I would like to link multiple times to the same dimension without making a copy of the dimension. I understand that other products have such a feature (role-playing dimensions) but I can't find such functionality in icCube.
Is it really not possible in icCube?
For the time being you can't link multiple time the same dimension in a measure group. So, you've to copy your dimension (you've a button for doing this in the UI).
Is this a problem ?
Related
I already saw other questions from other users and I still couldnt help myself on this problem.
Im using google form on my job to help my team mates to simulate some jobs and im using forms to make it easier without using the sheet in itself. Im using one page for the form and one page for the calculations based on the replies from that form.
The problem, as you know it, everytime I complete a form it makes a new row, and it doenst go to my calculation page. It jumps ahead 1 row.
Any suggestion on how I can make it block the jumping row?
I apologise if I am not understanding your problem fully, but I think you mean you're trying to add a calculated column in Google Sheets based on responses in Google Forms?
Let's say, for example, on the form there is a question for length and a question for width and you want Sheets to automatically calculate the area by multiplying the values in the Responses sheet.
You can't drag the formula down the column because when a new response is submitted in Google Forms, Google Sheets adds it as a new row, and the formula is not included.
You've done the right thing by having a separate sheet that deals with calculations but you should use an Array Formula that will refer to the whole column of the Responses sheet, and it would need an IF statement to account for the first row, which has the headers.
I think this video explains everything better than I could:
https://www.youtube.com/watch?v=0v-hQ3EecdE
I want to calculate and display the average scroll depth in Data Studio from analytics.
I’m looking to get an average scroll depth in Studio. I’ve got the 10%,25%, etc scroll depth data coming in, but I now need to be able to calculate the average scroll % from this data.
To calculate the average scroll depth:
multiply the scrolled threshold by the number of events (10x500) + (20x400) + (30x475) +(40x300) + (50x200) + (60x100) +(70x75) +(80x60) + (90x20) + (100x10)
Then, take that total divided by the total number of events. 500 + 400 + 475... etc
Because I can’t reference cells in Studio I can’t get it to work. I’ve also tried Google Sheets, which does work to do the calculation, but then I can’t use Data Studios filter to provide a specific page path?
I'm thinking that perhaps the calculation will need to be done at data source, but I am not sure how to reference a 'cell'?
Data Studio doesn't work based on a concept of "cells", it works based on a concept of "fields"—which are basically properties of the data source. Similarly, you don't have "formulas" per se, but rather "calculated fields". These fields can be created either at the chart-level (single-use, but doesn't require permissions to modify the data source) or in the data source (reusable across many charts, requires permissions to modify the data source). Most fields also have an aggregation type, which tells the report how to aggregate it in charts by default (e.g. Sum or Average).
When you either edit your data source and hit "Add Field" or the option with the same name under the "Add metric" or "Add dimension" menus on a chart, you'll be presented with a box to input the formula. To access a field, just type its name (of if you're in the data source, select it from the list on the left). The editor will also typically give you an auto-complete list below your cursor based on what you're typing. Once your entry matches a field, it will get a highlight box around it (the color is based on the type; green = dimension/string,blue = metric/number). The functions available are sort of a mash-up of something between what you'd expect in Google Sheets and in a SQL query, but with more constraints on when you're allowed to use certain functions.
The documentation for calculated fields is pretty simple, so I'd recommend starting there before you try to do too much heavy-lifting in Data Studio. Because of constraints in Data Studio's data model, you'll often find that you need to create separate calculated fields for different parts of the formula, and then combine them in a new calculated field. I'll warn you that the error messages in the field editor aren't super helpful sometimes, so you may need to re-read the documentation for the functions and field types you're working with to ensure you get a valid result.
If you're running into problems, including the field names and values that you need in your calculation may help, including the source of the data (are these GA events?). The more details you give, including what you've already tried, the more helpful we can be. Also, make sure to read the docs first to make sure you have a good handle on the product you're using and the terminology the community is most likely to understand.
I'm having a tough time with Google Analytics, trying to understand why the value of metrics changes when segments are applied.
