Tag: Data Analysis

Introduction

Alteryx Overview

• What is Alteryx?
• Alteryx features

Preparing the Development Environment

• Installing and configuring Alteryx

Input and Read

• Connecting data sources to Alteryx
• Importing data
• Using the input tool

Data Wrangling

• Using data preparation tools and parsing tools
• Working with joins and unions

Transformations

• Using various pivot methods
• Aggregating data

Layouts

• Reporting layouts
• Exporting reports

Summary and Conclusion

Introduction

Stata and Big Data

• What is Stata?
• Stata syntax and commands

Preparing the Development Environment

• Installing and configuring Stata

Datasets and Data

• Opening and cleaning datasets
• Compressing datasets
• Importing and exporting datasets
• Viewing, describing, and summarizing raw data
• Using tabulations and tables
• Working with distributional analysis
• Implementing variables for data manipulation
• Saving data
• Working with commands

Graphing in Stata

• Using plots, charts, and graphs
• Working with distributional analysis in graphing
• Styling and combining graphs

Statistics and Regression

• Using bivariate correlation and regression
• Working with OLS regression, logits, and probits
• Using interactive effects in regression models

Summary and Conclusion

• Introduction
• Overview of the Power BI Dashboard
• Examples and Comparisons between Well-Designed Dashboards and Poorly-Organized Dashboards
• Understanding Basic and Key Features of Power BI
• Essential Rules to Design A Beautiful Dashboard
• Choosing the Right Visuals for Your Data

Introduction

• Tableau Prep Builder as an ETL (Extract, Transform and Load) tool

Setting up Tableau Prep Builder

• Activating and Register Tableau Prep Builder

Overview of Tableau Prep Builder Features and Architecture

• Tableau Prep Builder and its relation to Tableau Desktop, Tableau Server and Tableau Prep Conductor

Navigating the Tableau Prep Builder Workspace 

• Panes and data grids

Connecting to Data Source

• Reading an Excel
• Reading from a database

Shaping Data

• Creating a Join
• Creating a Union

Pivoting Data

• Changing columns to rows

Cleaning Data

• What is dirty data?
• Changing the data type
• Filtering data
• Aggregating data
• Updating multiple values at once

Running a Flow

• Building a flow
• Refreshing a flow
• Running a flow from the command line

Outputing Data to Tableau Desktop

• Analyzing data

Publishing Data

• Packaging a Prep Builder data flow into an extract
• Publishing a flow with Prep Conductor 

Best Practices 

Troubleshooting

1. Connecting to datasources
   • Loading data into Tableau
   • Combining data tables – join
   • Combining data from different sources– merge
   • Extracting data to Tableau format
   • SQL queries
   • Managing data
   • Renaming data
   • Creating parameters (workbook variables)
   • Metadata
2. Effective visualisations
   • What makes a good visualisation
   • Choosing the right chart
   • The role of colour in data storytelling
   • How to avoid misleading your audience
   • Best practices
3. Calculations
   • Arithmetic calculations
   • Working with strings
   • Operations on dates and time
   • Array calculations
   • Conditional and logical expressions
   • Conditional filtering
4. Processing Array Data
   • Difference between Excel and Tableau
   • Processing arrays in Tableau
   • Writing custom SQL statements
5. Statistics
   • Adding reference and trend lines
   • Calculating descriptive measures
   • Subtotals
   • Aggregation and disaggregation
   • Forecasting
6. Building effective dashboards
   • Combining visualizations
   • Formatting dashboards
   • Adding filters and actions to create interactive dashboards
   • Making an aesthetically pleasing dashboard
   • Best practices for creating dashboards
7. Sharing dashboards
   • Publish to Tableau Reader
   • Publish to Tableau Server
   • Publish to PDF

• Introduction
• Connecting to data
• Simplifying and sorting your data
• Organizing your data
• Slicing your data by date
• Using multiple measures in a view
• Showing the relationship between numerical values
• Mapping data geographically
• Viewing specific values
• Customizing your data
• Analyzing data with quick table calculations
• Showing breakdowns of the whole
• Highlighting data with reference lines
• Making your views available

