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Tableau is an excellent way to visualize and analyze your data. You can use it for many purposes, including analyzing large amounts of data to gain insights about your business and its customers.
If you have access to Hadoop, you can use Tableau alongside Hadoop to get more value from your data. This article explains how using Tableau on Hadoop can help you get more out of your data set using tools together and separately.
Tableau works with Hive and Drill, and many other Hadoop components
Tableau helps you leverage your Hadoop data with several other tools, including Hive and Drill. Using its powerful analytical capabilities, you can use Tableau to analyze the results from these tools.
In addition, it works with Hadoop components that are not in the data warehouse, such as MapReduce, so you can get more value out of your Hadoop infrastructure.
Integration with the entire BI stack is important
For example, you can integrate Tableau with the full BI stack. If your organization has a data warehouse and analytics platforms like Oracle Data Integrator (ODI) or Greenplum Analytics, you may use Hadoop as an input layer in your ETL process.
By integrating Tableau with these platforms and other tools like Spark SQL and HiveQL, you’ll have complete data processing capabilities without buying additional software.
How does Tableau enhance Hadoop?
Tableau is a leading self-service analytics platform in the world. It helps you gain insight into your data and make better decisions faster.
With more than 170,000 customers and 1.5 million people using Tableau every month, this tool is used by more than 100,000 organizations worldwide to transform how they create customer experiences through visual analysis of their business intelligence (BI) data sources.
Tableau provides a visual interface to Hadoop, which makes it easy for users to connect data from Hadoop or HDFS. It can connect to Hadoop or HDFS, Hive, and SQL.
It also supports Hive integration with Amazon Redshift, a managed hosted database service that makes it easy to analyze your data in real-time. Tableau helps Athena, so you can use its query capabilities when working with large datasets and complex queries involving multiple sources.
A tableau is a great tool for visualizing and analyzing big data. You can use it to figure out what’s going on in your data, which will help you make informed decisions about how it should be used. It is also useful for working with Hadoop data because it allows us to manipulate our big files (more than 1 TB) without losing important information like timestamps or column names.
The Data Engine is the core of Tableau. It is a collection of real-time tools used to perform data analysis and visualization. The Data Engine has its engine, which means it can quickly process large volumes of data.
Still, it does not support external sources like Hadoop or HiveQL (the query language used by the Apache Foundation). However, you can connect your Tableau server with HiveQL using the built-in connector feature in Tableau Desktop 10.1 or higher and get results into your workbook without having to write any code yourself!
Conclusion
Using Tableau on Hadoop has strong space and is worth paying attention to. With Tableau’s ability to connect Excel and other tools with Hadoop, companies can start thinking about how they want their data to be visualized and analyzed. The next step is for more organizations to invest in these tools so they can get started on their journey toward becoming data-driven companies.
