Overview

Periscope

Stacks45

Followers94

Votes10

Tableau

Stacks1.3K

Followers1.4K

Votes8

Periscope vs Tableau: What are the differences?

Differences between Periscope and Tableau

1. Data Sources: Periscope primarily focuses on integrating with SQL databases, making it suitable for organizations that extensively use SQL. Tableau, on the other hand, has more diverse data source options, allowing users to connect to various data sources such as spreadsheets, cloud storage, and APIs.

2. Visualization Capabilities: Tableau is well-known for its extensive visualization capabilities, offering a wide range of charts, graphs, and interactive visualizations. Periscope, although it provides basic visualizations, does not have as extensive options as Tableau and lacks some advanced features like mapping and geospatial visualizations.

3. Collaboration and Sharing: Tableau provides robust collaboration and sharing features, which allow users to collaborate on projects, share dashboards, and schedule automatic updates. Periscope lacks some of these collaboration features and is more focused on individual user analysis rather than team collaboration.

4. Data Governance and Security: Tableau provides a comprehensive suite of data governance features, ensuring data security, access control, and compliance with organizational policies. Periscope, while it offers some security features, does not have the same level of data governance capabilities as Tableau.

5. Pricing Model: Periscope offers a straightforward pricing model where users pay per user per month, making it more suitable for smaller teams or organizations with limited budgets. Tableau, on the other hand, offers a more complex pricing model that includes different types of licenses and deployment options, which may be more suitable for larger enterprises with specific requirements.

6. Learning Curve and Ease of Use: Tableau is often considered more user-friendly with a relatively shorter learning curve compared to Periscope. Tableau's intuitive interface and drag-and-drop functionality make it easier for users to create visualizations and analyze data. Periscope, while it provides powerful functionality, may require more technical expertise and time to learn and navigate effectively.

In summary, Periscope and Tableau differ in their data source integration, visualization capabilities, collaboration features, data governance, pricing models, and ease of use, making them suitable for different organizational needs and preferences.

🔥 Trending in Business Intelligence on StackShare

Visual Data Analytics Software for Videowalls and Dashboards Business Intelligence

Visual Data Analytics Software for Videowalls and Dashboards

Try it View Docs Alternatives

Try

0

1

Advice on Periscope, Tableau

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

Periscope	Tableau
Periscope is a data analysis tool that uses pre-emptive in-memory caching and statistical sampling to run data analyses really, really fast.	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.
Beautiful Visualizations;Expert Query Tools;Seamless Sharing	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.
Statistics
Stacks 45	Stacks 1.3K
Followers 94	Followers 1.4K
Votes 10	Votes 8
Pros & Cons
Pros 6 Great for learning and teaching people SQL 4 Gorgeous "share-able" and "embeddable" dashboards	Pros 6 Capable of visualising billions of rows 1 Responsive 1 Intuitive and easy to learn Cons 3 Very expensive for small companies

What are some alternatives to Periscope, Tableau?

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.