I was accused by many that I like Tableau too much. That is wrong: in fact I love Tableau but I will try to show below that love can be “objective”. Tremendous success of TC15 (with 10000+ attendees, unmatched by any competitor; 1st conference in 2008 attracted only 187 people) convinced me to return to my blog to write about Tableau’s history – it is interesting how it came to be.

keynote_dev_002_3

Tableau was spun out of Stanford in 2003, from project Polaris, led by professor Pat Hanrahan and Chris Stolte. It was originated at Stanford as a government-sponsored (DoD) research project to investigate new ways for users to interact (including VizQL) with relational and OLAP databases. In 2004 Tableau got $5M from VCs. In 2005, Hyperion (now Oracle owns Hyperion) began to offer a Tableau under the name “Hyperion Visual Explorer“.

By end of 2010 Tableau had 4 products: Tableau Desktop ($1999 for Pro edition), Tableau Server ($10000 for 10 users), Tableau (free) Reader and Tableau (free web service) Public. In 2010 Tableau had about $34M revenue and was one of the fastest growing software companies in the world (123% YoY). Even in Q3 of 2015 Tableau’s revenue was $171M, 64% up from Q3 of 2014 and it was twice more than entire Tableau’s revenue over period of 2003-10. Overall for last 5 years Tableau had explosive (and unsustainable by industry standards) 75% or above growth; that YoY revenue growth (and Tableau expects $650M for entire 2015) presented in bar chart below:

tableauGrowth

The text below is based on recent Tableau’s attempt to re-write own history, version by version. Also I reused some posts from this blog – I already covered in my blog versions 6.0 (in 2010) and then 6.1, 7.0, 8.0, 8.0 Desktop, 8.0 server8.1, 8.2, Tableau Online, Tableau Reader, Tableau Public.

I will follow this pattern with one exception (and I promise to avoid the marketing BS like “revolutionary innovation”). I will start with something which is still is not here yet at the end of 2015. Noted by me before: No MDI, no re-sharing of workbook infrastructure with other workbooks, no internal DB (ugly data blending instead), no in-memory columnstore, wrong approach to partners etc.

What is below is said by Tableau version by version, but interpreted by me (my blog, my opinions, my interpretation). Part 1 “Intro” covers 2004-7 from version 1 to 3, Part 2 “Catching-up” covers 2008-10 from versions 4 to 6, Part 3 “Competition” covers 2011-13 from version 6 to 8 and Part 4 “Leading the field” covers 2013-15 from version 8.1 to 9.1, including Tableau Online.

1.0. 2004.

Introduction of VizQL allowed less coding (but required a lot of drag-drops, clicks, resizing and other gymnastics with mouse, which seems more acceptable to wider population – Tableau insists on “anyone, anywhere”). Tableau 1.0 can access to Access, Excel, Microsoft Analysis Services Cubes!), MySQL, SQL Server 2000. Data from multiple tables have to be denormalized (this proved overtime to be the weakest part of the tool) into one table before importing into Tableau.

I am not sure why even in 2015 the Tableau insists on its own self-assessment that it works as fast as you can think – that is offensive to thinkers.

Tableau1

Tableau 1.0 was available in three editions. The $999 Standard Edition can connect to Microsoft Excel, Microsoft Access, or plain text files. The $1299 Professional (MySQL) edition adds MySQL to the list of supported data sources, while the $1799 Professional edition extends the list to include Microsoft SQL Server and SQL Server Analysis Services.

2.0. 2006.

Tableau 2.0 added the ability to join tables in the same database. Added the ability to create Data Extracts and work offline without live connection to data. New features: Distinct Counts and Median aggregations, new “Size” shelf (marks will be sized proportionally to the value of the field in that shelf), new “Page” shelf (useful for animations, see example of it I did a while ago):

Here the content of this video as the presentation with 24 Slides:

Tableau 2.0 also added optional trend and reference lines, calculated fields (can be used with formulas, with all functions and with custom SQL and MDX expressions). 3 Screenshots below preserved for us by Stephen Few in his reviews of Tableau 2.0 and 3.0.

tableau2

Tableau 2.0 is priced at $995 for the standard edition and $1,799 for the professional edition, including one year of software maintenance and unlimited technical support.

