Lifecycle of Tableau Developer & connected architecture

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• What is Tableau Developer & Why Tableau Developer?
• Roles & Responsibilities of Tableau Developer
• What companies expect from Tableau Developer
• Roadmap of Tableau Developer Career Transition
• Why Tableau? Why Power BI? Why MySql?
• What is ETL? What is Datawarehouse? Datamart? Data Analytics Pipelines
• Different products in Tableau
• What to focus more for tableau developer role & for fast career transition

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Phase-1: Mastering Tabealu

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1. Creating visual analytics with tableau desktop

• Overview

• The shortcomings of traditional information analysis

• The business case for visual analysis

• The tableau software ecosystem

• Introducing the tableau desktop workspace

• Notes

2. Connecting to your data

• Overview

• How to connect to your data

• What are generated values?

• Knowing when to use a direct connection or a data extract

• Joining database tables with tableau

• Blending different data sources in a single worksheet

• How to deal with data quality problems

• Note

3. Building your first visualization

• Overview

• Fast and easy analysis via show me

• How show me works

· Able to represent your data using the following visualization types:

o Cross Tab o Geographic Map o Page Trails o Heat Map o Density Chart o Scatter Plots o Pie Chart and Bar Charts o Small Multiples o Dual Axis and Combo Charts with different mark types o Options for drill down and drill across

• Trend lines, Reference lines and statistical techniques to describe data

• Sorting data in tableau

• Enhancing views with filters, sort, sets, groups, bins and hierarchies

· Understand how and when to Use Measure Name and Measure Value

· Understand how to deal with data changes in your data source such as field addition, deletion or name change

Problem Statement: Connect to any datasource you are having data in it and build a report on sales and profit based on first day charts.

4. Creating calculations to enhance your data

• Overview

Create calculations including string manipulation, arithmetic calculations, custom

Aggregations and ratios, date math, logic statements and quick table calculations

• What is aggregation?

• What are calculated values and table calculations?

• Using the calculation dialog box to create calculated values

• Building formulas using table calculations

• Using table calculation functions

• Adding flexibility to calculations with parameters

Types of parameter with example

Useful window functions

Data blending

• Using the function reference appendix

Notes

5. Using maps to improve insight

• Overview

• Creating a standard map view

• Plotting your own locations on a map

• Replacing tableau's standard maps

• Using custom background images to plot spatial data

• Shaping data to enable point to point mapping

• Animating maps using the pages shelf or slider filters

Notes

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MySQL Tool

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1. Database Basics
2. Designing your Database
3. Data Types
4. Creating Databases and Tables
5. Querying Table Data
6. Modifying Table Data
7. Functions
8. Joining Tables

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Phase-2: Advanced Charts & Real-Time Projects

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How profits and expenses are varying across different geographical portions, Need to make a decision on how to increase the profits and decrease the expenses.

6. Advanced functions & Chart types

Overview

Using parameter to change dimensions and measures

LOD expressions

Waterfall chart

Pareto chart

Funnel chart

Control chart

Exponential Smoothing Models

7. Developing an ad hoc analysis environment

• Overview

• Generating new data with forecasts

• Providing self-service ad hoc analysis with parameters

• Editing views in tableau server

• Note

8. Tips, tricks, and timesavers

• Overview

• Saving time and improving formatting

• Improving appearance to convey meaning more precisely

• Customizing shapes, colors, fonts, and images

• Advanced chart types

9. Bringing it all together with dashboards

• Overview

• How dashboard facilitates analysis and understanding

• How tableau improves the dashboard building process

• The wrong way to build a dashboard

• The right way to build a dashboard

• Best practices for dashboard building

• Building your first advanced dashboard

• Sharing your dashboard with tableau reader

• Sharing dashboards with tableau online or tableau server

10. A Understanding and Using of all Tableau Functions

11. View reports on mobile devices

Build overview of a company across 3 years of data and project it on a dashboard and explain company overview using story telling and publish it on to Tableau Server.

