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  5. DOMO vs Mprove

DOMO vs Mprove

OverviewComparisonAlternatives

Overview

DOMO
DOMO
Stacks52
Followers75
Votes0
Mprove
Mprove
Stacks3
Followers6
Votes0
GitHub Stars329
Forks27

DOMO vs Mprove: What are the differences?

  1. Integration Capabilities: DOMO primarily focuses on providing easy integration with various data sources like databases, CRMs, and cloud applications. On the other hand, Mprove offers robust capabilities in integrating with Google Analytics, Google Sheets, and Excel files, making it ideal for data analysis tasks related to web analytics and reporting.
  2. Data Visualization Options: DOMO offers a wide range of out-of-the-box visualization options allowing users to create visually appealing dashboards and reports quickly. In contrast, Mprove specializes in offering advanced visualization features such as cohort analysis, funnel visualization, and attribution modeling, making it suitable for complex data analysis scenarios.
  3. Collaboration Features: DOMO provides extensive collaboration features such as real-time sharing, commenting, and notifications, enhancing teamwork and decision-making processes. Conversely, Mprove focuses more on individual data analysis tasks, offering limited collaboration functionalities, thus making it more suitable for independent analysts.
  4. Customization Flexibility: DOMO allows users to customize dashboards, reports, and data visualizations extensively, offering a high level of flexibility in designing and presenting data insights. Conversely, Mprove focuses on providing predefined analysis models and templates, limiting the customization options available to users.
  5. Cost Structure: DOMO follows a subscription-based pricing model, which may involve additional costs based on the number of users and data connectors required. In contrast, Mprove offers a more budget-friendly pricing structure, making it a cost-effective solution for small to medium-sized businesses with specific data analysis needs.

In Summary, when comparing DOMO and Mprove, key differences lie in their integration capabilities, data visualization options, collaboration features, customization flexibility, and cost structure.

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Detailed Comparison

DOMO
DOMO
Mprove
Mprove

Domo: business intelligence, data visualization, dashboards and reporting all together. Simplify your big data and improve your business with Domo's agile and mobile-ready platform.

A better workflow for teams. Data Analysts create SQL models. Business users explore models using a simple user interface.

-
Dashboards; Charts; Filters; SQL; Git powered workflow; Split SQL into YAML chunks; Reusable SQL blocks; Time zones; Open source
Statistics
GitHub Stars
-
GitHub Stars
329
GitHub Forks
-
GitHub Forks
27
Stacks
52
Stacks
3
Followers
75
Followers
6
Votes
0
Votes
0
Integrations
Box
Box
Loggly
Loggly
Basecamp
Basecamp
HipChat
HipChat
Asana
Asana
Google BigQuery
Google BigQuery
Amazon Redshift
Amazon Redshift
Mailchimp
Mailchimp
HubSpot
HubSpot
GitHub
GitHub
Clickhouse
Clickhouse
PostgreSQL
PostgreSQL
Google BigQuery
Google BigQuery

What are some alternatives to DOMO, Mprove?

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.

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.

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.

Redash

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

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.

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