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Amazon Quicksight vs Looker: What are the differences?
Amazon QuickSight and Looker are both business intelligence and data visualization platforms. Let's explore the key differences between the two.
Pricing and Cost Structure: Amazon Quicksight offers a pay-per-session pricing model, where users are charged based on the number of sessions initiated. On the other hand, Looker follows a subscription-based pricing model, where the cost is determined by the number of users and the specific edition chosen.
Data Integration and Connectivity: Quicksight offers seamless integration with various data sources, including Amazon Redshift, Amazon Athena, and Amazon S3. Looker, on the other hand, supports a wide range of SQL-based databases and cloud data platforms, offering more flexibility in terms of data connectivity.
Data Modeling and Transformation: Quicksight provides limited data modeling capabilities, primarily focused on data cleansing and transformation. Looker, on the contrary, offers advanced data modeling functionalities, allowing users to build complex data models with ease.
Visualization and Reporting: Quicksight offers a variety of visualization options and pre-built visualizations, which can be customized to create interactive dashboards and reports. Looker provides a rich set of visualization capabilities, including advanced charting tools and data exploration features, allowing users to uncover insights in a visually appealing manner.
Collaboration and Sharing: Quicksight offers basic collaboration features, allowing users to share dashboards and reports with others. Looker, on the other hand, provides more extensive collaboration capabilities, enabling users to collaborate in real-time, set permissions, and annotate and comment on specific data points.
Scalability and Performance: Quicksight leverages Amazon's scalable infrastructure, ensuring high performance and the ability to handle large volumes of data. Looker also offers scalability but may experience performance limitations when dealing with extremely large datasets.
In summary, Amazon QuickSight is an Amazon Web Services solution for quick and scalable data visualization, whereas Looker offers a comprehensive business intelligence platform with a focus on data exploration and collaboration.
We are a consumer mobile app IOS/Android startup. The app is instrumented with branch and Firebase. We use Google BigQuery. We are looking at tools that can support engagement and cohort analysis at an early stage price which we can grow with. Data Studio is the default but it would seem Looker provides more power. We don't have much insight into Amplitude other than the fact it is a popular PM tool. Please provide some insight.
Hello Mohan,
To be honest, I don't have experience working with analytics on apps and also I don't have experience with Looker, so I cannot say I will suggest that one. I know that Amplitude is a known product analytics tool for apps. I know that in the #GoPractice course, Oleg (CEO GoPractice) was using Amplitude in all his experience with mobile game apps, so I guess apps could work well too. I have experience using Amplitude for SaaS solutions and it is great to create all kinds of analytics for the product. Then Google Datastudio is the classic solution to create dashboards and reports connect it with any data source. Also, some people, instead of Amplitude are using the new Google Analytics, @GoogleAnalytics #GA4 or Mixpanel. However, my suggestion is to use Amplitude and if there are reports that you cannot answer with Amplitude, use Google Data Studio.
I hope that could help you.
Cheers,
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.
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.
Pros of Amazon Quicksight
- Dataset versionning1
- Good integration with aws Glue ETL services1
- More features (table calculations, functions, insights)1
- Better integration with aws1
- Super cheap1
Pros of Looker
- Real time in app customer chat support4
- GitHub integration4
- Reduces the barrier of entry to utilizing data1
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Cons of Amazon Quicksight
- Very basic BI tool1
- Only works in AWS environments (not GCP, Azure)1
Cons of Looker
- Price3
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What is Amazon Quicksight?
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