3.0. 2007.

Tableau Server introduced so people can see visualizations through browser over intranet or internet. When visualization application is published from Windows Desktop to Tableau Server (which is in fact, application server), it will be converted to web application: no downloads, plugins or coding required and all related data-sources will be published on that server.

Among other new features: new Sorting “shortcuts”,

tableau3

as well as Ad-hoc grouping, Auto-calculated reference lines, annotations and most importantly, dashboards with global filters. Tableau missed the opportunity to introduce the MDI into multi-view dashboards and this design bug persisted even now in 2015 – tool still using non-MDI containers (panels) instead of MDI child-windows for each chart. Another problem (in Tableau 3.0) was that views in dashboard updated sequentially and not in-parallel.

tableau3dash

By 2007 Tableau employed just 50 people but it was just a beginning:

tbGrowth

In 2007 the Tableau Software company got lucky, because TIBCO bought Spotfire that year and it greatly restricted the ability of Spotfire to lead Data Visualization field. Another luck for Tableau was a strategic mistake by both Qliktech and Spotfire to leave development teams in Sweden while placing their HQs, sales, marketing etc. elsewhere in multiple US locations. Tableau got lucky one more time later thanks to gift from Qliktech but I will discuss it later in Part 3 or 4 of this blog-post. As mentioned above, I am planning the Part 2 of this post: Tableau is catching-up, 2008-10, then Part 3: Tableau competes, 2011-13 and finally the Part 4: Tableau the leader, 2013-15

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Reading pointers below I borrowed from my Google+ microblogs “Data Visualization” (https://plus.google.com/111053008130113715119/posts , 7000+ followers) and “Data Visualization with Tableau” (https://plus.google.com/112388869729541404591/posts , almost 1000 followers). Sometimes the reading is more important then doing or writing. The reading on the beach (like below) can be even more…

PlaceToRead

  1. How Scalable Do Analytics Solutions Need to Be? http://www.perceptualedge.com/blog/?p=2097
  2. The Data Visualization Catalogue. http://blog.visual.ly/the-data-visualization-catalogue and http://datavizcatalogue.com/
  3. The Evolution of SQL Server BI, https://www.simple-talk.com/sql/reporting-services/the-evolution-of-sql-server-bi/
  4. Abela’s Folly – A Thought Confuser. http://www.perceptualedge.com/blog/?p=2080
  5. TIBCO Spotfire Promotes an Insidious Myth. http://www.perceptualedge.com/blog/?p=2035
  6. User Ideas Turned into Product Features: https://www.tableau.com/about/blog/2015/8/community-contributes-again-ideas-released-91-41812
  7. Is Data Is, or Is Data Ain’t, a Plural? http://blogs.wsj.com/economics/2012/07/05/is-data-is-or-is-data-aint-a-plural and http://www.theguardian.com/news/datablog/2010/jul/16/data-plural-singular?es_p=662983
  8. Talk: How to Visualize Data, https://eagereyes.org/talk/talk-how-to-visualize-data#more-8879
  9. Pillars Of Mapping Data To Visualizations, http://global.qlik.com/us/blog/authors/patrik-lundblad
  10. Radar Chart can be useful(?), https://www.tableau.com/about/blog/2015/7/use-radar-charts-compare-dimensions-over-several-metrics-41592
  11. Visualization Publication Data Collection, http://www.vispubdata.org/site/vispubdata/
  12. Visual Representation of SQL Joins, http://www.codeproject.com/Articles/33052/Visual-Representation-of-SQL-Joins and http://www.theinformationlab.co.uk/2015/02/05/joining-data-tables-tableau-alteryx/

Visual_SQL_JOINS_orig

  1. Example of stupidity of the crowd: http://about.g2crowd.com/press-release/best-business-intelligence-platforms-summer-2015/
  2. Reviving the Statistical Atlas of the United States with New Data, http://flowingdata.com/2015/06/16/reviving-the-statistical-atlas-of-the-united-states-with-new-data/
  3. Exploring the 7 Different Types of Data Stories: http://mediashift.org/2015/06/exploring-the-7-different-types-of-data-stories
  4. Set Your Own Style with Style Templates: http://www.tableau.com/about/blog/2015/6/saving-time-style-templates-39932
  1. A Look at Choropleth Maps , http://visualoop.com/blog/84485/a-look-at-choropleth-maps
  2. Mountain Chart for different categories (profiles) of web visits: https://public.tableau.com/profile/andrei5435#!/vizhome/MountainChart/MountainChart

