What is Tableau Data Extracts?

What is Tableau Data Extracts?

Tableau Data Extract (TDE) is a compressed screenshot of the data, saved on disk and uploaded into memory as needed for making Tableau. There are two important things in TDE Design, which make them perfect for using analytics and finding...

Tableau Data Extract (TDE) is a compressed screenshot of the data, saved on disk and uploaded into memory as needed for making Tableau. There are two important things in TDE Design, which make them perfect for using analytics and finding information.

The first one is that a TDE is a columnar store. Columnar databases save column values collectively, instead of row values. By this, it reduces the input or output greatly that is required to use, and collect the values in a column. This is the reason it is best suited for analytics, and finding information.

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The second important thing is the design of the Tableau Data Extract, which means the organization of the data, this affects the procedure of the memory loaded and applied by Tableau.

TDEs are ‘Architecture aware’ which means TDE uses all components of our computer’s memory, from RAM to hard disk and arranges every part to work according to its characteristics.

How Tableau Data Extract is created?
For creating a data extract, the first it specifies the TDE structure and designs different files for every column in the server.
After collecting the information, it classifies and compresses and adds the values for every column to their related file.
To finish the TDE creation, single column files are merged together with metadata to make a memory-mapped file or a single file that has many individual memory-mapped files, as columns are present in the controlling data source.
When Tableau requests information from a TDE, as Tableau Data Extraction is a memory-mapped file, OS loads the information directly into memory. There is no need to open, process or decompress the TDE to use it.

Why we use Tableau Data Extract?

Performance

Data Extraction increases the performance, not only when the hidden data sources are not taken. But, it also can increase the performance speed even when we use CustomSQL that slows down the speed.

Reduced load

Because of the high user traffic, there is a heavy load on the database. This load is reduced when we replace a live connection, to an OLTP server or any database with a TDE.

Portability

We can attach a TDE with visualizations inside a packaged workbook so that we can share and work together easily.

Pre-aggregations

Before designing the TDE, it provides us a choice of gathering all our information from various visible angles. This process is called as Aggregated Extract.

The aggregated extract is very small and has only gathered information, as per the name. It doesn’t contain any row-level information, which is saved in a normal TDE.

Getting the values for extra gatherings in visualization is easy and instant, as the work to get the values has already completed. So, the main reason for using aggregated extract is performance.

We can also select gatherings up to the selected level like a month, quarter, year, etc. of any one of the data fields that are hidden data sources.

This leads to the reduction in the extract size by decreasing the number of aggregate values saved in the extract, and for that specific level of gathering, it increases performance.

The materialization of Calculated fields

When we try to improve the extract, all estimated fields which are specified are converted to fixed values, when we refresh completely.

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At that time, they act as extra data fields, that can be accessed and collected as fast as any other field in TDE. As string calculations are slower compared to numeric and date estimations. So, the performance increases when working with string calculations.

Publishing to Tableau Public and Online

TDEs are the most commonly used data source, in Tableau environment. Tableau public only supports TDEs, whereas Tableau Online can link actively with cloud-based sources.

Support for functionality not available when using MS Jet

MS Jet engine is used by Versions 8.1 and previous versions of Tableau for using Excel, text files and MS Access. By designing an extract, some specific features are not supported by Jet like count distinct.

In version 8.2, it replaced MS Jet for using Excel and text files with a fresh, more effective and functional engine.

I hope now you got a better understanding of What is Tableau Data Extracts, and why we need to use them. Follow my articles, to get more updates on Tableau Technology.

Tableau Desktop Inside Tableau Server

Is there a Tableau Desktop executable inside the Tableau server installation.

Is there a Tableau Desktop executable inside the Tableau server installation.

I have a system where Tableau server in Cloud and would want to use Tableau Desktop in the same server? Is that feasible?

Tableau Desktop client has to talk to Tableau server

Tableau architecture shows that Desktop connects to tableau server (using gateway) and then to data server which are on tableau server. My question is do tableau client has to talk to tableau server? Can't I just install tableau desktop and connect to required database (even hosted on cloud)?

Tableau architecture shows that Desktop connects to tableau server (using gateway) and then to data server which are on tableau server. My question is do tableau client has to talk to tableau server? Can't I just install tableau desktop and connect to required database (even hosted on cloud)?

Regards, G.

Table Calculations in Tableau | Tableau Table Calculations Tutorial

Table Calculations in Tableau | Tableau Table Calculations Tutorial

The main aim of this tutorial on "Table Calculations in Tableau" is to help enable you to utilize Tableau to query your data, not only for engagement but also comprehension efficiency. You'll learn: What are Table Calculations in Tableau? Fundamentals of Table Calculations, How does Computation work in Table Calculations? To Build, Edit & Remove Table Calculations in Tableau

Great visualisation is achieved when we enable our audience to gain the maximum amount of insight with the least amount of effort. The main aim of this tutorial on "Table Calculations in Tableau" is to help enable you to utilize Tableau to query your data, not only for engagement but also comprehension efficiency. Following are the topics in this tutorial:

  • What are Table Calculations in Tableau?
  • Fundamentals of Table Calculations
  • How does Computation work in Table Calculations?
  • To Build, Edit & Remove Table Calculations in Tableau