What is data visualization, Comparison and benefits against reading raw numbers, Real usage examples from various business domains, Some quick powerful examples using Tableau without going into the technical details of Tableau, installing Tableau, Tableau interface, connecting to DataSource, Tableau Data Types, data preparation.
Installation of Tableau Desktop, Architecture of Tableau, Interface of Tableau (Layout, Toolbars, Data Pane, Analytics Pane etc), How to start with Tableau, Ways to share and exporting the work done in Tableau
Hands-on Exercise – Play with the tableau desktop, interface to learn its user interface, Share an existing work, Export an existing work
Connection to Excels, PDFs and Cubes, Managing Metadata and Extracts, Data Preparation and dealing with NULL values, Data Joins (Inner, Left, Right, Outer) and Union, Cross Database joining, Data Blending, data extraction, refresh extraction, incremental extraction, how to build extract
Hands-on Exercise – Connect to an excel sheet and import data, Use metadata and extracts, Handle NULL values, Clean up the data before the actual use, Perform various join techniques, Perform data blending from more than one sources
Marks, Highlighting, Sort and Group, Working with Sets (Creation of sets, Editing sets, IN/OUT, Sets in Hierarchies), constant sets, computed Sets, bins
Hands-on Exercise – Create and edit sets using Marks, Highlight desired items, Make groups, Applying sorting on result, Make hierachies in the created set
Filters (Addition and Removal), Filtering continuous dates, dimensions, measures, Interactive Filters, marks card, hierarchies, how to create folders in Tableau, sorting in Tableau, types of sorting, filtering in Tableau, types of filters, filtering order of operations
Hands-on Exercise – Add Filter on data set by date/dimensions/measures, Use interactive filter to views, Remove some filters to see the result
Formatting Data (Labels, Annotations, Tooltips, Edit axes), Formatting Pane (Menu, Settings, Font, Alignment, Copy-Paste), Trend and Reference Lines, Forecasting, k-means Cluster Analysis in Tableau, visual analytics in Tableau, reference lines and bands, confidence interval.
Hands-on Exercise – Apply labels, annotations, tooltips to graphs, Edit the attributes of axes, Set a reference line, Do k-means cluster analysis on a dataset
Coordinate points, Plotting Longitude and Latitude, Editing Unrecognized Locations, Custom Geocoding, Polygon Maps, WMS: Web Mapping Services, Background Image (Add Image, Plot Points on Image, Generate coordinates from Image), map visualization, custom territories, Map Box, WMS Map, how we can create map projects in Tableau, how to create Dual Access Map, how to edit location.
Hands-on Exercise – Plot latitude and longitude on geo map, Edit locations on the map, Create custom geocoding, Use images of a map and plot points on it, find coordinates in the image, Create a polygon map, Use WMS
Calculation Syntax and Functions in Tableau, Types of Calculations (Table, String, Logic, Date, Number, Aggregate), LOD Expressions (concept and syntax), Aggregation and Replication with LOD Expressions, Nested LOD Expressions, Level of Details, Fixed Level of Details, Lower Level of Details, Higher Level of Details, Quick Table Calculations, how to create Calculated Fields, predefined Calculations, how to validate.
Create Parameters, Parameters in Calculations, Using Parameters with Filters, Column Selection Parameters, Chart Selection Parameters, how to use Parameters in Filter Session, how to use parameters in Calculated Fields, how to use parameters in Reference Line.
Hands-on Exercise – Create new parameters to apply on a filter, Pass parameters to filters to selet columns, Pass parameters to filters to select charts
Dual Axes Graphs, Histogram (Single and Dual Axes), Box Plot, Pareto Chart, Motion Chart, Funnel Chart, Waterfall Chart, Tree Map, Heat Map, Market Basket analysis, Using Show me, Types of Charts, Text Table, Heat map, Highlighted Table, Pie Chart, Tree map, Bar chart, Line Chart, Bubble Chart, Bullet chart, Scatter Chart, Dual Axis Graphs, Funnel Charts, Pareto Chart, Maps, Hands on Lab, Assignment, Funnel Chart, Waterfall Chart, Maps
Hands-on Exercise – Plot a histogram, heat map, tree map, funnel chart and others using the same data set, Do market basket analysis on a given dataset
Build and Format a Dashboard (Size, Views, Objects, Legends and Filters), Best Practices for Creative and Interactive Dashboards using Actions, Create Stories (Intro of Story Points, Creating and Updating Story Points, Adding Visuals in Stories, Annotations with Description), DashBoards & Stories, what is Dashboard, Filter Actions, Highlight Actions, Url Actions , Selecting & Clearing values, DashBoard Examples, Best Practices in Creating DashBoards, Tableau WorkSpace, Tableau Interface, Tableau Joins, Types of Joins, Live vs Extract Connection, Tableau Field Types, Saving and Publishing Data Source, File Types
Hands-on Exercise – Create a dashboard view, Include objects, legends and filters, Make the dashboard interactive, Create and edit a story with visual effects, annotation, description
Introduction to Tableau Prep, how Tableau Prep helps to quickly combine join, shape and clean data for analysis, create smart experiences with Tableu Prep, get deeper insights into your data with great visual experience, make data preparation simpler and accessible, integrate Tableau Prep with Tableau analytical workflow, seamless process from data preparation to analysis with Tableau Prep
Introduction to R Language, Applications and Use Cases of R, Deploying R on Tableau Platform, Learning R functions in Tableau, Integration with Hadoop
Hands-on Exercise – Deploy R on tableau, Create a line graph using R interface, Connect tableau with Hadoop and extract data
R language for statistical programming, the various features of R, introduction to R Studio, the statistical packages, familiarity with different data types and functions, learning to deploy them in various scenarios, use SQL to apply ‘join’ function, components of R Studio like code editor, visualization and debugging tools, learn about R-bind.
