
- Updates the
int_zendesk__schedule_spine
model to convert the Holiday schedules into proper UTC values before being used in comparison with the schedule times. This ensures the holidays are properly mapped to schedules regardless of timezones. (PR #126)
- Added
solve_time_in_calendar_minutes
andsolve_time_in_business_minutes
to ourzendesk__ticket_metrics
model, which calculates calendar and business minutes for when the ticket was in the 'new', 'open', 'hold', or 'pending' status. (PR #123)
- Updated the seed files and seed file configurations for the package integration tests to align with changes in dbt_zendesk_source made in PR #42 for applying the
dbt_utils.star
macro. - Corrected the folder structure for the
.github
folder to properly categorize the Community and Maintainer PR templates. (PR #126)
This release includes fixes to issues introduced in v0.11.0-v0.11.1 surrounding the incorporation of schedule holidays.
Special thanks to @cth84 and @nschimmoller for working with us to figure out some seriously tricky bugs!
- Adjusted the gap-merging logic in
int_zendesk__schedule_spine
to look forward in time instead of backward. This allows the model to take Daylight Savings Time into account when merging gaps. Previously, schedule periods with differentstart_time_utc
s (because of DST) were getting merged together (PR #114).- Also removed the
double_gap
logic as it was rendered unnecessary by the above change.
- Also removed the
- In all of our intermediate business hour models, adjusted the join logic in the
intercepted_periods
CTE, where we associate ticket weekly periods with the appropriate business schedule period. Previously, we did so by comparing the ticket'sstatus_valid_starting_at
andstatus_valid_ending_at
fields to the schedule'svalid_from
andvalid_until
dates. This was causing fanout in certain cases, as we need to take the ticket-status'sweek_number
into account because it is part of the grain of the CTE we are joining (PR #114). - Adjusted the way we calculate the end of holidays in
int_zendesk__schedule_spine
. Previously, we calculated the end of holiday day by adding24*60*60-1
seconds (making the end the last second of the same day) to the start of the holiday. This previously worked because our downstream joins for calculating business metrics were inclusive (ie>=
instead of>
). We've updated these joins to be exclusive (ie>
or<
), so we've set the end of the holiday to truly be the end of the day instead of a second prior (PR #114). - Updated
int_zendesk__requester_wait_time_filtered_statuses
to include thehold
status, as zendesk updatedon-hold
to justhold
(PR #114). - Updates the logic in
int_zendesk__reply_time_combined
to bring through the correctsla_event_id
records to the endzendesk__sla_policies
model. (PR #108)- Originally, duplicate
sla_event_id
records were being persisted because the upstreamfiltered_reply_times
CTE did not include for all scenarios. With this update, the CTE will filter for the following scenarios:- Ticket is replied to between a schedule window
- Ticket is replied to before a schedule window and no business minutes have been spent on it
- Ticket is not replied to and therefore active. But only bring through the active SLA record that is most recent (after the last SLA schedule starts but before the next)
- Originally, duplicate
- Updated the ordering within the
int_zendesk__comments_enriched
model logic to also take into account when two comments are posted at the exact same time. Previously, the next comment would be picked arbitrarily. However, we now use thecommenter_role
as the tie breaker giving preference to theend-user
as they will likely be the first commenter when two comments are posted at the exact same time. (PR #114) - Modified the requester and agent wait time
sla_elapsed_time
metric calculations within thezendesk__sla_policies
to capture the maxrunning_total_scheduled_minutes
record as opposed to the cumulative sum. Max more accurately represents the upstream data as it is presented in a rolling sum in the previous intermediate models. (PR #114)
- The
dbt-date
dependency has been updated to reflect the recommended latest range, [">=0.9.0", "<1.0.0"]. This will help to avoid upstream dependency conflicts. (PR #113)
- @nschimmoller (#108)
- @cth84 (#107)
This PR #110 is a rollback to v0.10.2. We are seeing issues in business minutes and SLA duplicate records following the v0.11.0 release.
Tiny release ahead!
- Removes whitespace-escaping from Jinja code in
int_zendesk__field_history_scd
. In different whitepace parsing environments, this can jumble code up with SQL comments (PR #106).
Update: There have been bugs identified in this release and we have rolled back this package to v0.10.2 in the v0.11.2 release.
