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  5. Denodo vs Tableau

Denodo vs Tableau

OverviewDecisionsComparisonAlternatives

Overview

Tableau
Tableau
Stacks1.3K
Followers1.4K
Votes8
Denodo
Denodo
Stacks40
Followers120
Votes0
GitHub Stars0
Forks0

Denodo vs Tableau: What are the differences?

# Key Differences between Denodo and Tableau 

Denodo and Tableau are both widely-used tools in the field of data analytics and visualization, but they serve different purposes and have their own unique features. Below are the key differences between Denodo and Tableau:

1. **Functionality**:
Denodo is a data virtualization tool that focuses on integrating diverse data sources from various systems and providing a unified view of the data. On the other hand, Tableau is a data visualization tool that is used to create interactive and visually appealing charts, graphs, and dashboards from data stored in various sources.

2. **Data Integration**:
Denodo specializes in data integration, providing a layer of abstraction on top of multiple data sources, enabling companies to access and query data without the need to physically centralize it. Tableau, on the other hand, excels in data visualization, allowing users to create visually engaging representations of data for better decision-making.

3. **Performance**:
Denodo offers live data access, which means that users can query data in real-time from different sources. Tableau provides efficient data caching techniques, enhancing performance by storing data and improving query response times.

4. **Complexity**:
Denodo is more suited for complex data integration scenarios where data is scattered across multiple systems and requires a consolidated view. Tableau is more user-friendly and is ideal for creating simple yet powerful data visualizations and reports without the need for deep technical skills.

5. **Collaboration**:
Denodo focuses on enabling collaboration among technical teams for data integration and management. Tableau emphasizes collaboration among various business users and stakeholders for visualizing and analyzing data to make informed decisions.

6. **Deployment**:
Denodo can be deployed on-premises or in the cloud, providing flexible options based on the organization's requirements. Tableau also offers both on-premises and cloud deployment options, ensuring scalability and accessibility based on user needs.

In Summary, Denodo and Tableau serve different purposes, with Denodo excelling in data integration and providing a unified view of data sources, while Tableau specializes in data visualization and creating visually appealing dashboards for effective decision-making.

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Advice on Tableau, Denodo

Vojtech
Vojtech

Head of Data at Mews

Nov 24, 2019

Decided

Power BI is really easy to start with. If you have just several Excel sheets or CSV files, or you build your first automated pipeline, it is actually quite intuitive to build your first reports.

And as we have kept growing, all the additional features and tools were just there within the Azure platform and/or Office 365.

Since we started building Mews, we have already passed several milestones in becoming start up, later also a scale up company and now getting ready to grow even further, and during all these phases Power BI was just the right tool for us.

353k views353k
Comments
Wei
Wei

CTO at Flux Work

Jan 8, 2020

Decided

Very easy-to-use UI. Good way to make data available inside the company for analysis.

Has some built-in visualizations and can be easily integrated with other JS visualization libraries such as D3.

Can be embedded into product to provide reporting functions.

Support team are helpful.

The only complain I have is lack of API support. Hard to track changes as codes and automate report deployment.

230k views230k
Comments

Detailed Comparison

Tableau
Tableau
Denodo
Denodo

Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

It is the leader in data virtualization providing data access, data governance and data delivery capabilities across the broadest range of enterprise, cloud, big data, and unstructured data sources without moving the data from their original repositories.

Connect to data on prem or in the cloud—whether it’s big data, a SQL database, a spreadsheet, or cloud apps like Google Analytics and Salesforce. Access and combine disparate data without writing code. Power users can pivot, split, and manage metadata to optimize data sources. Analysis begins with data. Get more from yours with Tableau.; Exceptional analytics demand more than a pretty dashboard. Quickly build powerful calculations from existing data, drag and drop reference lines and forecasts, and review statistical summaries. Make your point with trend analyses, regressions, and correlations for tried and true statistical understanding. Ask new questions, spot trends, identify opportunities, and make data-driven decisions with confidence.; Answer the “where” as well as the “why.” Create interactive maps automatically. Built-in postal codes mean lightning-fast mapping for more than 50 countries worldwide. Use custom geocodes and territories for personalized regions, like sales areas. We designed Tableau maps specifically to help your data stand out.; Ditch the static slides for live stories that others can explore. Create a compelling narrative that empowers everyone you work with to ask their own questions, analyzing interactive visualizations with fresh data. Be part of a culture of data collaboration, extending the impact of your insights.
Data virtualization; Data query; Data views
Statistics
GitHub Stars
-
GitHub Stars
0
GitHub Forks
-
GitHub Forks
0
Stacks
1.3K
Stacks
40
Followers
1.4K
Followers
120
Votes
8
Votes
0
Pros & Cons
Pros
  • 6
    Capable of visualising billions of rows
  • 1
    Responsive
  • 1
    Intuitive and easy to learn
Cons
  • 3
    Very expensive for small companies
No community feedback yet
Integrations
No integrations available
DataRobot
DataRobot
AtScale
AtScale
Vertica
Vertica
Trifacta
Trifacta
Dremio
Dremio
Apache Kylin
Apache Kylin
SAP HANA
SAP HANA

What are some alternatives to Tableau, Denodo?

Metabase

Metabase

It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating.

Superset

Superset

Superset's main goal is to make it easy to slice, dice and visualize data. It empowers users to perform analytics at the speed of thought.

Cube

Cube

Cube: the universal semantic layer that makes it easy to connect BI silos, embed analytics, and power your data apps and AI with context.

Power BI

Power BI

It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards.

Pandas

Pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.

Mode

Mode

Created by analysts, for analysts, Mode is a SQL-based analytics tool that connects directly to your database. Mode is designed to alleviate the bottlenecks in today's analytical workflow and drive collaboration around data projects.

Google Datastudio

Google Datastudio

It lets you create reports and data visualizations. Data Sources are reusable components that connect a report to your data, such as Google Analytics, Google Sheets, Google AdWords and so forth. You can unlock the power of your data with interactive dashboards and engaging reports that inspire smarter business decisions.

NumPy

NumPy

Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.

AskNed

AskNed

AskNed is an analytics platform where enterprise users can get answers from their data by simply typing questions in plain English.

Shiny

Shiny

It is an open source R package that provides an elegant and powerful web framework for building web applications using R. It helps you turn your analyses into interactive web applications without requiring HTML, CSS, or JavaScript knowledge.

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