MountainChart

  1. To the point: 7 reasons you should use dot graphs, http://www.maartenlambrechts.be/to-the-point-7-reasons-you-should-use-dot-graphs/
  2. Rant: A Tableau Faithful’s View On Qlik , http://curtisharris.weebly.com/blog/rant-a-tableau-faithfuls-view-on-qlik
  3. Too Big Data: Coping with Overplotting, http://www.infragistics.com/community/blogs/tim_brock/archive/2015/04/21/too-big-data-coping-with-overplotting.aspx
  4. Too much data to visualize? Data densification in Tableau 9 , https://www.linkedin.com/pulse/too-much-data-visualize-densification-tableau-9-kris-erickson
  5. The Architecture of a Data Visualization, https://medium.com/accurat-studio/the-architecture-of-a-data-visualization-470b807799b4 , also see https://medium.com/@hint_fm/design-and-redesign-4ab77206cf9
  6. Filter Views using URL Parameters , http://kb.tableau.com/articles/knowledgebase/view-filters-url

space-time

  1. Building a Visualization of Transit System Data Using GTFS , http://datablick.com/2015/05/05/building-a-visualization-of-transit-system-data-using-gtfs/
  2. A Look At Box Plots , http://visualoop.com/blog/32470/a-look-at-box-plots
  3. Custom Tableau Server Admin Views , http://ugamarkj.blogspot.com/2014/08/custom-tableau-server-admin-views.html
  4. Circular and Hive Plot Network Graphing in Tableau , http://datablick.com/2015/04/13/circular-and-hive-plot-network-graphing-in-tableau-by-chris-demartini/
  5. Hexbins in Tableau , http://www.theinformationlab.co.uk/2015/05/12/hexbins-in-tableau/
  6. Tableau Public Goes Premium for Everyone; Expands Access to 10 Million Rows of Data , http://investors.tableau.com/investor-news/investor-news-details/2015/Tableau-Public-Goes-Premium-for-Everyone-Expands-Access-to-10-Million-Rows-of-Data/default.aspx

LookFromReadingPost

2 year ago the IPO instantly created almost $3B of market capitalization for Tableau Software Inc. and since then it almost tripled, making Tableau the most “valuable” Data Visualization company (click on image to enlarge):

MCap150606b

Tableau more then doubled the number of its Full-Time employees (almost 2200 now, roughly the same (or more?) as QLIK has) and more then doubled its Revenue (again, roughly the same as QLIK has). Tableau’s YoY growth still in range of 77%-100% per year, which is far, far more then any competition:

tableauGrowth

Combination of that growth with technological progress and new features of Tableau’s products led to huge growth of its share price – it reached in 1st week of June 2015 $115, while Qlik’s share price is hovering around $37 or even below (click on image to enlarge):

data150606

Visitors to this blog kept asking me of what is most impressive (for me) about Tableau and what are my concerns. I will list just 3 of each:

  • most impressive: YoY (Year-over-Year growth ratio); migration to 64-bit (finally) and performance improvements; and  increasing capacity of Tableau Public to 10 million rows and 10 GB storage.
  • concerns: rumors that price of Tableau Server will be increased (I heard doubled; that can slow down the growth and the popularity of Tableau); moving CEO to Europe away from HQ (repeating of mistake of Spotfire and Qliktech, who had/have R&D in Europe – away from american HQ);  and limited capacity of Tableau Online (basically it can be good only for small workgroup).

Not all of its huge success can be contributed to Tableau itself:

QLIK for example did not release Qlikview version 12 for last 4 years (but kept updating the last version, recently with release 11 (!) of Qlikview version 11.2). Another help Tableau got from TIBCO, who kept Spotfire inside strict corporate cage and went private with little change for Spotfire to be a spin-off. As a result, competition for Tableau during last 2 years was weaker then before its IPO and we are witnessing a massive migration to Tableau from competitive products.

