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Amazon SageMaker vs Microsoft Power BI comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

ROI

Sentiment score
7.3
Amazon SageMaker offers significant ROI with cost reductions, time savings, and notable financial benefits, especially in fraud detection and targeted ads.
Sentiment score
7.9
Organizations achieved substantial ROI with Microsoft Power BI, finding it cost-effective, user-friendly, and beneficial for small teams.
The return on investment varies by use case and offers significant value in revenue increases and cost saving capabilities, especially in real time fraud detection and targeted advertisements.
In a world surrounded by data, tools that allow navigation of large data volumes ensure decisions are data-driven.
Power BI is easy to deploy within an hour, providing robust security against data leaks.
 

Customer Service

Sentiment score
7.2
Amazon SageMaker customer service has mixed reviews, with satisfaction varying based on user experience, support promptness, and service tier.
Sentiment score
6.7
Microsoft Power BI customer service is generally responsive and effective, but many users rely on online resources for solutions.
The technical support from AWS is excellent.
The support is very good with well-trained engineers.
We have a partnership with Microsoft, involving multiple weekly calls with dedicated personnel to ensure our satisfaction.
Unfortunately, with Microsoft, you must accept the product as it is.
 

Scalability Issues

Sentiment score
7.6
Amazon SageMaker is highly scalable, handling diverse data needs effectively but may require deployment expertise for optimal efficiency.
Sentiment score
7.0
Microsoft Power BI scales well for diverse organizations, but large datasets and costs may affect performance and scalability potential.
The availability of GPU instances can be a challenge, requiring proper planning.
Amazon SageMaker is scalable and works well from an infrastructure perspective.
With increasing AI capabilities, architectural developments within Microsoft, and tools like Fabric, I expect Power BI to scale accordingly.
You expect only a small percentage of users concurrently, but beyond a thousand concurrent users, it becomes difficult to manage.
 

Stability Issues

Sentiment score
7.8
Amazon SageMaker is stable and reliable, with minor issues mainly due to user configuration errors, not infrastructure problems.
Sentiment score
7.5
Microsoft Power BI is reliable, with occasional issues on large datasets, generally viewed positively compared to similar products.
I rate the stability of Amazon SageMaker between seven and eight.
In terms of stability, there's no data loss or leakage, and precautions are well-managed by Microsoft.
We typically do not have problems with end-user tools like Excel and Power BI.
It's not a bad grade, as I know of better products in this field.
 

Room For Improvement

Amazon SageMaker needs UI simplification, better documentation, cost efficiency improvements, enhanced security, scalability, training resources, and performance optimization.
Microsoft Power BI needs improved data integration, user-friendly features, enhanced visualizations, better mobile support, and clearer licensing options.
Having all documentation easily accessible on the front page of SageMaker would be a great improvement.
Integration of the latest machine learning models like the new Amazon LLM models could enhance its capabilities.
This would empower citizen data scientists to utilize the tool more effectively since many data scientists do not have a core development background.
Access was more logical in how it distinguished between data and its formatting.
This makes Power BI difficult to manage as loading times can reach one or two minutes, which is problematic today.
Microsoft updates Power BI monthly based on user community feedback.
 

Setup Cost

Amazon SageMaker is costly, especially for notebook instances, with better visibility needed to optimize pay-as-you-go costs.
Microsoft Power BI provides flexible pricing with a free desktop version and paid options ideal for various enterprise needs.
For a single user, prices might be high yet could be cheaper for user-managed services compared to AWS-managed services.
The pricing can be up to eight or nine out of ten, making it more expensive than some cloud alternatives yet more economical than on-premises setups.
The cost for small to medium instances is not very high.
Power BI isn't very cheap, however, it is economical compared to other solutions available.
I found the setup cost to be expensive
 

Valuable Features

Amazon SageMaker provides flexible AI/ML solutions with easy AWS integration, strong deployment features, and comprehensive tools for scalability.
Microsoft Power BI offers robust data visualization, integration, and insights, enhancing decision-making with intuitive interfaces and extensive connectivity.
These features facilitate rapid development and deployment of AI applications.
SageMaker supports building, training, and deploying AI models from scratch, which is crucial for my ML project.
This allows monitoring and performance grading, as I instantly know when someone has a bad call.
In today's data-driven environment, these tools are of substantial value, particularly for large enterprises with numerous processes that require extensive data analysis.
It allows me to show detailed improvements in quality and safety and patient experience.
The entire ETL process is easy and supports many databases, allowing data pipelines from multiple sources to be gathered in one place for visualization.
 