R Functions, code compilation and data in well-defined format called R-Packages, learn about R-Package structure, Package metadata and testing, CRAN (Comprehensive R Archive Network), Vector creation and variables values assignment.
R functionality, Rep Function, generating Repeats, Sorting and generating Factor Levels, Transpose and Stack Function.
Introduction to matrix and vector in R, understanding the various functions like Merge, Strsplit, Matrix manipulation, rowSums, rowMeans, colMeans, colSums, sequencing, repetition, indexing and other functions.
Understanding subscripts in plots in R, how to obtain parts of vectors, using subscripts with arrays, as logical variables, with lists, understanding how to read data from external files.
Generate plot in R, Graphs, Bar Plots, Line Plots, Histogram, components of Pie Chart.
Understanding Analysis of Variance (ANOVA) statistical technique, working with Pie Charts, Histograms, deploying ANOVA with R, one way ANOVA, two way ANOVA.
K-Means Clustering for Cluster & Affinity Analysis, Cluster Algorithm, cohesive subset of items, solving clustering issues, working with large datasets, association rule mining affinity analysis for data mining and analysis and learning co-occurrence relationships.
Introduction to Association Rule Mining, the various concepts of Association Rule Mining, various methods to predict relations between variables in large datasets, the algorithm and rules of Association Rule Mining, understanding single cardinality.
Understanding what is Simple Linear Regression, the various equations of Line, Slope, Y-Intercept Regression Line, deploying analysis using Regression, the least square criterion, interpreting the results, standard error to estimate and measure of variation.
Scatter Plots, Two variable Relationship, Simple Linear Regression analysis, Line of best fit
Deep understanding of the measure of variation, the concept of co-efficient of determination, F-Test, the test statistic with an F-distribution, advanced regression in R, prediction linear regression.
Logistic Regression Mean, Logistic Regression in R.
Advanced logistic regression, understanding how to do prediction using logistic regression, ensuring the model is accurate, understanding sensitivity and specificity, confusion matrix, what is ROC, a graphical plot illustrating binary classifier system, ROC curve in R for determining sensitivity/specificity trade-offs for a binary classifier.
Detailed understanding of ROC, area under ROC Curve, converting the variable, data set partitioning, understanding how to check for multicollinearlity, how two or more variables are highly correlated, building of model, advanced data set partitioning, interpreting of the output, predicting the output, detailed confusion matrix, deploying the Hosmer-Lemeshow test for checking whether the observed event rates match the expected event rates.
Data analysis with R, understanding the WALD test, MC Fadden’s pseudo R-squared, the significance of the area under ROC Curve, Kolmogorov Smirnov Chart which is non-parametric test of one dimensional probability distribution.
Connecting to various databases from the R environment, deploying the ODBC tables for reading the data, visualization of the performance of the algorithm using Confusion Matrix.
Creating an integrated environment for deploying R on Hadoop platform, working with R Hadoop, RMR package and R Hadoop Integrated Programming Environment, R programming for MapReduce jobs and Hadoop execution.
Logistic Regression Case Study
In this case study you will get a detailed understanding of the advertisement spends of a company that will help to drive more sales. You will deploy logistic regression to forecast the future trends, detect patterns, uncover insights and more all through the power of R programming. Due to this the future advertisement spends can be decided and optimized for higher revenues.
Multiple Regression Case Study
You will understand how to compare the miles per gallon (MPG) of a car based on the various parameters. You will deploy multiple regression and note down the MPG for car make, model, speed, load conditions, etc. It includes the model building, model diagnostic, checking the ROC curve, among other things.
Receiver Operating Characteristic (ROC) case study
You will work with various data sets in R, deploy data exploration methodologies, build scalable models, predict the outcome with highest precision, diagnose the model that you have created with various real world data, check the ROC curve and more.
