Tableau Architecture Explanation

Tableau provides a scalable solution for the delivery and creation of web, mobile and desktop analytics.

Tableau Server is an analytics platform that is used to level up thousands of clients. Tableau Server presents a robust mobile and browser-based analytics and workings among a company’s presented security protocols and data strategy.

Now, we will do in-depth of each layer managing the architecture of Tableau Server:

Data Layer

One of the primary features of the Tableau is that it supports the user’s choice of data architecture. It does not need any data to be stocked in any single system or proprietary. Almost all organizations have a heterogeneous data environment where the data resides in a database or Cube, and flat files like Excel are still very much in use. One does not need to get the entire data in the memory until and unless it one select to choose. If your existing data environments are fast and scalable, then it allows you to directly control your investment by using the power of the database to response problems. If this is not the case, then it provides simple options to improve your data to be fast and responsive.

 

Data Connectors

It consists of many optimized data connectors for databases. It also supports some common connectors which are designed for the systems commonly known as ODBC connector. It operates without the intervention of a native connector. It further offers two modes of interaction with the data: Live connection or In-memory. The users can switch anytime between live and in-memory connection as per their need and requirement.

 

Live connection

Data connectors of Tableau regulate your available data groundwork by transferring MDX statements or dynamic SQL directly to the database rather than importing every single piece of data. If you have provided the data in a fast and optimized database unlike ‘Vertica’, then you get the advantages of connecting live to your data. This leaves the detail information in the source system and sends the aggregate result of a query to Tableau. In a nutshell, this means that the Tableau can effectively utilize tremendous amounts of data. Therefore, Tableau is considered as the most massive front-end analytics databases in the world. It has optimized each connector to receive the advantage of the unique characteristics of every single data source.

In-memory

Tableau offers a fast, in-memory Data Engine to optimize data analytics. You can directly connect with your data and with one click, you can get access in Tableau’s ‘in-memory’. Tableau’s Data Engine fully acquires your entire system to manage fast queries replies on millions of rows of data on commodity hardware. Since the Data Engine can use disk storage as well as cache memory and RAM, it is not limited to the quantity of memory on a system. However, this is not mandatory that an entire data set will be loaded into the memory to achieve its performance objectives.

Pin It on Pinterest

Share This