Overview

Power BI

Stacks953

Followers945

Votes29

Klipfolio

Stacks19

Followers18

Votes0

Klipfolio vs Power BI: What are the differences?

Key Differences: Klipfolio vs Power BI

Introduction

In this article, we will discuss the key differences between Klipfolio and Power BI - two popular business intelligence tools.

Integration capabilities: Klipfolio provides seamless integration with various third-party applications, enabling users to connect data from multiple sources easily. On the other hand, Power BI offers a wide range of integration options, including popular business applications like Microsoft Dynamics 365, Salesforce, and SharePoint.
Data visualization options: Klipfolio offers a visually appealing dashboard layout with customizable visual elements like charts, gauges, and tables. Power BI, however, offers a more advanced and extensive set of data visualization options, including customizable visuals, pre-built report templates, and interactive storytelling features.
Data modeling and preparation: Klipfolio mainly focuses on data visualization and lacks advanced data modeling capabilities. In contrast, Power BI provides robust data preparation and modeling features, allowing users to transform and shape their data using ETL (Extract, Transform, Load) functions, calculated columns, and measures.
Collaboration and sharing: Klipfolio allows users to share dashboards and reports with others through email, scheduled PDF exports, or by embedding them on a website. Power BI, on the other hand, provides more comprehensive collaboration features, such as real-time collaboration, shared workspaces, and the ability to publish reports to the Power BI service for wider accessibility.
Native data connectors: Klipfolio supports a wide range of data connectors but lacks some popular native connectors like Google Analytics and Salesforce. In contrast, Power BI offers a extensive collection of native data connectors, allowing users to connect to various data sources seamlessly.
Pricing model: Klipfolio follows a subscription-based pricing model, where pricing is based on the number of users and features required. Power BI, on the other hand, provides various pricing plans including a free version, making it more accessible for small businesses and individuals.

In Summary, Klipfolio and Power BI differ in terms of integration capabilities, data visualization options, data modeling and preparation features, collaboration and sharing functionality, native data connectors, and pricing models.

Advice on Power BI, Klipfolio

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.

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Comments

Detailed Comparison

Power BI	Klipfolio
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.	You can pull your data together using out-of-the-box, hassle-free connectors for hundreds of data sources, including spreadsheets, files, databases, and web services applications.
Get self-service analytics at enterprise scale; Use smart tools for strong results; Help protect your analytics data	-
Statistics
Stacks 953	Stacks 19
Followers 945	Followers 18
Votes 29	Votes 0
Pros & Cons
Pros 18 Cross-filtering 4 Database visualisation 2 Powerful Calculation Engine 2 Intuitive and complete internal ETL 2 Access from anywhere	No community feedback yet
Integrations
Microsoft Excel	MySQL Slack

What are some alternatives to Power BI, Klipfolio?

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.

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.