TABLEAU 2018: Hands-On Tableau Training For Data Science!

Identify the top performing employee in each region who earns the annual bonus by analyzing a CSV sales dataset in Tableau, using calculated fields, colors, labels, and exporting worksheets.

Connect Tableau to a csv text file using the connection manager, preview the data, identify dates, text, and numbers, and explore linking multiple data sources with live connections.

Navigate Tableau's workspace by exploring the data tab and dragging dimensions and measures to build worksheets. Create bar, pie, bubble, and tree map visuals with Show Me.

In this Tableau 2018 hands-on lesson, create calculated fields to compute total sales (units times unit price) and identify regional top performers by sorting visuals.

Learn how to use color in Tableau to enhance data storytelling, from applying discrete and continuous colors, choosing palettes (including colorblind-friendly options), to color-coding by region for clear comparisons.

Add labels and format charts in Tableau to enhance readability. Show total sales on bars with currency formatting and align axis settings.

Export Tableau worksheets as images by copying or using export, include the title and legend, and paste into Word or PowerPoint while learning basic Tableau navigation.

Download all visuals and workbooks from the Tableau public profile using the download icon. Open them in Tableau to check your work or follow along during the lessons.

Explore time series data by visualizing the US long-term unemployment rate, analyze trends across categories, and apply granularity, aggregation, and filters to craft an area chart.

Explore preparing and importing data in Tableau, compare live connections and extracts, and learn to create, save, and refresh data extracts for efficient analysis.

Explore time series visualization in Tableau by plotting unemployment over period, adjust granularity to month or year, and switch period from a dimension to a measure for an accurate timeline.

Explore how Tableau uses aggregation and granularity to control data level of detail, with measures and dimensions shaping monthly and gender breakdowns, and how detail enhances granularity without changing visuals.

Learn to create an area chart in Tableau, use highlighting to compare unemployment by gender and age from 2005 to 2015, and add labels for clarity.

Learn to add and customize filters in Tableau, including gender and age filters, use quick filters for instant updates, and explore filter types like single value lists and dropdowns.

Discover hands-on Tableau 2018 techniques as you build a regional sales map and customer scatterplot, then assemble your first interactive dashboard with actions.

Join two data tabs in Tableau by matching order id to create a unified table; understand inner join behavior and how duplicates appear when an order relates to multiple items.

Explore creating a Europe map in Tableau, building a geography hierarchy from country, state, and city, and calculating profit margin to visualize sales with filters, colors, and drill-down.

Create a scatter plot in Tableau, apply a filter across multiple worksheets, and build a multi-sheet workbook to analyze customer profitability by year with color by profit margin.

Create a dashboard in Tableau by combining a map of Europe and a customer scatterplot, then add quick filters, containers, and an all worksheets filter for interactive analysis.

Learn to make dashboards interactive in Tableau by adding actions, using filtering and highlighting, and drilling into regions with a map of Europe to filter related sheets.

Explore the difference between highlighting and filtering in Tableau dashboards, and learn to adjust granularity by state to accurately highlight customers without filtering data.

Explore how Tableau handles joining and blending data from multiple sources, including Excel, CSV, and Teradata, with practical tutorials and advanced calculated fields across a blend.

Explore inner, left, right, and full outer joins on two tables, learning how matches on a key produce combined results and how nonmatches yield nulls.

Explore inner joins with duplicates on the join column, merging table A orders with table B orders by order number, and learn how duplicates replicate rows while non-matches are discarded.

Learn how joining on multiple fields, including store and order number, with a left join prevents inflated sales and yields correct customer totals in Tableau.

Master data blending in Tableau and distinguish it from joining. Learn to blend on the fly with primary and secondary data sources, using region and period.

Explore the differences between joining and blending data in Tableau, and learn when blending is preferable for different data source types or granularity to build cohesive dashboards.

Master blending and create a dual axis chart in Tableau by joining data sources on category, month of order date, and year, then synchronize axes to compare targets with sales.

Create a calculated field across a blend to measure the excess of target versus actual sales, including aggregation details and keeping category as a detail.

Review the joining and blending of data in Tableau, covering inner, left, right, and full joins, duplicates, multi-field joins, blending mechanics, granularity, and dual axis charts.

Create an epic, highly interactive dashboard in Tableau that visually presents insights, using table calculations and parameters to combine all learned skills.

Download the UK bank customers dataset from supersize dot com slash Tablo, connect to the CSP text file in Tableau, and create visuals, dashboards, and a storyline showing regional representation.

Learn to set geographic roles for region data to generate maps, fix unknowns by assigning the United Kingdom, and display total customers using the number of records.

Create a gender-based pie chart in Tableau to visualize bank member demographics, using a table calculation to show percent of total for male and female segments.

