Overview

Tableau

Stacks1.3K

Followers1.4K

Votes8

Databox

Stacks30

Followers33

Votes0

Databox vs Tableau: What are the differences?

Introduction

Databox and Tableau are both powerful data visualization tools that offer unique features for organizations to analyze and present data effectively. Below are the key differences between Databox and Tableau.

1. Pricing Model: Databox offers a simpler pricing model with a flat rate for all features and users, making it more cost-effective for small to medium-sized businesses. On the other hand, Tableau's pricing structure is more complex, with different tiers and add-ons, catering to larger enterprises with diverse needs.

2. User Interface: Databox is known for its user-friendly interface, making it easy for non-technical users to create and customize dashboards quickly. Tableau, while offering more advanced visualization capabilities, has a steeper learning curve due to its complex interface and features, requiring more training for users.

3. Data Connection Options: Databox primarily focuses on connecting with popular data sources like Google Analytics, Facebook Ads, and Salesforce, offering seamless integrations for businesses using these platforms. In contrast, Tableau offers a wider range of data connections, including more niche sources and databases, making it suitable for organizations with diverse data sources.

4. Collaboration Features: Tableau excels in its collaboration features, allowing multiple users to work on the same dashboard simultaneously and share insights easily within the platform. Databox, while offering basic collaboration tools, lacks the real-time collaboration capabilities of Tableau, making it less suitable for teams working on projects together.

5. Customization Options: Tableau provides extensive customization options for users to create highly interactive and visually appealing dashboards, utilizing advanced features like calculated fields, parameters, and custom mappings. Databox, while offering some customization tools, is more limited in terms of design flexibility and advanced functionality compared to Tableau.

6. Mobile Accessibility: Databox is optimized for mobile use, providing a dedicated mobile app for users to access and interact with dashboards on the go, ensuring data is easily accessible anytime, anywhere. Tableau also offers mobile compatibility, but its mobile experience may not be as seamless or user-friendly as Databox's dedicated mobile app.

In Summary, Databox and Tableau differ in pricing structure, user interface, data connections, collaboration features, customization options, and mobile accessibility, catering to different needs and preferences in data visualization tools for organizations.

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Advice on Tableau, Databox

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

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	Databox
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.	Databox is an easy-to-use analytics platform that helps growing businesses centralize their data, and use it to make better decisions and improve performance.
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.	Metrics & KPIs; Dashboards; Reports; Benchmarks; Forecast; Goals; Performance Summaries; Notifications; Data Prep
Statistics
Stacks 1.3K	Stacks 30
Followers 1.4K	Followers 33
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	Google Search Console SEMrush Intercom Wistia ActiveCampaign Jira Harvest HubSpot SurveyMonkey Shopify

What are some alternatives to Tableau, Databox?

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'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: 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

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.

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

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.

AskNed

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

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.

Redash

Redash helps you make sense of your data. Connect and query your data sources, build dashboards to visualize data and share them with your company.

Azure Synapse

It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.