Categories and Ranking

Amazon SageMaker
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
36
Ranking in other categories
Data Science Platforms (3rd), AI Development Platforms (4th)
Microsoft Power BI
Average Rating
8.0
Reviews Sentiment
7.3
Number of Reviews
319
Ranking in other categories
BI (Business Intelligence) Tools (1st), Reporting (1st)
 

Mindshare comparison

While both are Business Intelligence solutions, they serve different purposes. Amazon SageMaker is designed for Data Science Platforms and holds a mindshare of 7.5%, down 9.9% compared to last year.
Microsoft Power BI, on the other hand, focuses on BI (Business Intelligence) Tools, holds 21.8% mindshare, down 22.7% since last year.
Data Science Platforms
BI (Business Intelligence) Tools
 

Featured Reviews

Hemant Paralkar - PeerSpot reviewer
Improves team collaboration with advanced feature sharing but needs a better user experience
Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker. This would empower citizen data scientists to utilize the tool more effectively since many data scientists do not have a core development background. Additionally, dealing with frequent UI updates can be challenging, especially for infrastructure architects like myself. It involves effort to migrate to new UIs, making the updates not seamless. User auditing requires enhancements as tracking operations performed by users can be difficult due to dynamic IP validation and role propagation.
James Balbach - PeerSpot reviewer
Robust system consistently elevates data visualization and seamlessly updates with user-driven advancements
Power BI is a general-use visualization system. I can express the performance of our network through high-level key performance indicators. It allows me to show detailed improvements in quality and safety and patient experience. I create improvement dashboards for task forces and work teams. I have built analytic dashboards that guide analytics, enabling research and dataset manipulation.
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Comparison Review

it_user79932 - PeerSpot reviewer
Feb 4, 2015
Comparison of SAP BO, Tableau, QlikView, Cognos, Microsoft, OBIEE and Pentaho
1. SAP BO/BI Enterprise scalability Security Ease of use Semantic layer 2. Tableau Visualization Data discovery Turnaround time 3. IBM Cognos Enterprise scalability Security In-memory feature 4. MS BI - Flexibility 5. Pentaho - Open source but still enterprise grade 6. QlikView Data…
 

Top Industries

By visitors reading reviews
Financial Services Firm
19%
Educational Organization
13%
Computer Software Company
11%
Manufacturing Company
8%
Educational Organization
43%
Financial Services Firm
8%
Computer Software Company
6%
Government
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

How would you compare Databricks vs Amazon SageMaker?
We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...
What do you like most about Amazon SageMaker?
We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to ChatGPT that requires models. We utilize Amazon SageMaker to create endpoints for t...
What is your experience regarding pricing and costs for Amazon SageMaker?
Before deploying SageMaker, I reviewed the pricing, especially for notebook instances. The cost for small to medium instances is not very high.
Seeking lightweight open source BI software
There are many...It would rather depend what System BI architecture or Enterprise legacy you have at your end...I would recommend as follows: 1) If you have legacies of SAP, Oracle - look for SAP...
Is Power BI a complete platform or only a visualization tool?
Power BI is an advanced visualization tool oriented to big data with a very complete set of widgets to visualize information, control users accessing information, the configuration of governance po...
How does Oracle OBIEE compare with Microsoft BI?
Oracle OBIEE is great in allowing design and creativity per the individual needs of the organization. Dashboards are fully customizable and very user-friendly. This solution is very stable. Oracle ...
 

Also Known As

AWS SageMaker, SageMaker
SSRS, SSAS, MSBI, MS Reporting Services, Microsoft BI Tools, Microsoft Big Data, Power BI Pro, MS BI
 

Overview

 

Sample Customers

DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit
Accenture Adidas Aetna AIG Airbus Alibaba Allstate Amazon American Express Aon AT&T Audi Bank of America BASF Bayer Berkshire Hathaway Boeing Coca-Cola Comcast Cisco Coca-Cola Dell Disney Emirates Equinix FedEx Ford GE Google H&M Home Depot Honda IBM Intel JPMorgan Chase Kellogg's Kroger L'Oréal McDonald's Merck MetLife Microsoft Nike Oracle P&G PepsiCo Procter & Gamble Prudential Financial SAP Siemens Snapchat Spotify Starbucks Target Toyota T-Mobile Unilever Visa Walmart WeWork World Bank Xerox
Find out what your peers are saying about Databricks, Knime, Amazon Web Services (AWS) and others in Data Science Platforms. Updated: February 2025.
842,194 professionals have used our research since 2012.