Qlik Sense Masterclass for Data Science and BI

Recap the basics and launch an end-to-end business challenge using density chart maps, scatter plots, and heat maps to derive insights from real-world data.

Explore Chicago crime hotspots by crime type on a geo map and create a production-ready dashboard to analyze seasonal patterns, daylight hours, and feels-like temperature across 2018 data.

Connect to multiple data files in Qlik Sense, create a new app, load daylight hours, temperatures, and crimes CSV data with the data manager, and set date-based associations for analysis.

Use a humble bar chart to visualize crime types by primary type, counting distinct ids for insight. Learn to present percentages, adjust horizontal layout, and show labels for clarity.

Explore correlation in QlikSense by analyzing daily crime counts against seasonality, temperature, and daylight using a scatter plot, bubble chart, and color-coded insights.

Use the heatmap extension in Qlik Sense to display crimes by weekday and week of year, using date and weekday functions and master items.

Derive insights from crime data visualizations, identifying Chicago downtown hotspots, the top three crimes (theft, battery, and criminal damage), and patterns by temperature and daylight with a self-service dashboard.

Revisit the density map geo analysis, data formatting (longitude before latitude), and the humble bar chart for dashboard insights. Explore scatter plots and heat maps, then preview scripting topics.

Master the fundamentals of scripting in this section with a step-by-step approach. Learn to load and filter data, manage variables, and drop columns using the data manager.

Explore data sources and three sales extracts across 2016–2018. Learn to preserve raw data and use scripting to load and audit data in Qlik Sense.

Load data in Qlik Sense using the script editor by creating a new app, establishing a data connection, loading Excel files, and renaming fields such as invoice date.

Learn to add and rename fields in Qlik Sense by importing the sales data, adding comments, and creating derived fields like order date, order year, order month, and order day.

Learn to define and use variables in Qlik Sense scripts for reusable values, using set, the V prefix, and dollar-bracket syntax, with a dedicated variables section and comments.

Automate data integration by stacking files with identical field names and counts using automatic concatenation in Qlik Sense, then load and verify a single consolidated table.

Learn how to perform forced concatenation in QlikSense by stacking multiple data files with missing fields, avoid synthetic keys, and use the concatenate keyword in the data load editor.

Explore how to prevent concatenation in Qlik Sense scripts by using no concatenate, apply where clauses, manage concatenation across loads, and drop fields to maintain clean data models.

Recap the Qlik Sense scripting section: load data with scripts, differentiate loading from selecting, manage fields and variables, validate imports, and control auto, force, or prevent concatenation for joining data.

Develop scripting techniques in Qlik Sense by exploring load options, debugging strategies, and mapping tables, while understanding synthetic keys and applying a reusable model to residential load data.

Harness resident load as a source qualifier in Qlik Sense to create a high quantity customer subset from an existing sales table, using a where clause and v high quantity.

Explore synthetic keys in Qlik Sense using the customer and region data, then learn to remove them by joining on region code and verify in the data model viewer.

Master the QlikSense debugging workflow in the data load editor, using the debug panel to view output, monitor variables, and run or step through code with breakpoints.

Master mapping tables in Qlik Sense to clean data by mapping incorrect values to correct ones. Use inline loads, mapping loads, and apply map to standardize classifications in customer data.

Residential load usage to reuse loaded data and create views, examine synthetic keys and their impact on performance, and cover inline loads and debugging tools with mapping tables.

Explore advanced visualization techniques in Qlik Sense, deepen set analysis, work with a new file type, and extend capabilities with extension add-ins and a chart not natively available.

Analyze New York business license applications using Qlik Sense, visualizing types and categories with a sunburst quadrant chart and performing year-based baseline analysis via set analysis.

discover qvd files, the click view data format, and learn to create, store, and load data in Qlik Sense for fast, consolidated data loads.

Explore extensions in Qlik Sense to add visuals like the sunburst quadrant chart, using web technologies, with drag-and-drop configuration and noting cloud limitations.

Explore building a sunburst quadrant chart in Qlik Sense, using license type, license category, and year start date to reveal hierarchical data and interactive insights.

Revisit set analysis basics and baseline analysis in Qlik Sense, recap the basic course, and learn to build set expressions with modifiers, identifiers, and year filters.

Learn to create a kpi with set analysis modifiers in Qlik Sense, using a baseline year (2017) and a dollar sign to respect current selections for dynamic year comparisons.

Learn to create a front-end variable in qlik sense, assign a default baseline year, and reference it in a set analysis expression using the dollar-bracket syntax.

Learn to create a baseline in Qlik Sense by using a slider variable input, define min and max years from the start date, and add a reference line for comparison.

Learn to manage files and their properties, extend Qlik Sense with sunburst quadrant charts via extensions, and set a baseline year using a variable input to display a reference line.