Don’t assume that Tableau is slowing down: I visualized (using Tableau Public of course, see it here: https://public.tableau.com/profile/andrei5435#!/vizhome/Data2Months/TableausMarketCap ) the Tableau’s Market capitalization during last 52 business days and it keeps growing at least as fast as last 2 years:

Tableau's Market Cap

Update 6/7/15: finally, just check the number of Job Openings @Tableau – 344 (as of today 6/7/15), @QLIK – 116 (3 times less then Tableau!), and only 1 (ONE!) opening for Spotfire… If you still think that Microstrategy can compete with Tableau, then please keep this in mind: as of today Microstrategy’s total number of Job Openings is … 50.

NewYear2015Greeting2

 

My best wishes in 2015 to visitors of this Data Visualization blog!

2014 was very unusual for Data Visualization Community. Most important event was the huge change in market competition where Tableau was a clear winner, QLIK lost it leadership position and Spotfire is slowly declining as TIBCO went private. Pleasant surprise was Microsoft, who is finally trying to package Power BI separately from Office. In addition other competitors like Microstrategy, Panorama and Datawatch were unable to gain bigger share in Data Visualization market.

2014 again was the year of Tableau: market capitalization exceeded $6B, YoY growth was highest again, sales approaching $0.5B/year, number of employees almost the same as @QLIK, LinkedIn index exceeded 90000, number of Job Openings increased again and as of today it is 337! I personally stopped comparing Data Visualization products for last few months, since Tableau is a clear winner overall and it will be difficult for others to catch-up unless Tableau will start making mistakes like QLIK and Spotfire/TIBCO did during last few years.

2014 was very confusing for many members of QLIK community, me included. Qlik.Next project resulted in new Qlik Sense Product (I don’t see too much success for it) and Qlikview 12 is still not released, while prices for both QLIK products are not public anymore. Market Capitalization of QLIK is below $3B despite still solids sales (Over $0.5B/year) and YoY growth is way below of Tableau’s YoY. Qlikview’s LinkedIn index now around 60000 (way below Tableau’s) and Qlik Sense’s LinkedIn index is only 286…  QLIK has only 124 Job opening as of today, almost 3 times less then Tableau!

Curiously, BI Guru Mr. Donald Farmer, who joined QLIK 4 years ago (a few months before the release of Qlikview 11) and who was the largest propagandist of Qlik.Next/Qlik Sense, was moved from VP of Product Management position to new “VP of Innovation” @QLIK just before the release of Qlik Sense and we hear much less from Donald now. Sadly, during these 4 years Qlikview 12 was never released, and QLIK never released anything similar to free Tableau Reader, free Tableau Public and Tableau Online (I am still hoping for Qlikview in Cloud) and all Qlikview prices were unpublished…

As a member of Spotfire community, I was sad to see the failure of Spotfire (and its parent TIBCO) to survive as public company: on December 5, Vista Equity Partners completed the acquisition of TIBX for $4.3 billion. I estimate Spotfire sales around $200M/year (assuming it is 20% of TIBCO sales). LinkedIn index of Spotfire (is way below Tableau’s and Qlikview’s) is around 12000 and number of Job Openings is too small. I hope Vista Equity Partners will spinoff the Spotfire in IPO as soon as possible and move all Spotfire’s Development, Support, Marketing and Sales into one American location, preferably somewhere in Massachusetts (e.g. back to Somerville).

Here is a farewell Line Chart (bottom of Image) to TIBX symbol, which was stopped trading 3 weeks ago (compared to DATA and QLIK Time Series (upper and middle Line Charts) for entire 2014):

data_qlik_tibx_2014

Tableau Server works as a team of multiple processes, processors, programs and applications, like data engine, data server, VizQL Server, bacgrounder, application server etc.: http://onlinehelp.tableausoftware.com/v8.3/server/en-us/processes.htm
ServerStatus
Each of those processes generates LOG files with data about user activities, data connections, queries and extractions, errors, views repaintings and interactions, etc.: http://onlinehelp.tableausoftware.com/v8.3/server/en-us/logs_loc.htm
Those data parsed regularly and stored into PostgreSQL-based Tableau Server Administrative Database, called “Workgroup” and also known as Tableau Server Repository.

