I.                   Objectives

This course focuses on the basic analysis part of the QlikView tool.

It provides the basis for understanding the philosophy of the associative model proposed by QlikView and the objects that allow access to data and display it in different formats.

At the end of the course, the student will have sufficient knowledge to:

Access different types of data (both file format and structure).Create tables and graphs for analyzing information (bars, lines, pie charts, etc.).Understand the associative model of QlikView elements.

Customize the display of analysis objects.

II. Requirements

No specific requirements are needed beyond having used other simple analysis tools (Microsoft Excel, for example).

Knowledge of SQL and the use of plain text files can facilitate understanding of the subject.

III.Duration

15 hours.

IV. Methodology

The course is developed through theoretical presentation accompanied by practical demonstrations and explanations of the results obtained.

The student carries out the modeling of different data sources, to test the characteristics of the product, in addition to designing analysis sheets and control panels by inserting selection elements and graphics.

Resolution of doubts about the concepts presented.

V.               Content

Introduction to QlikView and data analysis.Basic BI concepts.

Data models.

Main features of QlikView. Data modeling. Associative model. Importing data from flat files. Importing data from spreadsheets. Importing data from databases. ODBC. OLE DB. Data loading scripts. LOAD command.Using inline tables.Using star models.Using snowflakes.Using normalized models.Table viewer window.Expression editor window.

Creating content.Document setup.Sheet properties.General characteristics of an object.Using cyclic expressions.Object configuration:Titles.List boxes.Table boxes.Bookmark.Multiple selection box.Current selection box.Inserting images.Creating a “Top 10” object.Creating analysis sheets and control panels.Linking and copying objects.Indicator charts.Charts:Lines.Pie.Bars.Radar.KPIs.Using expressions in charts.Hierarchical charts.Using bookmarks.

Advanced buttons and objects.

I.                   Objectives

This course is focused on the analysis part of the Tableau tool.

It provides the necessary knowledge to use the data access and analysis tools.

At the end of the course, the student will have sufficient knowledge to:

Access data that resides in different sources.

Create analysis using Tableau.

II. Requirements

No specific requirements are needed beyond having used other simple analysis tools (Microsoft Excel, for example).

Knowledge of SQL and the use of plain text files can facilitate understanding of the subject.

III. Duration

20 hours.

IV. Methodology

The course is developed through theoretical presentation accompanied by practical demonstrations and explanations of the results obtained.

The student carries out practical exercises in which he/she models different data sources to test the characteristics of the product, in addition to using the data analysis functions.

Resolution of doubts about the concepts presented.

V.               Content

Introduction to Business Intelligence, Data Warehouse and Tableau. Basic concepts of B.I. Data models. Main characteristics of Tableau.

Data access and preparation.

Use of plain text files.

Pivoting dataset.Fixed length plain text files.Plain text files with field separator character.Using Microsoft Excel as a data source.Joining data using Microsoft Excel.Using Google Sheets.Basic use of geographic information.Complementing data using extractions.LEFT / RIGHT / FULL data joins.CROSS data joins.BLENDING data joins.Data analytics:Data tables.Context filters.Sorting and hierarchical sorting.Charts:Basic.Bullet Chart.Bar in bar.Heat map.Other charts.Calculated elements:Row level calculations.Grouped calculations.Null values ​​in grouped calculations.Dimensional level calculations.Parameters.Trend lines.Clustering.Forecast.Dashboard.Creating the dashboard. control.Using visualizations.Inserting images.

Story.Creating a story.Adding elements to each sheet.

Adding comments to each sheet.

General concepts 1a. Power BI objects.
1b. Measures and dimensions.

Data analytics objects 2a. Creating visuals.
2a1. Tables and matrices.
2a2. Charts.
2a3. Text boxes. 2b. Filters and slicers.
2b1. Levels of filter usage.
2b2. Selectors for slicers. 2c. Hierarchies.
2c1. Creating dimension hierarchies.
2c2. Using hierarchies in visuals. 2d. Interaction between elements. 2e. Creating the dashboard.

Advanced elements 3a. Calculated tables.
3b. Measures using calculated tables.