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The SecuTix Data Analytix (DAN) is the business intelligence module (BI) of SecuTix 360°. It based on the Qlik Sense platform and comes with a comprehensive set of standard reports powered by our BI partner Kultur Planner.

Key terminology

  • Dimension: A dimension is a field in the database, e.g., seat category or sales date. You can select any number of dimensions as filters.
  • Measure: A measure is a computed value, e.g., number of tickets or revenue. Measures will take into account the selected filters.
  • Visualization: Dimensions and measures can be combined to build visualizations, i.e., graphs, tables, etc.
  • Sheet: A sheet (report) allows building a layout combining several visualization. DAN comes with many pre-built standard sheets.
  • Bookmark: A bookmark allows saving the current filters and sheet.
  • Snapshot: A snapshot is a picture of visualization at a given point in time.
  • Story: A story is a set of slides, similar to powerpoint, in which you can insert static elements, like snapshots, shapes, texts, or dynamic elements like a sheet. Sheets within story are stored along with the current filters (think bookmark) and will be refreshed each time the story is replayed.

Qlik Sense

Qlik sense is the framework on top of which the DAN reports are built. You will find an extensive help on the Qlik web page describing the two main views:

and how to use all the different elements of the tool:



DAN reports (sheets)

A description of the full list of DAN sheets is available in the DAN guides and tutorials section of the release notes, along with screenshot. The page is a precious tool to help you find the right report for your needs. It contains the exhaustive list of all dimensions and measures used in each one of them, along with an illustrative screenshot. You can either search for a word using the browser's text search or scroll through the screenshots to find the one that is right for you.

Note that the list references the reports of all verticals, some of which may not be available in your context.


Latest revenue distribution [G] | Package Sales [G] | Membership Sales [G] | Service Sales [G] | Voucher Sales [G] | Donation Sales [G] | Goods Sales [G] | Open Product Sales [G] | Revenue utilization per product [G] | Contact filters [G] | Contact list [G] | Catchment area [G] | Contact purchase details [G] | Geoanalysis [G] | Season ticket transition flow [G] | Upcoming performances KPI [LE] | Latest sales KPI [LE] | Latest performances [LE] | Latest events [LE] | Event KPI [LE] | Event weekday/month distribution [LE] | Event utilization [LE] | Latest sales per audience category [LE] | Latest sales per performance [LE] | Calendar view [LE] | Year/season comparison [LE] | Utilization per month [LE] | Seat cat./contingent utilization matrix [LE] | Sales potential per performance/seat cat. [LE] | Configuration seat map [LE] | Sales timeline seat map [LE] | Venue utilization [LE] | Seasonal utilization [LE] | Event life cycle [LE] | After event premiere [LE] | Sales period [LE] | Sales categorization relative to performance date [LE] | Sales comparison relative to performance date [LE] | Sales cross-distribution [LE] | Season ticket sales [LE] | Season ticket sales per event/performance [LE] | Season ticket sales date distribution [LE] | Ticket Resales [LE] | Consumer behaviour 1 [LE] | Consumer behaviour 2 [LE] | Contact cross-distribution [LE] | Latest attendance/sales KPI [MU] | Latest sales per date [MU] | Ticket sales year comparison [MU] | Revenue year comparison [MU] | Attendance history [MU] | Attendance time/weekday/month distribution [MU] | Group attendance cross-distribution [MU] | Individuals attendance cross-distribution [MU] | Attendance year comparison [MU] | Attendance distribution per price type [MU] | Guided visits distribution [MU] | Visitor flow [MU] | Latest group attendance [MU] | Upcoming group attendance [MU] | Latest individual attendance [MU] | Upcoming individuals attendance [MU] | Attendance and revenue per time of day [MU] | Attendance/sales cross-distribution [MU] | Visit revenue/visitor scatter plot [MU] | Timeslot schedule by date/month/weekday [MU] | Consumer behaviour [MU] | Contact cross-distribution [MU] | Upcoming matches KPI [SP] | Latest sales KPI [SP] | Latest matches [SP] | Sales categorization relative to match date [SP] | Latest competitions [SP] | Competition KPI [SP] | Competition weekday/month distribution [SP] | Latest sales per audience category [SP] | Latest sales per match [SP] | Year/season comparison [SP] | Utilization per month [SP] | Sales potential per match/seat cat. [SP] | Configuration seat map [SP] | Sales timeline seat map [SP] | Venue utilization [SP] | Seasonal utilization [SP] | Competition life cycle [SP] | Sales period [SP] | Sales cross-distribution [SP] | Season ticket KPI [SP] | Season tickets per season [SP] | Season ticket sales period [SP] | Season Ticket Usage [SP] | Ticket Resales [SP] | Contact cross-distribution [SP] | Loyalty transition flow [SP] | Access control seat map [SP] | Access control timeline seat map [SP] | Access control time distribution [SP] | Customer knowledge seat map [SP] | Competition Utilization [SP] | Seat cat./contingent utilization matrix [SP] | Calendar view [SP] | Consumer behaviour 1 [SP] | Consumer behaviour 2 [SP]

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