PostgreSQL Server containing Workgroup DB usually runs on the same Windows Server as Main Tableau Server or (if Tableau Server runs on multimode cluster with Worker Tableau Server(s)) on other Windows Server, which runs Worker Tableau Server and uses non-standard TCP/IP port 8060.

During installation Tableau Server will create the almost empty Workgroup Repository with the main DB Schema called “public”, 100+ tables, 900+ columns (about 100 of them used as Keys), 300+ Joins, 16+ Views and 4 pre-approved users ( 2 internal (repository and rails), 1 SuperAdmin ( tblwgadmin ) and 1 default user ( tableau, which has read-only access to 16 views (click on image to enlarge):
wg82TableauViews
and nothing else). Similar Schema (with linkage between Keys for Tableau 7.0 Repository) is here (Originally published by great Russell Christopher) :
DataDictionary70

None of these pre-approved Workgroup users available outside of Tableau Server environment (unless designated static IP address(es) will be added (this may violate your Tableau License) to pg_hba.conf PostgreSQL configuration file, except “tableau” user (and new default “readonly” user) who can be given a privilege to connect to Workgroup Repository remotely as described here:
http://onlinehelp.tableausoftware.com/current/server/en-us/help.htm#adminview_postgres_access.htm

In November 2014 Tableau Software introduced (Release 8.2.5) a new, 2nd default user, named “readonly” with read access to all Tables and Views of Workgroup Repository: http://www.tableausoftware.com/support/releases/8.2.5

New “readonly” user enables us (if/when migration to Tableau 8.2.5+ or 8.3 happened) to create custom Operational Dashboards and monitor the usage and state of Tableau Server in Enterprise environment. TABADMIN utility’s command DBPASS now has new parameter “—username” which can enable remote access for “readonly default user:

tabadmin dbpass –username readonly p@ssword

Tableau Software also introduced and published the Data Dictionary and Documentation for entire Repository, its DB Schema, Tables, Views and other details here:
http://onlinehelp.tableausoftware.com/samples/en-us/data_dictionary/data_dictionary_8.2.5.html
and here:

http://onlinehelp.tableausoftware.com/current/server/en-us/data_dictionary.html

Please find below the list of all tables, columns, their data types:

Tableau 8.2 Repository: tables and columns

or you can see it here: https://public.tableausoftware.com/profile/andrei5435#!/vizhome/shared/4WQSHR642

and the portion of Diagram of “public” DB Schema for Tableau Server Repository (click on image to enlarge):
wg82L

Russell Christopher originally posted the portion of DB Schema of Tableau Server Repository for v.7.0. here: http://tableaulove.tumblr.com/post/50438516817/better-late-than-never-tableau-7-data-dictionary and then added awesome articles about History Tables in Data Dictionary for v. 8 here: http://tableaulove.tumblr.com/post/50529179435/tableau-server-v8-history-tables and here: http://tableaulove.tumblr.com/post/51220703630/tableau-server-v8-history-tables-part-3-the

Tableau’s IPO on May 17 2013 instantly created the most valuable (in terms of Market Capitalization) Data Visualization Vendor. Since then Tableau kept having the best in “BI industry” YoY growth and its sales skyrocketing, almost reaching the level of QLIK sales. During summer of 2014 DATA (stock symbol for Tableau) shares were relatively low and as one visitor to my blog cynically put it, TCC14 (Tableau Customer Conference for 2014) can be easily justified, since it raised DATA Stock and added (indirectly) to Market Cap of Tableau more than $1B to the level of more than $5B. Below is entire history of DATA prices (click on image to enlarge):

DataQlikTibxMstrSinceIPO

Tableau’s IPO on May 17 2013 instantly created the most valuable (in terms of Market Capitalization) Data Visualization Vendor. Since then Tableau kept having the best in “BI industry” YoY growth and its sales skyrocketing, almost reaching the level of QLIK sales. During summer of 2014 DATA (stock symbol for Tableau) shares were relatively low and as one visitor to my blog cynically put it, TCC14 (Tableau Customer Conference for 2014) can be easily justified, since it raised DATA Stock and added (indirectly) to Market Cap of Tableau more than $1B to the level of more than $5B. Below is entire history of DATA prices (click on image to enlarge):

For me the more indicative then the stock prices, market capitalization and a number of participants in customer conferences are numbers of job openings for competing vendors and Tableau has 270+ of them (more than 20% of its current number of employees), QLIK has 120+ (about 7% of its number of employees) and TIBCO has only about 2 dozens of openings related to Spotfire (unless I misread some other openings). For the quarter finished June 30, 2014, the company posted a year-over-year revenue increase of 82% with just over $90 million in revenue. Headcount was up 62% year-over-year to 1,532 employees worldwide.

