The Advanced QlikView Developer Bootcamp

Examine synthetic keys and tables, then use composite keys to avoid them; understand circular references and join behavior to model national teams, clubs, and country cities.

Define the relationship between tables to model data in QlikView, enabling bidirectional filtering and cross-table questions, with star or snowflake patterns, concatenated keys, and testing anchored to business requirements.

Explore types of data models, from traditional modeling and single-table schemas to snowflake schemas, then examine Stotsky, clickthrough specific modelling with concatenated factor, mixed granularity schemas, and league tables.

Demonstrates building a snowflake schema in QlikView by adding and linking dimension tables such as product description, supplier, and employee address to the fact table.

Demonstrate how to build and concatenate fact tables from store and web sales, align fields across a star and snowflake schema, and use flags to track load type.

Explore how to simplify a snowflake schema data model that uses a fact table with related tables such as customer, employee, employee address, teams, master calendar, and products.

Implement a second challenge by renaming three fields with mapping load, converting employee name to team MPLX name from input to output using a liberty file to explore mapping nodes.

Explore how QlikView script execution flows left to right and top to bottom, grouping load and select statements into blocks, with preceding load evaluating inputs and tabs as logical placeholders.

Learn how resident load works in QlikView, including why it requires a preloaded table, how multiple instances occur, and when to drop or avoid auto concatenation, or use order clause.

Explain the difference between where and having clauses; where filters rows before grouping, having filters groups after, using grouping by sales order to compute total price and apply thresholds.

Learn how to emulate a having clause in QlikView by using a preceding load with group by and aggregation, filtering on an aggregated line sales amount.

Convert a synthetic-key load into two tables using wildcard loads and preceding or resident load, and create the percentage ki required date and a Phelim field.

Learn to use linkable tables to replace synthetic ones by moving common fields into a composite key, labeled with a percent prefix, and connect two tables via a link cable.

Learn how incremental reload helps manage large data sets, such as tables with 10 million rows. Explore three types: insure, incertain update, and insert update and delete.

Master incremental reload scripting in QlikView to load only new records, following a nine-step blueprint that uses a stored primary key for subsequent reloads and full reload fallbacks.

Extend the incremental reload to handle both insert and update operations by formatting the date field as a date and replacing outdated records with updated ones using not exists logic.

Master incremental load in QlikView by creating scripts for inserts and updates on the orders table using a max key and order date, then validating with full and incremental reloads.

Explore associative joins versus explicit ANSI style and natural joins in QlikView, highlighting default outer joins, ANSI 92 inner joins, and practical examples with colors and fruit data.

Master left join by stacking the left-hand side table with matching records, producing a result from the left table and ignoring non-matching right-hand side rows.

Explore right join fundamentals by combining fruit and colors tables to yield three common rows, and learn that its effect mirrors a left join when tables are swapped.

Compare less and more efficient master calendar scripts, extract min and max dates, generate a date table, and build a master calendar with preceding load for performance.

Master calendar challenge: replace interpretation function with a formatting function, use NUM and percent key order date field, and ensure the calendar reload shows 805 rows and 45 fields.

Extract min and max dates, generate calendar, and create master calendar; use the filled value function to scan unique field values (symbol table) with preceding, interpretation, and permitting functions.

Apply consistent QlikView naming conventions by prefixing variables with v and expressions with xp, name colors clearly, and designate navigation and temp variables to stay organized.