Sprinkle vs Power BI
Sprinkle Self-serve Data Interface reduces more than 80% of Adhoc report requests and lets the Analytics team focus on Data Modelling and Machine Learning. Sprinkle is a complete Analytics platform unlike Power Bi which is merely a Dashboarding Tool.
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Ease of Use |
Can be used by non-technical users
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Requires Expertise
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Data Modelling & Metric First Approach |
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Only a Dashboarding tool
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Exploratory Analysis on unlimited Data |
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Inbuilt Data Preparation & ETL/ELT |
Multi-stage Data Pipelines
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Realtime Data Refresh |
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Loading Data make it slow
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ML using inbuilt Jupyter Notebooks |
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Data Catalog |
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GitHub Integration |
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SQL Interface |
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Python Editor |
Transform & EDA in python
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Create Custom Expression using SQL |
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Requires DAX functions
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Automatic Partition Management |
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Semi-structured data analysis |
Supports nested and complex data types
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Automatic Schema Discovery |
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Row Level Security |
Easy to configure
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Complex to achieve
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Notifications - Slack & Email |
Slack and Email
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Only Email
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Sprinkle is Fast, Agile, Cost-effective & Easy to scale unlike Power BI

- Limitation on the amount of data that can be analysed.
- Expensive Power BI servers as data scale increases
- Increased operational complexity to manage ETL within Power BI
Why do companies prefer Sprinkle over Power BI ?
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Self-service Analytics for non-Technical users
Power BI is complex to use. Requires Power BI developers to maintain and make any changes. Sprinkle is easy to use. It can be used by non-Technical users for self-serve data analysis. Non-technical users can create their own dashboard and reports.
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Sprinkle allows you to work on all the data
Work on all the data from summarize views to easily drilling-down to granular data points
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Realtime data refresh with integrated ETL
Power BI has no or very limited data transformation capabilities. Sprinkle allows users to create transformation pipelines in SQL and python. Sprinkle has inbuilt support for Real time incremental data pipelines.
Why do data teams love Sprinkle ?
and many more