As a background for Tableau growing sales (and tremendous YoY) you can see slow growth of QLIK sales (QLIK also delayed for almost 3 years the release of new product: we will not see Qlikvew 12, we still waiting for release of QLIK.NEXT and only recent release is Qlik Sense, which does not make too much sense to me) and almost no changes in Spotfire sales. I am guessing that Tableau is taking all those sales away from competition…

Keynotes and sessions of TCC14 were packed (you cannot find available seats on images below) and full of interesting info and even entertainment for new users and customers.

tableau-keynote-2014

These 2 fresh multimillionaires (see below, not sure why Christian’s face looks unhappy – I guess it is just me) opened TCC14 as usual, with exciting keynote.

2MultiMillionairs

You can find their keynote either on TCC14 website (link below) or on Youtube (below TCC14 link). Keynote contains 3+ parts: two speeches from co-founders (this year Christian choose theme of “Data Art” – I am not sure if it help sales,  but nevertheless entertaining and very speculative topic) and the rest of keynote about new features in upcoming release of Tableau (8.3 and 9.0?).

http://tcc14.tableauconference.com/keynote

As you see from slide below, Tableau is positioning new features in 7 groups, and I will try to mention those.

tcc-keynote-features

Let’s start with most interesting to me: potential performance gain 2x or even 4x, mostly because better usage of multithreading and 64-bit code and I quote here: “Vice President of Product Development Andrew Beers takes his turn next, speaking about Performance. He shows breakthroughs in the Viz Engine, flying through a visualized painting, seamlessly panning, zooming, and selecting. Switching into data more likely to be representative, he shows a live connection to a database of 173 million taxi rides in New York City, and dives in showing results easily four times faster than the same calculations run on the same machine running Tableau 8.2, leveraging a change in the Data Engine to use multiple CPU cores in parallel. Database queries will likewise be parallelized, with cited examples reducing 15 second queries to three, and more complex ones reduced from nearly a minute to as little as seven seconds.”

tab_conf_pan

Among other features, Chris introduced “Lasso & Radial Selections”:  these selections allow interactors to select points in shapes other than just a square. In Stolte’s keynote, he used a map as an example. He only wanted to lasso points in a city from the northwest to the southeast, not selecting some along the way. The shape ended up being like a figure eight. This was impressive.

Vice-President of Product Marketing Ellie Fields talked about new developments forthcoming in Cloud computing with Tableau, featuring Tableau Online as a platform for connecting Cloud data warehouses and applications in conjunction with on-premise data which can be presented in web browsers, on mobile devices, or even encapsulated in embedded applications.

Of course the star of TCC14 was Prof. Hans Rosling – as keynoter as well as part of the excited crowd.

HansKeynotingAtTCC14Hans stars even in cafeteria (could not resist to include his picture seating at table with right hand raised).

HansAtTCC14Another memorable event was “ZEN Masters of 2014” –

zens14

this is a living prove of huge and very capable Tableau community

ZenMastersTCC14

Tableau provided during TCC14 a lot of classes and training sessions – almost all of them were well prepared and packed. Expect many of them to be available online – many for free.

TCC14_TrainingSessionI included below two video interviews, showing insider’s take on Tableau as Sales Organization

and also Tableau’s approach to Product management with these priorities (I am curious if they always followed in real life): Quality – Schedule – Features.

 

 

While on Cape Cod this summer and when away from beach, I enjoyed some work-unrelated fun with Tableau. My beach reading included this article: http://www.theinformationlab.co.uk/2014/03/27/radar-charts-tableau-part-3/ by Andrew Ball and I decided to create my own Radar. When I show it to coworkers later, they suggested to me to publish it (at least the fun with Polygons, Path and Radars) on my blog. I may reuse this Radar chart for our internal Web Analytics. CloudsOverAtlantic

Natural Order of Points and Segments in Line.