Introduction and Getting Started

1. Filtering, Sorting & Grouping
   1. Advanced options for filtering and hiding
   2. Understanding many options for ordering and grouping your data
   3. Sort, Groups, Bins, Sets
   4. Interrelation between all options
2. Working with Data in Tableau
   1. Dimension versus Measures
   2. Data types, Discrete versus Continous
   3. Joining Database sources,
   4. Inner, Left, Right join
   5. Blending different datasources in a single worksheet
   6. Working with extracts instead of live connections
   7. Data quality problems
   8. Metadata and sharing a connection
3. Calculations on Data and Statistics
   1. Row-level calculations
   2. Aggregate calculations
   3. Arithmetic, string, date calculations
   4. Custom aggregations and calculated fields
   5. Control-flow calculations
   6. What is behind the scene
   7. Advanced Statistics
   8. Working with dates and times
4. Table Calculations
   1. Quick table calculations
   2. Scope and direction
   3. Addressing and partitioning
   4. Advanced table calculations
5. Advanced Geo techniques
   1. Building basic maps
   2. Geographic fields, map options
   3. Customizing a geographic view
   4. Web Map Service
   5. Visualizing non geographical data with background images
   6. Mapping tips
   7. Distance Calculations
6. Parameters in tableau
   1. Creating parameters
   2. Parameters in calculated fields
   3. Parameter control options
   4. Enhancing analysis and visualizations with parameters
7. Building Advanced Chart Visualizations
   1. Bar chart variations –bullet, bar-in-bar, highlights chart
   2. Date and time visualizations, gantt charts
   3. Stacked bars, treemaps, area charts, pie charts
   4. Heat map
   5. KPI chart
   6. Pareto chart
   7. Bullet chart
8. Advanced formattting
   1. Labels
   2. Legends
   3. Highlighting
   4. Annotations
9. Telling a data story with Dashboards
   1. Dashboard framework
   2. Filter actions
   3. Highlight actions
   4. URL actions
   5. Cascading filters
10. Trends and Forecasting
    1. Understanding and Customizing trend lines
    2. Distributions
    3. Forecasting
11. Integrating Tableau and R for advanced data analytics
    1. Possibility to include different data analytics methods in R on participants request

• Connecting to various databases
• Data connection types
• Working with Single Data Sources Multiple data sources & data blending
• Tableau geocoding
• Advanced mapping + using Background Images
• Overview of additional visualizations
• Dashboards: quick filters, actions, and parameters
• Advanced calculations
• Parameters, calculations, sorting, filtering etc.
• Best practices when using Tableau R programming

• Advanced data analysis
• Comparative analysis using alternative states
• Custom visualizations
• Advanced functions and calculations
• Pareto (ABC), basket and Monte Carlo analysis.
• Segmentation and classification of sales data
• Advanced transformations in the script
• Incremental loads and QVD layers
• Optimization of the data loading process,
• Debugging and troubleshooting
• Advanced technical concepts and solutions in real scenarios

Introduction

Qlik Sense at a Glance

• What is Qlik Sense?
• Qlik Sense multi-cloud architecture
• The associative engine and AI

Preparing the Development Environment

• Installing and configuring Qlik Sense Desktop
• Navigating the interface

Qlik Sense Quick Start

• Creating a chart
• Building a dashboard
• Customizing Qlik
• Working with data sources
• Managing Qlik Sense sheets
• Creating pivottables and reports
• Sorting and filtering data

Qlik Sense Scripting

• Using data load editor
• Connecting, extracting, and loading data
• Working with tables
• Debugging scripts

Synthetic Keys and Flat Files

• Working with synthetic keys
• loading tables
• Importing data
• Adding flat files

Data Model Optimization

• Creating QVD files
• Optimizing QVD load