I have a datset of .7 million records for a month and I built a tableau report having 60 plus attributes and .7 million records. The report is taking huge time to open in tbaleau server and same as tableau desktop. Now I want to build a self service dashboard where user can have capability to add or remove the fields and prepare the report as per the need. Can you please guide me how and what steps to follow to build the tableau report?
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I am trying to come up with a FIXED LOD calculation that labels if a [customer] (string field) stopped reporting. To do this, I want to count instances by month, using Month of [Purchasedate] in the columns shelf. I want the rows to state one of the following and count all instances that a [customer] falls in each month: "No Sales Previous Month - Existing Reporter", "No Sales Previous Month - New Reporter", or "Reported Sales in Previous Month".
I've tried a bunch of different calculations and am not getting the results that I expect. Any help writing this formula, if it is possible, would be greatly appreciated.
Hi Ken,
You may want to create a FIXED LOD to identify whether a customer had sales in the previous month, then use that result in a classification calculation.
For example, you could first calculate the customer’s previous reporting month:
{ FIXED [Customer] : MAX(DATETRUNC('month',[PurchaseDate])) }
Then compare it to the current month in a separate calculation to determine whether they are:
- Existing Reporter
- New Reporter
- Stopped Reporting
You may also need a table calculation such as LOOKUP() if you want to compare month-over-month activity dynamically in the view.
The combination of FIXED LOD + LOOKUP usually works well for this type of retention/churn analysis.
Since few days, i can't refresh datasource extract from the connector Sharepoint List JDBC
Here is the message i have :
"Tableau received an OAuth error from your request. Please see the error message for more information: Required attribute: instanceurl is either missing or null.. (errorCode=170006)"
i'm unable to embed credential to run the extract. Everything is working fine on Tableau desktop but not when it's published online.
Hi,
It looks like the OAuth configuration for the SharePoint connector may be incomplete on Tableau Online.
Since it works on Tableau Desktop but fails after publishing, you could try re-authenticating the SharePoint connection directly in Tableau Online and republishing the datasource with embedded credentials enabled.
Also check whether the instanceurl parameter is correctly configured in the connector settings.
Hope this helps!
I would like to create a professional looking isopotential plot. I have created the maths in Mathcad but their graphics leaves a lot to be desired. I have produced a nice contour plot using Grapher software, but I do not want to buy an expensive licence just to produce a nice contour plot. I can produce all the data in a Matrix in Excel and import it to Tableau easily. Attached is the Grapher plot. Grateful for any guidance. Thanks.
Hello @Ken Lax, I suspect that a bug prevents me from seeing your target visual, as I am presented with the text "[image: image.png]". I think it will be possible to do with Tableau, but maybe you can send the image again? I can't help you further at the moment because of this. Cheers, Roland
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https://usergroups.tableau.com/events/details/tableau-analytics-tableau-user-group-presents-analytics-tableau-user-group-map-layers-web-objects-trusted-viz-extensions/Hi - I've created a Pareto table that uses running sum % (of sales) to split my category information (Title) into 80/20 buckets. It works fine except for one thing: I'm not able to aggregate the sales data into just two lines (the Top 80% and All Other buckets). No matter what I do the sales data stays disaggregated at the Title level. Any suggestions?
@Joel Acker well you've a great job on the pareto but the issue is the use of table calc's, which provide a displayed value, not a real value to work with going forward. And, in this case due to use of running sum requires the detail to be in the view as rows
. It becomes extremely difficult to aggregate thereafter as a 'total'. Even if you were able to change the Pareto calc to be a measure, something along the lines of:
80% Pareto Bucket
WINDOW_SUM(IF [Running Sum %] <= FLOAT([Top N %])
THEN SUM([Sales])
END)
That would break out the 80 vs 20, but it would still require the title to be in the detail. Of which, any changes to Title would be cause for the above calc to break. Closest you'd get with this in Tableau would be something like:
...and Grand Totals won't work here. These are limitations of Table Calc's that involve use and rely upon other table calc's such as Running_Sum(). That said, I'd suggest a workaround of using Tableau Prep to 'assign' whether a value falls into the appropriate bucket so that in turn you could easily aggregate the results.
For example in Tableau Prep, a running sum can be handled at the row level:
Add in the other calc's to determine 80 / 20 sorted on Data Source order:
The Output of that is then used in Desktop, with a slight variance in the sales by 80/20 but the ratio's being virtually same:
That would be a better approach. Attaching the packaged flow as example.
Building a dashboard on quality events that occur at 70+ sites, need to stabilize the denominator of total number of trays per day to achieve error rate (# of quality events/trays processed). I do have access to Tableau prep to join the tables, but I cannot build relationships since all tables are published into a server.
There is one data source, Quality Table, that (usually) has multiple rows per site per day. The data is collected when a Quality Event is uploaded to the system, there are multiple types of Quality Events, which is captured in the quality event field. It is possible, however, that a site may have no quality events occur in a day, in which case there would not be any rows in this table for that site. There are also categories in the Quality Event field, some of them start with IA:, ORF:, IF:, and VF:. These are important distinctions that tell you were a quality event was found (Internal Audit, OR Finding, Internal Finding, Vendor Finding). Each category can have a wide variety of quality events (Missing label, bioburden, etc.). This data must be put into a dashboard to show trends, areas of focus, and overall performance to compare different sites, both by Quality event category and the specific type of Quality event. There is a "tally" field that counts 1 quality event per row, which I have aggregated in Tableau prep so each row is a unique record of number of events per each site, date, and quality event combination. (EX: Site 1 on 1/23 had QE1 occur 23 times, and Site 1 on 1/23 had QE2 occur 12 times are 2 different rows).
There is another data source, Sterilization table, that has one row per site per day. Each site will have a number of trays processed from this table, as each site processes trays every day, regardless of if a quality event occurs or not. I want to join these tables together, because we would like to use trays processed as a denominator to get the error rate overall, as well as for each type of Quality event. However, joining these tables in tableau prep leads to there being overinflated trays sterilized, since the number will repeat for each row in the quality table. We need to keep in mind the fact that rows may be missing from the quality table for some sites on some dates.
The desired views are a bar chart ranking most common quality event by event count, while also showing the error rate. We would also like to create a timeline of error rate, all of which can be filtered by site, date, and quality event type. The denominator, trays processed, should not change unless site or date is filtered. It should be the same number across all quality event types. See below for a draft dashboard screenshot.
I keep running into errors no matter what I try. The closest I've gotten is using a WINDOWS_MAX(AVG(trays processed)) calculation, which is not foolproof as I would also like to see grand totals.