AMIs are Amazon Machine Images, virtual appliance deployed on EC2. The AWS Deep Learning AMIs provide machine learning practitioners and researchers with the infrastructure and tools to accelerate deep learning in the cloud, at scale. Users can launch Amazon EC2 instances pre-installed with deep learning frameworks and interfaces such as TensorFlow, PyTorch, Apache MXNet, Chainer, Gluon, Horovod, and Keras to train sophisticated, custom AI models, experiment with new algorithms, or to learn new…
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Microsoft BI (MSBI)
Score 8.7 out of 10
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Microsoft BI is a business intelligence product used for data analysis and generating reports on server-based data. It features unlimited data analysis capacity with its reporting engine, SQL Server Reporting Services alongside ETL, master data management, and data cleansing.
$14
per month per user
Pricing
Amazon Deep Learning AMIs
Microsoft BI (MSBI)
Editions & Modules
No answers on this topic
Power BI Pro
$14
per month per user
Power BI Premium
$24
per month per user
Offerings
Pricing Offerings
Amazon Deep Learning AMIs
Microsoft BI (MSBI)
Free Trial
No
No
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
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Community Pulse
Amazon Deep Learning AMIs
Microsoft BI (MSBI)
Features
Amazon Deep Learning AMIs
Microsoft BI (MSBI)
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Amazon Deep Learning AMIs
-
Ratings
Microsoft BI (MSBI)
9.8
49 Ratings
18% above category average
Pixel Perfect reports
00 Ratings
9.842 Ratings
Customizable dashboards
00 Ratings
9.749 Ratings
Report Formatting Templates
00 Ratings
9.847 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Amazon Deep Learning AMIs
-
Ratings
Microsoft BI (MSBI)
9.8
49 Ratings
20% above category average
Drill-down analysis
00 Ratings
9.844 Ratings
Formatting capabilities
00 Ratings
9.749 Ratings
Integration with R or other statistical packages
00 Ratings
9.839 Ratings
Report sharing and collaboration
00 Ratings
9.849 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Amazon Deep Learning AMIs
-
Ratings
Microsoft BI (MSBI)
9.8
48 Ratings
17% above category average
Publish to Web
00 Ratings
9.844 Ratings
Publish to PDF
00 Ratings
9.844 Ratings
Report Versioning
00 Ratings
9.840 Ratings
Report Delivery Scheduling
00 Ratings
9.843 Ratings
Delivery to Remote Servers
00 Ratings
9.824 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Amazon AMIs has been very useful for the quick setup and implementation of deep learning for data analysis which is something I have used the service for in my own research. We commonly use the service to enable students to run intensive deep learning algorithms for their assessments. This service works well in this scenario as it allows students to quickly set up a suitable environment and get started with little hassle. If you are looking to run simple, surface level deep learning algorithms (kind of contradictory statement I know) then AMI is more complicated than most will need. When it comes to teaching the basics of Machine Learning, this kind of system is unnecessary and there are other alternatives which can be used. That being said this service is a must if you are looking to run complex deep learning via the cloud.
Microsoft BI is well suited for Stream analytics, easy data integration, report creation and UI/UX designs (limited but what all available are great ones) Microsoft BI may be less appropriate for handling huge number of datasets and difficult queries. It may also be difficult for a company with heavy data.
The race to perfect gathering of Non-Traditional datasets is on-going; with Microsoft arguably not the leader of the pack in this category.
Licensing options for PowerBI visualizations may be a factor. I.e. if you need to implement B2C PowerBI visualizations, the cost is considerably high especially for startups.
Some clients are still resistant putting their data on the cloud, which restricts lots of functionality to Power BI.
Microsoft BI is fundamental to our suite of BI applications. That being said, Northcraft Analytics is focused on delighting our customers, so if the underlying factors of our decision change, we would choose to re-write our BI applications on a different stack. Luckily, mathematics are the fundamental IP of our technology... and is portable across all BI platforms for the foreseeable future.
The Microsoft BI tools have great usability for both developers and end users alike. For developers familiar with Visual Studio, there is little learning curve. For those not, the single Visual Studio IDE means not having to learn separate tools for each component. For end-users, the web interface for SSRS is simple to navigate with intuitive controls. For ad-hoc analysis, Excel can connect directly to SSAS and provide a pivot table like experience which is familiar to many users. For database development, there is beginning to be some confusion, as there are now three tool choices (VS, SSMS, Azure Data Studio) for developers. I would like to see Azure Data Studio become the superset of SSMS and eventually supplant it.
SQL Server Reporting Services (SSRS) can drag at times. We created two report servers and placed them under an F5 load balancer. This configuration has worked well. We have seen sluggish performance at times due to the Windows Firewall.
While support from Microsoft isn't necessarily always best of breed, you're also not paying the price for premium support that you would on other platforms. The strength of the stack is in the ecosystem that surrounds it. In contrast to other products, there are hundreds, even thousands of bloggers that post daily as well as vibrant user communities that surround the tool. I've had much better luck finding help with SQL Server related issues than I have with any other product, but that help doesn't always come directly from Microsoft.
I have used on-line training from Microsoft and from Pragmatic Works. I would recommend Pragmatic Works as the best way to get up to speed quickly, and then use the Microsoft on-line training to deep dive into specific features that you need to get depth with.
We are a consulting firm and as such our best resources are always billing on client projects. Our internal implementation has weaknesses, but that's true for any company like ours. My rating is based on the product's ease of implementation.
Both of these services provide similar functionality and from my experience both are top class services which cover most of your needs. I think ultimately it comes down to what you need each service for. For example Amazon DL AMIs allows for clustering by default meaning I am able to run several clustering algorithms without a problem whereas IBM Watson Studio doesn't provide this functionality. They both provide a wide range of default packages such as Amazon providing caffe-2 and IBM providing sci-kitlearn. My main point is that both are very good services which have very similar functionality, you just need to think about the costs, suitability of features and integration with other services you are using.
We have used the built in ConnectWise Manager reports and custom reports. The reports provide static data. PowerBI shows us live data we can drill down into and easily adjust parameters. It's much more useful than a static PDF report.
As a SaaS provider we see being able to provide self-service BI to our client users as a competitive advantage. In fact the MSSQL enabled BI is a contributing factor to many winning RFPs we have done for prospective client organisations.
However MSSQL BI requires extensive knowledge and skills to design and develop data warehouses & data models as a foundation to support business analysts and users to interrogate data effectively and efficiently. Often times we find having strong in-house MSSQL expertise is a bless.