There is a standard audience overview report, which is based on 100% of sessions (no sampling) and the view is not filtered. The period is March of 2017.
Standard "All visitors" segment looks like this:
Then, there is another built-in segment called "Bounced Sessions". When I apply this segment, the "All visitors" values changes:
Amount of users increases, but the count of pageviews decreases.
Any ideas how to explain this?.. Thank you in advance!
Oki, there can be, multiple reasons. Let me explain first how these numbers are calculated, then we move on to your query.
There two types of data gathering and manipulation from google.
Pre-calculated data -- pre-aggregated tables
These are the precalculated data that Google uses to speed up the UI. Google does not specify when this is done but it can be at any point of the time. These are known as pre-aggregated tables
Data calculated on the fly
Some that you do which result in computation or manipulation falls under this category. Like using segments, creating custom reports etc.
Coming to your problem. When you apply segment, every metric that it effects will be calculated again. Thus it may result in numbers greater than you see in normal view.
Standard audience overview report is pre-aggregated at some point of the day. When you apply segment, the results will be calculated with the fresh data. Since latter is the latest, it will automatically give you increased number of the metrics. Even you can see a decrease as well, all depends on your data and user behavior.
Resolution: If you are a premium user, use Big Query. You must rely on big query for every metric as they are fresh and calculated on the fly
I'm building a cube with 2 fact tables that share some dimensions.
In the example below, I have Fact_Employee, Fact_Manager, Dim_Date, Dim_Country, Dim_Employee and Dim_Manager, with the respective links.
In SSAS I've created one Dim_Country. In the Cube "Dimension Usage" I am creating 2 dimensions (Man_Country and Emp_Country) and linking to the respective measure groups.
My Fact_Employee has the key for the Dim_Manager, so I can relate them.
My problem here is, when in the pivot table I drag the Man_Country, Emp_Country, Emp_Amount and Man_Amount, this doesn't work because I'm getting the list of all Manager Countries not related to the Manager Number and then the Employee Countries are correctly linked to the Employee Number, but are duplicate.
The below image shows the result Pivot table and what I am trying to get.
What do I need to change in the data source view or cube dimension usage to have the correct results.
The users should be able to filter the pivot by, for example, Manager Country to see all the employee Countries and Numbers and the amounts (for Managers and Employees).
Many thanks in advance for any help.
Regards,
PC
If you have country dimension then you should use this dimension for both measure groups, just remember to configure dimension usage for this dimension vs both measure groups.
There are special cases where you would want to separate those dimensions, f.eks:if you want them to act separately - let say you have a fact table with parcels and you need to have both DimFromCountry and DimToCountry. In this case you would want to use role playing dimension - it is same dimension then, but connected differently.
I've got metrics in Graphite showing response time for various organizations. The list of organizations can change on the fly. I want panels in Grafana to appear for any origanization who's response time is over a certain threshold. Was thinking the Singlestat panels was the right panel to use. Question is how to make them appear dynamically? Is a scripted dashboard the right approach?
If a scripted dashboard is the correct solution, can anyone recommend a Grafana cloud/service provider that supports scripted dashboards? The current one I have been testing out does not support scripts. Note that I am not really tied to Graphite as the backend since this project is in proof of concept phase. Just need the backend to also be a service. Don't want to roll the backend myself. Thanks.
As far as I know, it is not possible right now.
We had a similar use case in my organisation, and here is what we did.
You can define a template variable for your organizations, and then use SingleStat panel with “Repeat Panel” on this variable, but that will display panels for all of your organizations. Filtering based on a criteria is a requested feature.
Alternatively, you can use the Table panel for your use case.
Choose Table panel
In “Metrics”, enter your metric organizations.*.response_time (or whatever more complicated you need, applyByNode can be handy for such cases)
In “Options”
“To Table Transform”: choose “Time Series aggregations”
“Columns”: Avg, or Current (depending on your needs)
“Coloring”: use thresholds to paint in red or something anything above your desired response-time threshold.
Sort the Table per the Number column.
Ta-da! Your organisations needing attention will be at the top of the table and highlighted.
In the lack of true filtering, this worked for us. Hope it will work for you too :)