Many visualization tools will draw the line chart, its datapoints and connecting line segments between datapoints in natural progressing order – repainting them from left to right (horizontal ordering by Axis X) or from bottom to upside
(vertical ordering by Axis Y) or vice versa.

Path as the method to break the Natural Order.

Some demanding visualizations and users wish to break the natural repainting and drawing order and Tableau allows to do that by using the Path as the method to order the datapoints and line segments in Lines and Polygons. A Collection of increasing Ordering Numbers (Pathpoints) for each Datapoint in Line defined a Path for drawing and connecting datapoints and segments of that Line (or Polygon). Each Pathpoint can be predefined or calculated, depends on mplementation and business logic.
Changing the Natural Order can create “artificial” and unusual situations, when two or more datapoints occupying the same pixels on drawing surface but have very different Pathpoints (example can be a Polygon, when Line ends in the same point it starts) or when two or more Line Segments intersecting in the same Pixel on screen (example can be the Center of the letter X ).

Radar.

Radar Chart has 2 parts: Radar Grid (background) and Radar Polygons (showing repetitive Data Patterns, if linear timeline can be collapsed into circular “timeline”). Radar Grid has Radials (with common Center) and Concentric Rings.
Polygons optionally can be filled with (transparent) color. For future Discussion let’s use the RMax as the maximal possible distance between the Center of Radar Grid (in case of Radar Grid) or the Center of Radar Polygon (in case of Radar
Polygon) and the most remote Datapoint shown in Radar Grid or Polygon respectively. We will use the “normalized” statistics of Visits to typical Website to visualize the hourly and daily (by day of the week) patterns of Web Visitations. By
normalization we mean the removal of insignificant deviations from “normal” hourly and daily amounts of Web Visits. For complete obfuscation we will assume for Demo purposes that RMax = 144.

Radar Radial Grid.

Radial Grid contains a few Radiuses (equidistant from each other) and we will draw each Radius as 3-point line where Starting and Ending points of each line are identical to each other and collocated with the Center of Radar. For Demo Web Visitation Radar we will use Radial Grid with 8 Radiuses, corresponding to the following hours of the complete 24-hours day: 0, 3, 6, 9, 12, 15, 18, 21:
radials
For example see the Radius, corresponding to HOUR = 3 (below in light brown, other Radiuses greyed out on that image):
Radiuses3
And for that Radius we are using (redundantly) the following 3 datapoints:
Radius3Data

Concentric Rings for Radar Grid.

For Demo Radar we will use 4 Concentric Rings, corresponding to 25%, 50%, 75% and 100% levels of maximum visitation per hour:
Rings
Each ring is a line with 25 datapoints, where Starting and Ending Points collocated/equal. For example, dataset for external Ring (red line above) looks like this:
Ring1Data
When Radials and Concentric Rings collocated and overlaid they represent the Radar Grid, ready to be a background for Radar Chart:
Background

Radar Polygons.

For Demo purposes we use only 2 Polygons – one (largest) representing average Hourly Visits during Weekday and 2nd Polygon representing average Hourly Visits during Weekend day. For Websites which I observed the minimum number of visits happened around 1 AM, so you will see both Polygons are slightly rotated clockwise and slightly shifted up from the Center of Radar Grid to reflect the fact that the minimum number of visitors (even around 1 AM) is slightly more then 0. Each Radar Polygon (in our Demo) has 25 Data Points with Starting and Ending Points collocated at 1AM. Here is a Weekday Polygon, overlaid with Radar Grid:
weekday
Here are the data for Weekday Polygon: 

PolygonForWeekdayData

Here is a Polygon for Weekend day, overlaid with Radar Grid:

weekend

Radar Chart.

When Radar Grid and Radar Polygons overlaid (Polygons transparent but on top of
Grid) we will get the Radar Chart. Please note that Centers of Radar Grid and Radar
Polygons can have different locations:

RadarChart

 

I published Tableau workbook with this Demo Radar Chart and Radar Data here: 

https://public.tableausoftware.com/profile/andrei5435#!/vizhome/radar/Radar