I am currently working on Tableau using 2 data sources using each a join of 2 tables (named A, B, C):
Data source 1: A-B
Data source 2: A-C
Basically, A contains the major information that I need and then I join data from B and C to get the extra information I need for each report I am doing.
I then do a dashboard that contains reports using the data source 1 and 2.
My problem now is that I am filtering this dashboard using a dimension in A and I would like it to apply to all worksheets (e.g. for those using data sources 1 and those using data source 2).
I thought that because A is the common table in all data sources, that using a dimension in A would be ok to filter everything but it seems that it is not the case.
Is there a way to fix this?
I read some forums about creating a parameter. However, the filtering I am doing is basically as follows: I want my users to choose 1 shop name. They can find it either by:
Typing the name in the 'Shop name' quick filter,
Using a combination of the quick filters 'Region' and 'country' to then get a drop down of 'Shop Name' that has a reduced amounts of shop names (easier when the user knows where the shop is but does not remember its exact name).
Using a parameter would not allow me to do this anymore since all of this is based on 'filtering the relevant values'.
Does anyone have any recommendations?
Related
I am currently working with a field in pig that contains multiple values. I am looking to count users by product by location and I used LOAD to create data in the following format: (Location, {(product1), (product2), (product3)}, numOfUsers). I am looking to separate out each of the products and treat them as separate entities meaning i'd like to end up with the following:
(location, (product1), numOfUsers)
(location, (product2), numOfUsers)
(location, (product3), numOfUsers)
I believe I need to use some sort of nested FOREACH function, but i'm a bit lost. Num of users for each product contained in the same tuple will be the same since they are grouped and that's perfectly fine. I am a beginner (started with Pig 3 days ago) so any guidance would be greatly appreciated. I believe I would use FLATTEN?
FOREACH A GENERATE location, FLATTEN(products) AS product, numOfUsers;
Solved the issue. This created a cross product of all records that were stored within the bag. Used http://www.st.ewi.tudelft.nl/~hauff/BDP-Lectures/9_10_advanced_pig.pdf for reference. Very useful resource.
When I use kettle , I was wandering how to get a table column's source column. Just for an example , after I have merged two tables into one table based on primary key already , Given any column in output table , I could judge whether table it belongs to and get the original column name in original table. Thank you for helping and sorry for my poor English...
http://i.stack.imgur.com/xoR0s.png
When I was given any field in table3 (suppose a field named A in table3) , I could know where it comes from without the graphical view (from java code or other ways) , like the original table name (here are input1 or input2) and the original column name(maybe B in input1 , but represents A in table3). Besides I use mysql.
There are a couple of ways to do this:
1) Manually. If you right-click on the output step and choose Show Output fields (or whatever it's called), you will see the "origin step" for each of the outgoing fields. You can do the same for input fields. Then you can trace them back to those origin steps, and repeat the process of viewing the input fields at those steps, and seeing those fields' origins, and so on. This is probably not what you're looking for.
2) With code. Prior to 6.0, you'd need to programmatically perform the same operations as are listed in option 1 above. In 6.0 there is the Data Lineage capability, which offers the LineageClient API that can find the origin fields for the specified output fields. For more information see my blog post describing the Data Lineage capability. Also I put a Gremlin Console in the PDI Marketplace, to make the use of LineageClient easier (and you can visually see the lineage graph too).
I'm testing Kibana 4 for a project.
I have created an index from my database table which is composed by 3 fields:
Date
User
Action
I would like to display my index as a simple table (3 column, N rows) in my dashboard.
I tried to use "Data table" visualization but I can't find a way to display my results without any Metrics (Count, Sum etc...)
Maybe is pretty simple and I missed something... is there a way to do this?
Regards,
On the Discover tab, create a view that has just the fields you want and then save that as a search.
On the Dashboard tab, click on Edit then hit the + Create new button to add a widget, but if you look at the top, there's a Searches tab. Select that and add your saved search in.
[Elastic 7.x / 2019 Update]
I was a bit confused when I read #Alcanzar's answer so I am sharing a little more noob-friendly step-by-step how-to here :
STEP 1 : Create the Index Pattern
STEP 2 : Go to the Dashboard view, and create a view on your index
Select each column you want to include/add in your view by clicking "add" on it (The confusing part is that until you do that, you will have a "scrambled" view listing everything in a jumbled way.)
STEP 3 : Go to the Dashboard view, and create a view on your index
The trick is to select the specific columns you want to include... and voila !
Don't forget to save your view, this will help a lot in the process.
In Kibana 7.5.0 you can do it as follows:
Go to Discover section
Select fields you are interested in
Click on Save to save your discover search so you can use it in visualizations and dashboards
Click on Dashboard and create a new dashboard
Click on Add and select the panel
There is no step 6
The accepted solution has its pros (if, for simplicity, you see your index as a table, this is the only way to deal with rows naturally) but also cons (it allows the user to see too much information, by expanding the records that appear in the table; users cannot get an export of the values).