Project 1 – Tableau Interactive Dashboard
Data Set – Sales
Objective – This project is involved with working on a Tableau dashboard for sales data. You will gain in-depth experience in working with dashboard objects, learn about visualizing data, highlight action, and dashboard shortcuts. With a few clicks you will be able to combine multiple data sources, add filters and drill down specific information. You will be proficient in creating real time visualizations that are interactive within minutes.
Upon completion of this project you will understand how to create a single point of access for all your sales data, ways of dissecting and analyzing sales from multiple angles, coming up with a sales strategy for improved business revenues.
Domain – Crime Statistics (Public Domain)
Objective – The Project aims to show the types of crimes and their frequency that happen in the District of Columbia. Also to provide the details of the crimes like, the area/location and day of the week the crime has happened
Problem statement : Police departments are often called upon to put more “feet on the street” to prevent crime and keep order. But with limited resources, it’s impossible to be everywhere at once. This visualization shows where crimes take place by type and which day of the week. This kind of information gives local police more guidance on where they should deploy their crime prevention efforts.
Project 3 :Analyzing economic data
Industry – Government
Problem Statement – How unemployment is affecting global malnutrition
In this Tableau project you will be working on vast amounts of data and analyze it to come up with trends, insights and correlations. The data sets include the global unemployment figures for multiple years, world population statistics across several years, nutritional data across the globe. Analyzing this data, you will correlate the malnutrition problem with the unemployment rates by using Tableau.
Project 4 : Analyzing market performance
Industry : Retail
Problem Statement – Using the Consumer Packaged Goods data to analyze which are the markets which are performing well for a particular retail enterprise using Tableau Desktop.
Topic : This Tableau Desktop project involves working with the complex Consumer Packaged Goods data to come up with the brand performance analysis, regions that are contributing good to the revenues, where there is a need to offer more discounts to spur sales, and making in-depth budget vs. spend analysis for any particular year.
Domain – Restaurant Revenue Prediction
Data set – Sales
Project Description – This project involves predicting the sales of a restaurant on the basis of certain objective measurements. This project will give real time industry experience on handling multiple use cases and derive the solution. This project gives insights about feature engineering and selection.
Domain – Data Analytics
Objective – To predict about the class of a flower using its petal’s dimensions
Domain – Finance
Objective – The project aims to find the most impacting factors in preferences of pre-paid model, also identifies which are all the variables highly correlated with impacting factors
Domain – Stock Market
Objective – This project focuses on Machine Learning by creating predictive data model to predict future stock prices
Intellipaat provides the most sought-after Tableau and R training for professionals looking to upgrade their skills. R is a statistical language that is Open Source and it can be connected with Tableau Desktop so that the various R libraries, functions and packages can be used with Tableau. With R and Tableau you can get a simple drag and drop visualization functionality.
This training gives you a powerful combination of one of the best BI tools combined with a statistical computation framework. The entire course content is in line with clearing the Tableau Desktop Qualified Associate Exam Certification.
This is a completely career-oriented training designed by industry experts. Your training program includes real time projects, step-by-step assignments to evaluate your progress and specially designed quizzes for clearing the requisite certification exams.
Intellipaat also offers lifetime access to videos, course materials, 24/7 Support, and course material upgrades to latest version at no extra fees. Hence it is clearly a one-time investment.
This course is designed for clearing the following certification exam:
The entire training course content is in line with respective certification program and helps you clear the requisite certification exam with ease and get the best jobs in the top MNCs.
As part of this training you will be working on real time projects and assignments that have immense implications in the real world industry scenario thus helping you fast track your career effortlessly.
At the end of this training program there will be quizzes that perfectly reflect the type of questions asked in the respective certification exams and helps you score better marks in certification exam.
Intellipaat R Certification and Intellipaat Course Completion certificate will be awarded on the completion of Project work (on expert review)(upon review by experts) and on scoring of at least 60% marks in the quiz. Intellipaat certification is well recognized in top 80+ MNCs like Ericsson, Cisco, Cognizant, Sony, Mu Sigma, Saint-Gobain, Standard Chartered, TCS, Genpact, Hexaware, etc.
You will get Lifetime access to high quality interactive tutorials along with life time access to complete Course Material .There will be 24/7 access to video tutorials with email support. If you stuck in any unexpected problem we will provide online interactive sessions with trainer for issue resolving.
We provide 24X7 support by email for issues or doubts clearance for Self-paced training.
In online Instructor led training, trainer will be available to help you out with your queries regarding the course. If required, the support team can also provide you live support by accessing your machine remotely. This ensures that all your doubts and problems faced during labs and project work are clarified round the clock.
This course is designed for clearing Tableau Desktop Qualified Associate Certification conducted by Tableau software and Intellipaat R Certification and Intellipaat Course Completion certificate conducted by any reputed agency.
At the end of the course there will be a quiz and project assignments once you complete them you will be awarded with Intellipaat Course Completion certificate.
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