- Added support of the new
schedule_holiday
table in theschedule_spine
intermediate model in order to properly capture how holidays impact ticket schedules and their respective SLAs. (PR #98) - Made relevant downstream changes within the following models to capture proper business hour metrics when taking into account holiday schedules: (PR #98)
int_zendesk__agent_work_time_business_hours
int_zendesk__reply_time_business_hours
int_zendesk__reply_time_combined
int_zendesk__requester_wait_time_business_hours
zendesk__sla_policies
- Added
open_status_duration_in_business_minutes
andnew_status_duration_in_business_minutes
columns to theint_zendesk__ticket_work_time_business
andzendesk__ticket_metrics
models. These are counterparts to the already existingopen_status_duration_in_calendar_minutes
andnew_status_duration_in_calendar_minutes
columns. (PR #97)
- Added coalesce to
0
statements to the following fields in thezendesk__ticket_metrics
model. This is necessary as some tickets may have responses entirely outside of business hours which will not count towards business minute metrics. As such, a coalesce to0
is more representative to the metric as opposed to anull
record: (PR #103)first_resolution_business_minutes
full_resolution_business_minutes
first_reply_time_business_minutes
agent_wait_time_in_business_minutes
requester_wait_time_in_business_minutes
agent_work_time_in_business_minutes
on_hold_time_in_business_minutes
- Fixed the
total_agent_replies
field inzendesk__ticket_metrics
so the value is derived from public agent comments logic, and also ignores ticket creation comments from an agent, matching the Zendesk definition. (PR #102)
- Leveraged
dbt_date.week_start
in place ofdbt.date_trunc
for business hour metrics to more consistently capture the start of the week across warehouses. (PR #98) - Start of the week is now consistently set to Sunday. (PR #98)
- Incorporated the new
fivetran_utils.drop_schemas_automation
macro into the end of each Buildkite integration test job. (PR #98) - Updated the pull request templates. (PR #98)
PR #101 includes the following updates:
- Updated the
group
variable in thedbt_project.yml
to have properly closed quotes within the variable declaration. - Adjusted the
in_zendesk__calendar_spine
to set the return result ofdbt.current_timestamp_backcompat()
as a variable. This ensures that when the variable is being called within the model it can properly establish a dependency within the manifest.
- Modified the
int_zendesk__ticket_schedules
model to have the execute statement reference the sourceschedule
table as opposed to thestg_zendesk__schedule
model so the package may successfully compile before being run for the first time. (#90)
PR #81 includes the following breaking changes:
- Dispatch update for dbt-utils to dbt-core cross-db macros migration. Specifically
{{ dbt_utils.<macro> }}
have been updated to{{ dbt.<macro> }}
for the below macros:any_value
bool_or
cast_bool_to_text
concat
date_trunc
dateadd
datediff
escape_single_quotes
except
hash
intersect
last_day
length
listagg
position
replace
right
safe_cast
split_part
string_literal
type_bigint
type_float
type_int
type_numeric
type_string
type_timestamp
array_append
array_concat
array_construct
- For
current_timestamp
andcurrent_timestamp_in_utc
macros, the dispatch AND the macro names have been updated to the below, respectively:dbt.current_timestamp_backcompat
dbt.current_timestamp_in_utc_backcompat
dbt_utils.surrogate_key
has also been updated todbt_utils.generate_surrogate_key
. Since the method for creating surrogate keys differ, we suggest all users do afull-refresh
for the most accurate data. For more information, please refer to dbt-utils release notes for this update.- Dependencies on
fivetran/fivetran_utils
have been upgraded, previously[">=0.3.0", "<0.4.0"]
now[">=0.4.0", "<0.5.0"]
.
- If doing a dbt_compile prior to dbt_run, it fails at
int_zendesk__calendar_spine
because the staging model it references is not built yet. This PR changes the intermediate models to reference source tables instead of staging models. (#79)
π¨ This includes Breaking Changes! π¨
- Databricks compatibility 𧱠(#74).
- Updated README documentation updates for easier navigation and setup of the dbt package (#73).
- Added
zendesk_[source_table_name]_identifier
variables to allow for easier flexibility of the package to refer to source tables with different names (#73). - By default, this package now builds the Zendesk staging models within a schema titled (
<target_schema>
+_zendesk_source
) in your target database. This was previously<target_schema>
+_zendesk_staging
, but we have changed it to maintain consistency with our other packges. See the README for instructions on how to configure the build schema differently.
- Swapped references to the
fivetran_utils.timestamp_diff
macro withdbt_utils.datediff
macro. The dbt-utils macro previously did not support Redshift.
- Quick fix on missing logic in the case statement for determining multi-touch resolution metrics.
- @tonytusharjr (#7).
- This Zendesk Source package now allows for custom fields to be added to the
stg_zendesk__ticket
model. These custom fields will also persist downstream to thezendesk__ticket_enriched
andzendesk__ticket_metrics
models. You may now add your own customer fields to these models by leveraging thezendesk__ticket_passthrough_columns
variable. (#70)
- It was brought to our attention that the
dbt_utils.date_trunc
macro only leverages the default arguments of the date_trunc function in the various warehouses. For example,date_trunc
in Snowflake for theweek
argument produces the starting Monday, while BigQuery produces the starting Sunday. For this package, we want to leverage the start of the week as Sunday. Therefore, logic within the business metric intermediate models has been adjusted to capture the start of the week as Sunday. This was done by leveraging theweek_start
macro within thedbt-date
package. (#68)
- The
0.7.1
release of the zendesk package introduced a bug within thezendesk__sla_policy
model that caused duplicate sla records via a join condition. This join condition has been modified to leverage the more accuratesla_policy_applied.valid_starting_at
field instead of thesla_policy_applied.sla_applied_at
which changes forfirst_reply_time
slas. (#67)
- The logic used to generate the
zendesk__ticket_backlog
model was updated to more accurately map backlog changes to tickets. As the underlyingzendesk__ticket_field_history
model is incremental, we recommend a--full-refresh
after installing this latest version of the package. (#61)
- Addition of the DECISIONLOG.md. This file contains detailed explanations for the opinionated transformation logic found within this dbt package. (#59)
- Added logic required to account for the
first_reply_time
when the first commenter is an internal comment and there are no previous external comments applied to the ticket. (#59) - For those using schedules, incorporates Daylight Savings Time to use the proper timezone offsets for calculating UTC timestamps. Business minute metrics are more accurately calculated, as previously the package did not acknowledge daylight time and only used the standard time offsets (#62).
