How To Hacking Cross-database Unions In Tableau Services In Saudi Arabia?

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Bilytica # 1 is one of the top Tableau Services In Saudi Arabia One of our clients required an executive-level, company-wide dashboard to examine indicators for the last two fiscal years across all business divisions. The dashboard itself was straightforward, but finding, structuring, and collecting all of the data was a difficult. The company is divided into three distinct business areas, with data stored in four separate databases. To make matters even more complicated, data from one business unit was stored in two of these databases. We also wanted to incorporate predicted figures as well as other historical data from a Google document. Tableau does not allow cross-database unions, which is a problem.

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Build A Union Using Cross-Database Join

Although Tableau does not offer cross-database unions, it does support cross-database joins for practically all data sources, which we used to create a union. We used a cross join, also known as a cartesian join, to hack a cross-database union. To get started, we required a scaffold data source to act as the left side of our cross join, including keys from each data source. We could utilize the Google Sheets prediction data as the scaffold data source in our scenario because it had data from all three business divisions as well as the required essential fields. The end result was a table on the left side of the join that had prediction data from three Google sheets that had been joined together Tableau Services In Saudi Arabia. The right side was made up of five different joins based on business unit and date from historical data sources.

We were able to get all of the required rows from a single data source using this cross join. Because the cross join yields null values in a third of the cells, the next step was to create consolidated fields for the dashboard. This consolidation procedure was made more difficult by the fact that we had to weight measurements on a regular basis and do ratio computations between them. Depending on the metrics involved, each data source included between five and 10 original columns, for a total of 48 columns. After completing all computations, we had a total of 193 columns. We constructed the custom SQL queries to provide us only three rows of data every day (one per BU) because this was a high-level dashboard, thus speed was not an issue.

Steps Of Cross-Database Union In Tableau

A simple sample of one day of records in the final data source is shown below. For the sake of simplicity, I simply included one metric. We didn't consolidate the BU and Date columns from the forecast data source because they were present on every row Tableau Services In Saudi Arabia. For this job, we merely needed to combine measurements. I'll utilize Sample Superstore data to demonstrate how this works in detail. I divided the data into two files, one containing data from the East and West areas and the other containing data from the Central and South. Make an excel file with one column labelled "Key" and two rows labelled "1" and "2." Simply keep adding rows with unique values if you need to combine more data sources.

Connect each of your data sources in Tableau. Then, as the left side of your joins, pull out your scaffold data source first. Then, using the Key field from the scaffold and a join calculation with "1" as the value, create a left join with one of your "actual" data sources. The field "Create Join Calculation" appears at the bottom of your field list. If you set the data source view to "Manage Metadata" and sort by A to Z ascending, you'll see that each data source has one of each field. Our two data sources that were nearby to each other were connected using the cross join. Where columns from one data source overlap into the other, there is a null in every cell. You can see where the two data sources overlap if you show all 9994 rows in the data source and scroll down to the end of the first table. Following this, every cell in the first set of columns is null, while the second set is filled with data.

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Consolidated Fields That Are Created

We now have all of the data in one database, but no columns containing data from all of the areas. Then, for our dashboard, we add consolidated fields Tableau Services In Saudi Arabia. We can achieve this in a number different methods, but for this lesson, I'm simply going to combine a few fields: Region, Date, and Sales. This is the simplest option, in which each field is evaluated to see if it is null, and if it is, another field is used. If you're merging more than two data sources, you can nest several IFNULLs. By showing the amount of records, we can notice the difference between the old region columns and the new one. Only values from their own data sets are used in the original fields.

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Tableau Services in Saudi Arabia
Tableau Services in Saudi Arabia
Tableau Services in Saudi Arabia
Tableau Services in Saudi Arabia

11/03/2022