Data is at the heart of every decision, no matter your industry. Platforms need to crunch all that data into actionable insights. One common way to analyze large amounts of unstructured data is through Tableau Hadoop. Tableau has recently released an integration with Hadoop, making it easy for anyone to explore their big data using Tableau tools.
Using Tableau’s Hadoop Integration to Analyze Big Data
A data warehouse collects all your business’s historical data in its original form. This helps you analyze the data using SQL queries and other tools. Still, it can be difficult to access large amounts of big unstructured data like social media messages, videos, or logs.
Tableau’s Hadoop integration allows you to use MapReduce to analyze this data type. MapReduce is an open-source tool for processing vast amounts of big unstructured data by splitting it into smaller parts that can then be processed independently.
Hive is another open-source tool that allows users to query large datasets stored on Hadoop HDFS in familiar SQL syntax instead of learning new languages like Pig or HiveQL.
Benefits of Integrating Tableau with Hadoop
Tableau Hadoop integration is a powerful tool that allows you to analyze big data in real-time. Tableau’s Hadoop integration is easy to use, allowing users of all levels of experience to access their data from diverse sources. Additionally, it will enable users to create interactive dashboards that are easy for anyone in your organization to understand and use.
The benefits of integrating Tableau with Hadoop include the following:
- Comparing large volumes of unstructured information can be done more quickly and efficiently than ever before.
- Allowing you access to the latest technology while still keeping costs low by using existing infrastructure.
Data Preparation via Virtualization
Data virtualization integrates data from multiple sources using an abstraction layer. Data virtualization can be used to prepare data for analysis, and it can also be used to prepare data for Hadoop.
Hadoop is a popular big data processing platform that uses MapReduce (a parallel programming framework) and HDFS (a distributed file system). Many organizations use it because it’s easy to use, scalable, reliable, fault-tolerant, and inexpensive—but not all organizations have the resources or expertise necessary to set up their Hadoop cluster.
Analysis of Relational and Non-Relational Data
Tableau helps you analyze relational and non-relational data. It is an excellent tool for performing exploratory analysis on big data, visualizing it, and performing predictive modeling.
Several tables and their relationships can represent relational data. You can use the Tableau connector for Hadoop to connect with Hive or Impala databases to access the relational data that resides in them.
Non-relational data refers to unstructured or semi-structured data, such as images, audio files or documents, etc., which cannot be easily captured into a traditional table format with rows and columns. You can use the Tableau connector for Hadoop to connect with Pig or Spark programs/scripts that read from various sources, including HDFS (Hadoop Distributed File System) using text files and JSON files (JavaScript Object Notation).
An In-Depth Look at the Tableau Prep Hadoop Integration
Tableau Prep is a data preparation tool that allows you to prepare your data for use in Tableau Desktop. Many organizations use it to connect to Hadoop and other data sources as part of their ETL (Extract, Transform, Load) processes. Tableau prep can be used to prepare data for use in Tableau by:
- Designing the source system for MapReduce execution on Hadoop
- Transforming raw data into views that Tableau understands
- Performing denormalization or aggregation operations
Conclusion
What started as a simple data analysis tool has evolved into a powerful analytics solution that can handle even some of the most complex data sets. Tableau Hadoop integration makes this possible through its ability to perform advanced analytics on big data. This blog post gives you an overview of how Tableau works with Hadoop, its benefits over traditional methods, and why businesses consider it so valuable today.
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