Using IBM Bluemix I created an app, a Cloudant NoSQL DB, a dashDB and an Embeddable Reporting service. In dashDB I created a table with a couple of columns and some simple data. Next I configured the Embeddable Reporting service and pointed it to the Cloudant DB for its own storage and dashDB for reporting data. Next I open Report Studio and create a chart mapping in some data:
When I play the report page, I get an indication that I have not supplied data:
However if I create a different report and ask for a List ...
The list appears just fine ...
I am at a loss to understand why my chart will not appear but my list will. I will be happy to amend and update my question with any relevant information anyone may need.
Imagine a vertical column chart. Now imagine data of the form:
Dallas 10
New York 30
San Francisco 50
We can easily imagine the cities on the X-Axis and the values on the Y-Axis. This is easy enough. But now imagine that our X-Axis rows in our data are not unique ... for example:
West-Region 10
East-Region 30
West-Region 20
What then should the "value" of the West-Region column be? The column names should be unique and hence we can't have two columns with the same name. Should the value of the West-Region be 30 (the sum) or 15 (the average) or something else?
And that is where the problem comes in. When we define a column in a chart, there is no defined Aggregate Function. What we need to do is define how we want values to be aggregated together. If we select the column and select its properties, we can find an Aggregate Function option. We can choose a function such as Average.
Once defined, the chart will show up correctly because it can now properly handle aggregation. Now, this might seem strange especially if we know for certain that there is never a need for aggregation because values are unique ... but apparently, these are the rules (for better or worse) and, once set, charts now show:
Related
Does anyone know if I can add two rows together so that I end up with just one row in Tableau (see screenshot)? So, if both rows are city Aachen and one row has a value for cost but not for purchasing power and the other row has a value for purchasing power but not cost, I would want just one row with both values. I am not interested in the columns "Table Name" and "Document Index(...". Thankful for any help!
Manipulating data like that in Tableau is usually no-go. Nevertheless, you can try Tableau prep and you should be able to do what you need here. Or maybe a different tool (even excel).
With that said, even though you have the info in two rows, the default approach for Tableau is always to aggregate data, so even if you have many rows with similar cases, once you take it to a viz using City (for example) as a dimension, this issue shouldn't really matter.
I am creating an interactive 'calculator' using tableau. I have a series of dataframes that I have crossed with one another, such that the resulting dataframe is every possible combination between the tables, and every row is unique.
Each column is its own worksheet as a table. Each table in the dashboard is a pane. So, here we have a series of tables with selectable units of measurement, and the final pane on the dashboard should filter to the cell for its respective column, on the unique row of the dataset that the user has selected and 'filtered out'.
I'm having some issues getting this to work and not sure why.
The closest I can think to solving this would be 'Cascading Filters.' Here are a couple resources:
General Use
In dashboard action-filter form
The critical piece, however, is that the filters must be selected in a specific order - therefore making them 'cascading.' This may differ from your presumed concept of clicking/filtering in any order on the worksheets to then arrive to a final answer. I do think that this may be a limitation of Tableau - I don't think that a 'many to many' type of relationship can be set up within Action Filters.
I have an issue that I have been trying to solve for the better part of a week now. I have a large database (in Google sheets) representing casestudies. I have some columns with multiple categories listed (in this example 'species', 'genera', and 'morphologies'), and I want to be able to tally how many times each category occurs in the data set.
I use Tableau to visalise the data, and the final output will be a large publc tableau. I know I can do a "find" based on the specific string, but I'd like the dataset to be dynamic and be able to handle new data being added without having to update calculated fields? Is there a way of finding uniqe terms (either from a single column of comma separated values, or from multiple columns), and tallying them?
Things I have tried so far:
1 - A pivot table in Tableau. Works well, but messes with all the other data, since it repeats lines.
2 - A pivot table on its own data source in Tableau. Also works well, and avoids the problem of messing with the other data. However, now each figure is disconnected from the others so I can't do a large dashboard where everything is filtered by each other (ie filtering species and genera by country at the same time).
3 - An SQL query() in google sheets, which finds all unique terms and queries them, which can then be plotted in Tableau. Also works well, but similar problem of the data being disconnected from all the other terms in the dataset.
Any ideas of a field calculation that will find, list and tally unique terms in a single comma separated column (or across multiple columns), without changing the data structure?
I have placed a sample data set here (google sheets), which is a smaller version of what I'm actually working on. In it I have marked comma separated columns in grey, and they're followed by a bunch of columns with the values split into columns. I only need to analyse either of those (ie either a calculation to separate comma separate values or from multiple columns).
I've also added a sample Tableau workbook here.
I need to create a dashboard to be used in a control room, where a bunch of operators will need to monitor the number of tasks assigned to other employees (among other aspects).
Source data will be coming from a RDBMs (PostgreSQL, in this case). We have people with assigned and numbered tasks that also have a status, and the DB data is like this (purely fictional: but it resembles the real one)
Having to create and mantain a dashboard i was thinking to use tools like Grafana, Kibana or similars, to plot something like this
The problem is that Grafana, for example, doesn't let me use alphabetical values for the x-axis. It only allow numeric values, while i've names to plot (Mark, Luke, Brian).
Is there a best practice than i can follow? Am i trying to use the wrong tools?
Actually solution is easier then you think although it also took me some time to figure it out. I will place here an example for some unspecified shop data grouped over countries - you just need to change it for your task. Example was tested on Grafana 5.0.3
PostgreSQL query for metrics
SELECT
$__time( partition_date ),
country as metric,
sum(value) as value
FROM
aggregations.my_data_for_dashboard
WHERE
shop = 'myshopname' AND
$__timeFilter(partition_date )
group by 1, 2
Grafana will show usual metrics:
In "Axes" tab look at "X-Axis" section, item "Mode" - switch "Time" to "Series" and Grafana will show bar chart for countries.
What is the best way to store metrics data used in displaying graphs?
Currently I have a table analytics(domain::text, interval_in_days::int, grouping::text, metric::text, type::text, labels[], data[], summary::json)
domain is the overall category of the metrics. Like what part of the application they're under. Could be sales or support etc.
the interval_in_days and grouping are 'view options' the end user can specify at the interface level to have a different view of the data points.
grouping can be date, day_of_week or time_of_day
interval_in_days can be 7, 30 or 90
labels is an array of the labels on the x-axis and data are the corresponding datapoints.
type is either data_series or summary. If data series, the row represent's the data used for drawing the graph, while a summary has the summary:json field populated with an object like {total_number_of_X: 132, median_X: 320.. etc}
metric is simply the metric the corresponding graph represents, so there's a separate graph for each value of metric
From this it follows that for each metric/graph I display, I have 9 (3 intervals * 3 groupings). For each domain I have a single row with type summary.
Every few hours I aggregate a lot of data across multiple tables into the analytics table. So I don't have to perform expensive queries adhoc.
I feel this is not the optimal approach, so I'm really interested in seeing how other people accomplishes the same task or any suggestions.
There is nothing wrong with storing 9 rows of raw data and later aggregating them to something more comfortable. It's a common approach and has performance benefits in some situations.
What I would really re-think in your design are the datatypes. From your description it seems you can transform all ::text fields into something like ::varchar(20). Then you can use STORAGE PLAIN on these columns and your table will become more efficient.
Also, consider adding foreign keys to describe what is stored in individual columns. For example, you stated grouping can be date, day_of_week or time_of_day, so you could have a groupings table that will list these options. But again, the foreign key would have to be covered by an index, so you may want to skip on that due to performance reasons.