- Updated the incremental logic within
int_zendesk__field_history_scd
to include an additional partition forticket_id
. This allows for a more accurate generation of ticket backlog records. (#61) - Corrected the spelling of the partition field within the cte in
int_zendesk__field_history_scd
to bepartition
opposed topatition
. (#61)
π dbt v1.0.0 Compatibility Pre Release π An official dbt v1.0.0 compatible version of the package will be released once existing feature/bug PRs are merged.
- Adjusts the
require-dbt-version
to now be within the range [">=1.0.0", "<2.0.0"]. Additionally, the package has been updated for dbt v1.0.0 compatibility. If you are using a dbt version <1.0.0, you will need to upgrade in order to leverage the latest version of the package.- For help upgrading your package, I recommend reviewing this GitHub repo's Release Notes on what changes have been implemented since your last upgrade.
- For help upgrading your dbt project to dbt v1.0.0, I recommend reviewing dbt-labs upgrading to 1.0.0 docs for more details on what changes must be made.
- Upgrades the package dependency to refer to the latest
dbt_zendesk_source
. Additionally, the latestdbt_zendesk_source
package has a dependency on the latestdbt_fivetran_utils
. Further, the latestdbt_fivetran_utils
package also has a dependency ondbt_utils
[">=0.8.0", "<0.9.0"].- Please note, if you are installing a version of
dbt_utils
in yourpackages.yml
that is not in the range above then you will encounter a package dependency error.
- Please note, if you are installing a version of
-
Updated logic within
int_zendesk__sla_policy_applied
to more accurately reflect thesla_applied_at
time forfirst_reply_time
sla's. Per Zendesk's documentation thefirst_reply_time
sla is set at the creation of the ticket, even if the sla is applied after creation. (#52) -
It was found that
first_reply_time
Zendesk SLA policies can be modified after they are set if the priority of the ticket changes. As such, this resulted in the package providing multiplefirst_reply_time
sla records in the finalzendesk__sla_policies
output model. As such, now only the latestfirst_reply_time
sla is provided in the final output model. (#52)
- Redshift recently included
pivot
as a reserved word within the warehouse. As such, thepivot
CTE within theint_zendesk__field_history_pivot
model has been changed topivots
to avoid the Redshift error. (#57)
- @jackiexsun (#52)
- Fix incremental logic bug introduced in v0.5.0 which caused the
zendesk__ticket_field_history
model to not be properly incrementally updated. (#44)- The above fix resulted in the removal of the
valid_from
andvalid_to
fields in the final model.
- The above fix resulted in the removal of the
- Incremental bug fix noted in the
Breaking Changes
section of the changelog. - Updated the logic used to calculate
first_reply_time_calendar_minutes
andfirst_reply_time_business_minutes
to include first comments made by agents and find the time difference from the first public agent and the ticket created date. This was updated to better align with Zendesk's First Reply Time metric definition. (#50) - Fixed the comment metric reference for the
total_agent_replies
withinzendesk__ticket_metrics
to accurately map to thecount_agent_comments
metric (showing all public and non-public comments made by agents) opposed to thecount_internal_comments
(only non-public comments) metric. (#50)
- Add the number of ticket handoffs metric as
count_ticket_handoffs
to thezendesk__ticket_metrics
model which is a distinct count of all internal users who have touched/commented on the ticket. (#42) - Ticket field history calendar limit variables (#47):
- Added
ticket_field_history_timeframe_years
variable to limit the ticket field history model to X number of years (default is 50). - Limited by default the last ticket calendar date as it's close date. This highly reduces the query cost of the
zendesk__ticket_field_history
query and takes advantage of the Zendesk functionality of not being able to change a ticket after the close date. - Added
ticket_field_history_extension_months
variable to extend field history past Y months from ticket close (for reporting purposes). - Refer to the README for more details.
- Added
- Better Postgres incremental strategy within the
zendesk__ticket_field_history
model to reflect more recent incremental strategies. Similar to the strategy taken in jira__daily_issue_field_history. (#44)
- csaroff (#47)
- jackiexsun (#42)
- emiliedecherney (#50)
- gareginordyan (#44)