So if you plan to build tables to use in reports seen by users which should not see everthing and may want to get exports of the data, I recommend a different (hacky) approach using Table visualizations:
Say you have three columns A, B and C:
If there are no duplicates considering the combined values of A and B, you can use these two vales as aggregation fields, and then set a Max or Top hit Metric for C.
If even A, B and C have duplicates, then you can use the three of them as aggregation fields and add a Metric count, that will give you the number of repeated rows. This solution makes somehow sense, because instead of repeating the same row 'n' times you just tells you should have repeated 'n' times that row.
If A and B have duplicates but A, B and C are unique, then there is, afaik, no elegant solution. You have to use the three of them as aggregation fields, but then you would have a dummy metric at the end (e.g. count, always equal to 1).
Why? why do we have to go through all of this? that is another question...
I'm testing Kibana 4 for a project.
I have created an index from my database table which is composed by 3 fields:
Date
User
Action
I would like to display my index as a simple table (3 column, N rows) in my dashboard.
I tried to use "Data table" visualization but I can't find a way to display my results without any Metrics (Count, Sum etc...)
Maybe is pretty simple and I missed something... is there a way to do this?
Regards,
On the Discover tab, create a view that has just the fields you want and then save that as a search.
On the Dashboard tab, click on Edit then hit the + Create new button to add a widget, but if you look at the top, there's a Searches tab. Select that and add your saved search in.
[Elastic 7.x / 2019 Update]
I was a bit confused when I read #Alcanzar's answer so I am sharing a little more noob-friendly step-by-step how-to here :
STEP 1 : Create the Index Pattern
STEP 2 : Go to the Dashboard view, and create a view on your index
Select each column you want to include/add in your view by clicking "add" on it (The confusing part is that until you do that, you will have a "scrambled" view listing everything in a jumbled way.)
STEP 3 : Go to the Dashboard view, and create a view on your index
The trick is to select the specific columns you want to include... and voila !
Don't forget to save your view, this will help a lot in the process.
In Kibana 7.5.0 you can do it as follows:
Go to Discover section
Select fields you are interested in
Click on Save to save your discover search so you can use it in visualizations and dashboards
Click on Dashboard and create a new dashboard
Click on Add and select the panel
There is no step 6
The accepted solution has its pros (if, for simplicity, you see your index as a table, this is the only way to deal with rows naturally) but also cons (it allows the user to see too much information, by expanding the records that appear in the table; users cannot get an export of the values).
So if you plan to build tables to use in reports seen by users which should not see everthing and may want to get exports of the data, I recommend a different (hacky) approach using Table visualizations:
Say you have three columns A, B and C:
If there are no duplicates considering the combined values of A and B, you can use these two vales as aggregation fields, and then set a Max or Top hit Metric for C.
If even A, B and C have duplicates, then you can use the three of them as aggregation fields and add a Metric count, that will give you the number of repeated rows. This solution makes somehow sense, because instead of repeating the same row 'n' times you just tells you should have repeated 'n' times that row.
If A and B have duplicates but A, B and C are unique, then there is, afaik, no elegant solution. You have to use the three of them as aggregation fields, but then you would have a dummy metric at the end (e.g. count, always equal to 1).
Why? why do we have to go through all of this? that is another question...
I have a Tableau dashboard with various visualizations created from 3 data sources (i.e. A,B, C).
Each data source has a relationship (join) with the same secondary data source (i.e. D), and the secondary data sources provides information to create a filter for each data source. In other words, there is the following relationship for my data sources:
A - D
B - D
C - D
I would like to create a global filter on a dashboard I have created. I would like one filter card from "D" to show up and be applied to "A," "B," and "C" at once rather than having a separate filter card show up for each data source.
I tried to create a global filter via a parameter and calculated field, but the parameter requires layers of connections because data sources "A,B, and C" only have "D" in common.
Thoughts?
Its not completely clear from your question, but it sounds like you are using Tableau data blending on your worksheets to include data from multiple data sources, rather than a join to create a data source based on multiple tables. If all your tables are on the same database server or spreadsheet, then traditional joins are usually more efficient than data blending.
The following approach often works well.
Instead of using Tableau's quick filter feature, create a worksheet based solely on D that shows the values you wish to use for filtering. It can be a simple list of names, or a bubble chart or anything you like. Use that worksheet as your filter by creating actions where it is the source and all the other worksheets on your dashboard are the target. Typically, you would want to specify the field names explicitly.
Data blending is useful but can be complex. Depending on details, you may need to make D the primary data source on your other worksheets. Experiment.
The parameter and calculated field you mentioned can be even simpler and faster than using actions, but users are restricted to selecting a single value for a parameter unlike the filter action approach. (Of course, one parameter value can represent multiple values in your target data source field depending entirely on how your calculated field interprets the parameter).
I can't tell why that didn't work for you or what you mean by "layers of connections". You might consider clarifying that part of your question.