Author: pramaraj0459

Fix for corrupted Tableau dashboard

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Error Code: D2E8DA72

This document has no version number.

My situtation: Developed a Tableau dashboard spending lots of time using Tableau Public and when I tried to publish, it crashed and closed automatically without showing any prompts.

Steps taken:

Searched my computer and found Temp app created at ..\Users\AppData\Local\Temp\TableauTemp

When I tried to open that app I was prompted with above Error dialog. It was trying to open in Tableau desktop (not Public)

Then I tried with Tableau public desktop that didn’t work either but error message was different.

Resolution:

Then I took a copy of that Temp TWB in a different location and extracted it using 7-zip extractor.

A file (TWB) and a folder (Data) got extracted, twb file had the same name which I used initially.

Then I was able to open up the extracted TWB file with Tableau desktop (not Public). After opening I saved that file as packaged workbook and tried opening packaged workbook with Tableau Public desktop, this time it worked perfect.

Tableau Desktop/ Public Desktop Version: 2021.1.2

Tableau LOD explained with Simple example

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Scope of any Calculations or Aggregate functions is limited to the dimensions that are used in the View or Worksheet. Tableau LOD feature is basically for overriding that limitation.

There are basically three types of LOD Expressions,

  1. Fixed – Fixing/Hard-coding the scope, not influenced by the dimensions in View or Worksheet
  2. Exclude – Exclude the granularity, used to get rid of one or more dimensions in View or Worksheet
  3. Include – Include the granularity, dimension which is not part of the View or Worksheet can still be added to the calculation using Include expression.

Enough theory, let’s jump on to a simple example.

Sample Data:

Employee Year Cycle Reason Incentive
Emp_101 2020 Jan Company Performance 1000
Emp_101 2019 Jan Individual Performance 950
Emp_101 2019 Mar Individual Performance 950
Emp_101 2019 Oct Individual Performance 950
Emp_101 2018 Jul Company Performance 900
Emp_201 2020 Jan Company Performance 700
Emp_201 2020 Mar Individual Performance 375
Emp_201 2019 Mar Individual Performance 675
Emp_201 2018 Jul Individual Performance 650
Emp_301 2020 Jan Company Performance 800
Emp_301 2020 Mar Individual Performance 400
Emp_301 2019 Mar Individual Performance 760
Emp_301 2018 Jul Company Performance 720
Emp_301 2018 Jan Company Performance 350
Emp_301 2018 Mar Individual Performance 350

Tableau result table using all three LOD Expressions:

Tableau LOD

Calculations used in the above View:

Total Incentive – Sum(Incentive) – Regular Calculation which is influenced by dimensions in View or Worksheet

Emp Total Incentive (Exclude) – { EXCLUDE [Year]: SUM([Incentive]) } – Exclude Year dimension from the scope of SUM(Incentive) calculation

Incentive Program Total Spend (Fixed) – { FIXED : SUM([Incentive]) } – Fixing here the scope to global, it’ll not respond/get limited to any dimension used in this View or Worksheet

Avg Incentive – Avg(Incentive)

Avg Incentive based on Reason (Include) – { INCLUDE [Reason]: SUM([Incentive])} – Included additional dimension (Reason) to this calculation. The objective of this calculation was to find the Average of Incentive based on the reason types. Eg. Take a look at the Incentive amount (Source Data) for Emp_301 for 2018.  “Individual Performance” = 350 & “Company Performance” = 720 + 350 = 1070. Result for this calculation = 350 + 1070 /2 = 710, this is what you see in Tableau table chart above.

Hope this helps…

Data Modeling Blog Posts

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https://www.talend.com/blog/2017/05/05/data-model-design-best-practices-part-1/

https://www.talend.com/blog/2017/07/31/data-model-design-best-practices-part-2/

DataModelingProcess

 

DATA MODEL ASPECT HOLISTIC CONCEPTUAL LOGICAL PHYSICAL
Data Silos √      
Data Silo Relationships √      
Element Names   √    
Element Relationships   √    
Element Generalizations   √    
Element Items   √    
Entity Names     √  
Entity Relationships     √  
Entity Keys     √  
Entity Attributes     √  
Entity Constraints     √  
Table / View Names       √
Column Names       √
Column Data Types       √
Column Default Values       √
Primary / Foreign Keys       √
Index Names       √
Index Properties       √
Storage Configurations       √

 

Tableau LOD Expression

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Came across requirement to find the number of tickets worked by multiple support persons.

Especially opened New ticket by somebody and closed by another guy.

Created below dummy data to demonstrate it.

 

Date Ticket ID Support Person Status Business User Group
1/1/2019 101 Prabhu New Suman Sales
1/1/2019 101 Prabhu Inprogress Suman Sales
1/2/2019 101 Prabhu Closed Suman Sales
1/1/2019 201 Aditya New Evan Sales
1/2/2019 201 Prabhu Closed Evan Sales
1/1/2019 301 Subbu New Rob Sales
1/2/2019 301 Prabhu Closed Rob Sales
1/1/2019 401 Praveen New Rob Sales
1/2/2019 401 Subbu Closed Rob Sales
1/1/2019 501 Praveen New Rob Sales
1/2/2019 501 Subbu Closed Rob Sales

Loaded this data into a Tableau dashboard and created below calculated field.

Tickets worked by different Support Person: “IIF({FIXED [Ticket ID]: COUNTD(IIF([Status]=’New’ and [Status]=’Closed’, [Support Person], [Support Person]))}=2,1,0)”

This field can be used as filter or in appropriate marks of the worksheets.

Used the calculated field directly in table below just to show.

post1

Used in below bar chart too. 0 represents Tickets worked by just same person and 1 represents by different person.

Post2.JPG

–map-column-hive is getting ignore in sqoop 1.4.6

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sqoop import -D mapred.job.queue.name=root.ficc.qar -D mapreduce.map.memory.mb=3072 -D mapreduce.map.java.opts=-Xmx3072m –connect “jdbc:oracle:thin:@servername.corp.company.com:40000/DB_ServiceName” –table EMPLOYEE –username USERNAME –password-file /user/id/pwd –split-by JOINDATE -m 1 –hive-import –hive-database hiveDB –hive-table EMPLOYEE –map-column-hive ID=INT64,NAME=VARCHAR,DEPARTMENT=VARCHAR,JOINDATE=TIMESTAMP –compress –compression-codec org.apache.hadoop.io.compress.SnappyCodec –as-parquetfile

Hive> describe Employee;

Name Type
1 id string
2 name string
3 department string
4 joindate bigint

Generic Image Thumbnails for a Workbook in Tableau Server

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On the server where you publish, one of the options for browsing content is by thumbnail view. In this view, thumbnails are generated based on the workbook and its sheets. If your workbook contains user filter, you can specify which user’s filter to use for creating the thumbnails.
For example, if you want the thumbnail image to show all regions of a sales forecast, you can generate thumbnails per the user who is allowed to see all regions.
In the following scenarios, a generic image appears in place of the view thumbnail.
The user you select does not have permission to see the data.
The data is from a Tableau Server data source that was published with data source filters, user calculations, impersonation, or other user reference.