The Advanced QlikSense Masterclass

Explore how the Qlik associative engine operates under the hood, detailing the inference and calculation engines, symbol and data tables, and how selections render possible, excluded, and selected states.

Discover how symbol tables store distinct values with binary indexes and how data tables store pointers, revealing how high cardinality drives symbol space and date and timestamp fields.

Learn how to improve Qlik Sense performance by managing field cardinality, reducing symbol table size, and applying best practices for incremental loading, link tables, and optimized QVD loads.

Master design best practices for QlikSense by replacing nested if statements with pick and match and set analysis, avoiding Edgar, and selecting visuals by data type (nominal, ordinal, interval, ratio).

Perform a full initial load to a qvd, then daily incremental loads append new or updated records using a primary key and not exists to avoid duplicates, and handle deletions.

Master the architecture of incremental loads in QlikSense, including QVD loading. Schedule Qmk tasks, merge incremental source rows with the QVD, and apply optimized load rules.

Implement incremental inserts in QlikSense by checking for an existing QVD, loading full data when absent, storing and using the max primary key to fetch new records, and concatenating results.

Learn to build an incremental load insert script, define the full load steps, set up database and qvd connections, and track the max order id (39999) for the invoice table.

Explore incremental loads by checking qvd existence with file length, performing a full load when needed, then derive and store the max key for inserts in future runs.

Implement incremental load in qliksense by checking file existence and using the prior max key to fetch new records, then concatenate them to the qvd and update the max key.

Learn to implement incremental load for inserts and updates in QlikSense by checking file existence, using max date updated, and concatenating with existing qvd data.

Learn to create insert and update incremental load scripts using a date field, swap max key with update field, and validate changes with a full load and qvd updates.

Implement incremental load for inserts and updates on the purchase table, using purchase ID as the key and purchase date for updates, starting with a full load.

Explore link table fundamentals in Qlik Sense, replacing synthetic keys with a controlled link table using composite keys, field prefixes, and handling different table granularity to improve model performance.

Create a link table by joining orders and purchases with a composite key of order date and product ID, using distinct values and not exists to avoid duplicates.

Explore replacing resident loads with a field value based link table, without resident load, using subfield and field value count to derive date and product id for improved efficiency.

Add inventory transaction to the link table with a composite key linking to purchases and orders, and apply the improved link table script using the fill value function.

Explore the aggr function in qliksense, an advanced aggregation that nests inner and outer aggregations to form a virtual in-memory table, with set analysis and max-per-customer examples.

Develop a QlikSense KPI that shows the highest sales per customer and a second KPI for average sales, using aggr to build a virtual table with max outer aggregation.

Explore the concat function in script and chart, joining strings or numbers with a delimiter, and use distinct, set analysis, and dollar sign expansion for top three customers per product.

Master concat() with a state qualifier to rank top three customers by sales in a text and image object, with a product filter and descending order.

Explore the first sorted value function in Qlik Sense, usable in script and chart, returning a dimensional value with a short weighted rank and nulls on ties, ascending by default.

Learn to display the highest selling product using the first-sorted value function with an associated dimension name and inner aggregation, including a minus sign for top-item view.

Replace if statements with the first sorted value function to display the top three customers using the third parameter, in descending order with a minus sign.

Master set analysis fundamentals in QlikSense by understanding set identifiers, modifiers, and operators, and apply examples like sum of sales for John Doe while leveraging dollar and one state.

Learn how dollar sign expansion in set analysis expands variable content within expressions to nest functions and create dynamic year-based comparisons.

Master building a slope graph in Qlik Sense using set analysis and dollar-sign expansion to show year-over-year revenue trends by country from 2000 to 2005.

build a slope graph with set analysis dollar sign expansion to compare prior and current year by country, and apply year filters and a gradient expression.

Master set analysis with aggr and concat to display top three customers and build slope graphs, improving performance by replacing if statements with expression search.

In the QlikSense masterclass, lecture explains set analysis operators minus equal, equal minus, plus equal, and intersection (asterisk equal), showing how to add or exclude values in filters with accessories.

Master field comparison in Qlik Sense by using set analysis and the equality operator to match ship date to the required date and list qualifying order IDs.

Learn to filter QlikSense data by composing a set modifier with an expression to show order IDs with order total greater than 25,000, intersecting ship date and required date conditions.

Explore alternate states in Qlik Sense to enable comparative analysis by building state one and state two, assigning charts and filters to each state, and leveraging set analysis.

Create a two-state Qlik Sense pivot table showing country sales for state one and state two, using set analysis with state one and state two, and propagate selections across charts.

Describe how authentication identifies users and authorization grants access to QlikSense resources through security rules, section access, and attribute-based access control, with roles from root admin to content admin.

Master the security user access workflow with custom properties that match user attributes to stream and app properties, and use ad groups and roles to control access.

Set up a testing environment by installing the AI portal to impersonate multiple roles for testing security rules in enterprise Qlik Sense, using the GS Framework community resources.

Configure a stream level security rule in the qmc that grants read access via a custom property matched to an Active Directory group, demonstrated with the finance stream.

Examine app level access rules in QlikSense, showing that stream access alone may not grant an application. Configure app-specific ad groups and app id group to control access.

Learn how to enforce sheet-level access by extending security rules with a custom property 'hide sheets', assigning values like airfare and dashboard to users, and validating invisibility of restricted sheets.

Learn how on demand app generation links a selection app to a dynamically created detail app using a dynamic where clause and templates.

Explore on-demand application generation (odag) in Qlik Sense by coupling a template and detail app with a selection app to create dynamic where clauses and load reduced data.

Explore subset ratio and associative insight to identify noncontributing customers, compare distinct values across fact and dimension tables, and reveal those with no orders.

Learn how to perform optimized loads in Qlik Sense by applying the no transformation rule, using single-field exists with aliasing limits, and spotting non-optimized behavior with a QVD example.

Learn to load a SharePoint list into a Qlik Sense app by extracting list GUID, crafting an XML URL, and loading title and instructor fields with a web file connection.

Discover how to concatenate tables in Qlik Sense and load files in one statement, then extract a date field from the file name with file name, subfield, and date functions.

Explore when to use the previous and big functions in QlikSense, applying previous to input records and big to output records to build a cumulative total by order id.

Discover how nested parameterized variables in QlikSense enable dynamic KPI calculations, using buttons to set a variable value and update labels and colors.

Explore the new set analysis syntax that externalizes set expressions, enabling flexible modifiers and reusing measures with inheritance rules to compute year-to-date, prior-year, and percent contributions.