Create age distributions in Tableau by binning ages into five-year groups, converting the age field to a dimension, then display percentages of total for dashboard-friendly insights.

Learn to leverage parameters in Tableau to dynamically adjust balance and age bin sizes, linking integer parameters to charts and enabling quick, insightful explorations.

Create a tree map in Tableau 2018 using the job classification and record counts, adjust colors and formatting, then save the worksheet.

Assemble a customer segmentation dashboard in Tableau by integrating map, balance and age distributions, gender split, and job classification tree map, with formatting for an interactive visualization.

Make the dashboard interactive with filter actions and region filters to cross-filter charts, revealing regional, gender, and occupation patterns, then disable tooltips for a cleaner view.

Explore how the customer segmentation dashboard reveals regional differences across England, Scotland, Wales, and Northern Ireland, analyzing balance, age, gender, and job class to tailor regional marketing campaigns.

Transform a customer segmentation dashboard into a Tableau storyline across the United Kingdom, with region-specific captions and annotations. Explore demographics, age bands, and balance distributions using independent parameter controls.

Master data cleaning and preparation in Tableau using pivoting, splitting, and the metadata grid to prepare data for analysis and minimize map errors.

Learn how to format data for Tableau imports by structuring it with separate age, gender, and period dimensions and a single measure, removing totals, and filling blanks for accurate analysis.

Learn to clean and structure messy human-style data with Tableau’s data interpreter, then review results to correctly map regions, countries, and years as columns for seamless data import.

Pivot the data in Tableau to transform year columns into a single year column with region, country, year, and total sales, enabling easy comparison with your spreadsheet.

Master the split feature in Tableau 9 to turn a single column into multiple columns, such as separating surname from a full name, by using a space as the separator.

Explore the metadata grid to view and refine column names, regions, countries, and pivot year fields. Apply table calculations to show percent of total regional shares of vehicles sold.

Fix geographical data errors in Tableau maps by editing locations, correcting misspellings, and geocoding unknowns. Learn to specify country when cities or regions are ambiguous to ensure accurate map visualizations.

Evaluate two sales regions and ten new cities in Tableau to compare revenue, marketing spend, and ROI, guiding optimal marketing investments for startup expansion.

Learn to create custom territories in Tableau using groups, visualize two sales regions on a map, and compare metrics like average revenue, marketing spend, and return on marketing investment.

Learn how to create custom territories in tableau 2018 by using geographic roles, converting states into sales regions through data aggregation, and visualizing with maps.

Learn to visualize company markets in Tableau 2018 with geographies, revenue-driven map visuals, and the highlight feature to identify the ten new expansion cities quickly.

Learn to cluster Tableau data with k-means to group cities by revenue and marketing spend, build storytelling visualizations, and derive return on investment insights from identified clusters.

Explore cross-dataset joins in Tableau 2018 to fuse an Excel population file with a text and CSV dataset, join by city and state, and validate results to refine clustering analysis.

Learn how Tableau's cluster analysis incorporates population alongside marketing spend and revenue to reveal three distinct groups, and how trend lines guide investment decisions.

Save and reuse clusters across sheets by creating a group from clusters, then apply them to color and size on maps to show average population per cluster and city distribution.

Explore how to design and test dashboards for mobile devices in Tableau 2018, using device preview to adapt layouts for tablets and phones, including maps, cluster analysis, and trend lines.

In this section, explore Tableau 2018 features while solving two real-world business challenges—analyzing NYC park crime incidents from PDFs and spatial files, using map visuals with tooltips and filters.

Connect and analyze pdf data in Tableau 10.3, recognizing pdfs as portable, non editable documents with images, text, tables, graphs, and no metadata.

Connect to pdf data in Tableau, use data interpreter to clean tables, union multiple pages, resolve header issues, and filter out totals to reveal 109 incidents.

Connect to spatial files in Tableau by using shapefiles (SHP, SHX, DBF) to build polygon, point, and line maps, using the geometry field and NYC parks as examples.

Learn how to join spatial files with pdf crime data using inner and left joins, ensure data integrity and completeness, manage duplicates, and prep geometry for a Tableau map.

Build an end-to-end tableau map by importing a pdf and merging it with spatial data, cleaning data, and applying a green-to-red incident color scale to NYC parks by borough.

Create a single-sheet Tableau visualization that maps average salary by county, shows top five industries by county, and displays a time-series of county averages with step and jump line charts.

Learn to build a New York counties map in Tableau, compute the average annual salary across years, and embed two sheets into tooltips to compare counties and top industries.

Extract data from PDFs with Tableau's PDF connector, join spatial NYC open data, and apply unions and data interpretor checks to explore time trends while preserving data quality.

Celebrate completing Tableau 2018 hands-on training for data science with a post-course tribute featuring Tasmania scenery, Cradle Mountain, and Crater Lake, while inviting you to leave a review.