Denodo Architecture - A Complete Guide

Denodo simplifies work by providing a unified data view for all business apps. Denodo also provides a comprehensive view of corporate data by combining core master data from MDM (master data management) with real-time data from a variety of sources, such as Salesforce and internet applications. To comprehend more about Denodo architecture, read this blog till end.

Denodo, the data virtualisation tool, emphasises the importance of integrating intellectual business data. It gives multiple business applications an uniform view of data. It also helps to ensure that governance standards and laws are followed throughout the data supply chain. This blog introduces Denodo architecture, covering all of the fundamentals.

Denodo Architecture - Table Of Content

Key Components of Denodo Architecture

To illustrate the entire workflow and the components employed. The architecture of Dendodo and its components will be explained in this section.

Denodo is a data virtualisation technology that works in three steps:

  • Connect
  • Combine
  • Consume 

These three components work together to provide business users with a comprehensive picture of corporate data from the underlying source systems. 

Denodo's data virtualisation software may link to a variety of data sources. Databases, data warehouses, cloud apps, big data repositories, and even excel files can be used as data sources. The platform also merges linked data into business views regardless of their data types, such as relational databases, no SQL, Hadoop, Web Services, Cloud APIs (application programming interfaces), and files, in the data virtualisation process. Thanks to data virtualisation, business users may consume data through reports, dashboards, portals, mobile apps, and web apps thanks to data virtualisation.

The consumer layer provides a single point of contact and access to the fundamental data sources and abstracted data views in a uniform delivery style. The consumer layer provides JDBC, ODBC, ADO.Net, SOAP web services, RESTful API services, and data widgets to meet the demands of business users.

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Denodo is a unified, virtual data layer that enables corporate applications and users to access any enterprise data, independent of its location, format, or protocol, using the techniques that best fit their needs, such as data discovery and search.

Industry-leading firms have used data virtualisation technologies to achieve tactical agility on significant projects while also establishing a broad-spectrum enterprise information access and delivery capability. Each project creates a standard logical data layer in the company by integrating varied data and unstructured information to give real-time business information in readily comprehended data services formats for applications, business intelligence tools, and directly to end-users.

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Key Features of Denodo

  • The user experience is improved, unified, and web-based.
  • In logical data warehouse and data fabric situations, performance acceleration for complicated analytical queries.
  • Cloud and hybrid environments have PaaS support.
  • Graph-like access to Denodo views via enhanced data services APIs.
  • The reinforcement of data science and machine learning goes beyond the logical data warehouse.
  • In the data catalogue, the user experience has been improved.

[Also Read: Denodo Tutorial]

What's the Significance of using Denodo?

1. Cost-Based Optimiser is Integrated

The CBO (cost based optimiser) can transfer all portions of the execution tree to the MPP query accelerations based on data value assessment and the cost of these specific operations.

  • Pushes down partial aggregation.
  • It will make the source processing as efficient as possible.
  • Reduces network traffic dramatically.
  • Parallel execution
  • For quick analytical processing in low-cost Hadoop-based applications, Denodo supports spark, presto, Hive, and Impala.
  • Denodo automatically produces and uploads parquet files when you need them.

2. Agile Business Intelligence

  • A logical data warehouse logically stores data.
  • Data marts that aren't physically present. Virtual marts
  • Self-services

[Also Read Related Article: Denodo Interview Questions]

3. Denodo- a Single View Application

  • Single customer's perspective
  • View of a single product
  • View of a single inventory
  • Specific to the vertical

4. Big Data and Cloud Integration

  • Data warehouse offloading for advanced analytics Big data for corporate Cloud and SaaS product integration

5. Data Services

  • The layer for unified data services.
  • Abstraction of logical data
  • Agile application development.
  • Services based on linked data

[Related Article: Denodo Data Virtualization]

Denodo is Commonly used in the following Contexts

  • You work for a firm with client information (CRM) stored in MySQL databases.
  • A Denodo will keep track of the organisation's data and guarantee that it is stored so that different business procedures may be carried out.
  • The complete billing information for every client is available on an internal web service, and a Denodo is required to keep it up to date.
  • When end users choose not to utilise various programs to recover consumer information that was previously available (CRM, sales applications, etc.).
  • IT firms don't want to waste time and money developing a new application for this business necessity; thus, they'd instead utilise this global customer view in other applications.

Conclusion

Keeping track of business data in any corporation is a complex undertaking. Most of today's leading firms are on the lookout for cutting-edge technology to handle data transactions. Denodo architecture acts as a single data delivery platform, bridging the gap between IT infrastructure and business applications that consume data. 

Course Schedule
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Denodo TrainingOct 15 to Oct 30View Details
Denodo TrainingOct 19 to Nov 03View Details
Denodo TrainingOct 22 to Nov 06View Details
Denodo TrainingOct 26 to Nov 10View Details
Last updated: 04 Apr 2023
About Author

 

Madhuri is a Senior Content Creator at MindMajix. She has written about a range of different topics on various technologies, which include, Splunk, Tensorflow, Selenium, and CEH. She spends most of her time researching on technology, and startups. Connect with her via LinkedIn and Twitter .

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