12. Tableau Server

• The Reasons to Deploy Tableau Server
• Licensing Options for Tableau Server and Tableau Online
• Tableau Server’s Architecture & Environmental Factors That Can Affect Performance
• Configuring Tableau Server for the First Time
• Data Alerts via email

13. Using Tableau Server to Facilitate Fact-Based Team Collaboration

• Publishing Dashboards in Tableau Server
• Organizing Reports for Consumption
• Options for Securing Reports
• Customized Views
• Authoring and Editing Reports via Server Design and Usage Considerations Related to Web and Tablet & Mobile
• Sharing Connections, Data Models, and Data Extracts
• Embedding Tableau reports securely on the web
• Using Subscriptions to Deliver Reports via E-mail

14. Automating Server with Tableau’s Command Line Tools

• What do tabcmd and tabadmin do?
• Installing the Command Line Tools
• What Kinds of Tasks Can Be Done with Tabcmd?
• Learning to leverage Tabcmd

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Phase-3: Interview Preparation Phase

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• How to explain about your team members, project methodology, project lifecycle e.t.c

• How to speak in interviews based on the job description
• How to explain tell me about project which you worked? Live Explanation over the video call to understand confidence and e.t.c

• Interview Etiquette to follow as Tableau Developer

• Resume Marketing, Linkedin Marketing, Keywords optimisation, job profile optimisation e.t.c.

• Mock Interviews to benchmark your skill(Any number of mocks until you feel confident)
• Most frequently asked Tableau Interview Questions

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Python for Data Analytics

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• Goal Behind Python Mastering, Deliverables expected from every learner from Python

• Basics of Python Like Install and setup, What is value, variable, function & libraries? What is an IDE?

• Overview into Data Structures like list, tuple, set, dict, Series, Data Frame, Array

• Practice on List, Tuple, Set, Dict, Series, Data Frame & Array

• Deep Dive into List & Tuple

• Practice on List & Tuple

• Deep Dive into Set & Dict

• Explanation on: User Defined Functions, Escape Seq, For Loop, While Loop, Selection Statements, Iterations, Python Modules(Submission Date)

• Assignment Working and Submission(Programming Live Tasks)

• Live Hackathon - 1 & Solution Discussion

• Introduction to OOPS, OOPs vs POP, Types of OOPs, Types of Variables

• Types of Methods in OOPS, Practical Implementation of all the different types of OOPS

• Introduction to Pandas and Basic Pandas Commands

• Practice on 10Mins to Pandas(Pandas Task)

• Numpy Commands

• Data Visualization Theory

• Practice on Data Visualization with Matplotlib

• Practice on Data Visualisation with Seaborn & Plotly

• Data cleaning using Pandas

• Data Cleaning using Sklearn, Label Encoding, One-Hot Encoding, Imputer

• Assignment-1 on Data Cleaning

• Assignment-2 on Data Cleaning

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Basics Statistics

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• What is Data? Properties of Data like Uniform and Non-Uniform? What is Random Variable & Types of Random Variable like Continuous & Discrete Data.

• Different Types of Analytics like Descriptive Analytics, Predictive Analytics & Prescriptive Analytics.

• What is Sample vs the Population? Descriptive Statistics like Mean, Median, Mode, Standard Deviation Variance, Range, Quantiles, Outlier Identification

• Normal Distribution, Skewness & Kurtosis

• Coding to check normality, skewness & kurtosis & CL

• What is Outlier identification/Anamoly detection & Real-time implementation of statistics

• Understanding the concept of Correlation & Covariance, Probability theory & Different types of Probability and Probability Distributions, KDF, Sampling Distribution & CLT

• Q-Q Plot, Chebyshev’s inequality, Bernoulli & Binomial distribution. Log Normal distribution, Power Law Distribution, Box cox transform.

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