Jupyter Notebook vs. Microsoft BI (MSBI)

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Jupyter Notebook
Score 8.4 out of 10
N/A
Jupyter Notebook is an open-source web application that allows users to create and share documents containing live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, and machine learning. It supports over 40 programming languages, and notebooks can be shared with others using email, Dropbox, GitHub and the Jupyter Notebook Viewer. It is used with JupyterLab, a web-based IDE for…N/A
Microsoft BI (MSBI)
Score 8.7 out of 10
N/A
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
Jupyter NotebookMicrosoft 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
Jupyter NotebookMicrosoft BI (MSBI)
Free Trial
NoNo
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Jupyter NotebookMicrosoft BI (MSBI)
Features
Jupyter NotebookMicrosoft BI (MSBI)
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Jupyter Notebook
9.0
22 Ratings
8% above category average
Microsoft BI (MSBI)
-
Ratings
Connect to Multiple Data Sources10.022 Ratings00 Ratings
Extend Existing Data Sources10.021 Ratings00 Ratings
Automatic Data Format Detection8.514 Ratings00 Ratings
MDM Integration7.415 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Jupyter Notebook
7.0
22 Ratings
19% below category average
Microsoft BI (MSBI)
-
Ratings
Visualization6.022 Ratings00 Ratings
Interactive Data Analysis8.022 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Jupyter Notebook
9.5
22 Ratings
15% above category average
Microsoft BI (MSBI)
-
Ratings
Interactive Data Cleaning and Enrichment10.021 Ratings00 Ratings
Data Transformations10.022 Ratings00 Ratings
Data Encryption8.514 Ratings00 Ratings
Built-in Processors9.314 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Jupyter Notebook
9.3
22 Ratings
10% above category average
Microsoft BI (MSBI)
-
Ratings
Multiple Model Development Languages and Tools10.021 Ratings00 Ratings
Automated Machine Learning9.218 Ratings00 Ratings
Single platform for multiple model development10.022 Ratings00 Ratings
Self-Service Model Delivery8.020 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Jupyter Notebook
10.0
20 Ratings
16% above category average
Microsoft BI (MSBI)
-
Ratings
Flexible Model Publishing Options10.020 Ratings00 Ratings
Security, Governance, and Cost Controls10.019 Ratings00 Ratings
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Jupyter Notebook
-
Ratings
Microsoft BI (MSBI)
9.0
53 Ratings
10% above category average
Pixel Perfect reports00 Ratings8.546 Ratings
Customizable dashboards00 Ratings9.653 Ratings
Report Formatting Templates00 Ratings9.051 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Jupyter Notebook
-
Ratings
Microsoft BI (MSBI)
8.6
53 Ratings
7% above category average
Drill-down analysis00 Ratings8.548 Ratings
Formatting capabilities00 Ratings8.353 Ratings
Integration with R or other statistical packages00 Ratings8.442 Ratings
Report sharing and collaboration00 Ratings9.053 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Jupyter Notebook
-
Ratings
Microsoft BI (MSBI)
8.6
52 Ratings
5% above category average
Publish to Web00 Ratings9.448 Ratings
Publish to PDF00 Ratings9.248 Ratings
Report Versioning00 Ratings7.544 Ratings
Report Delivery Scheduling00 Ratings8.547 Ratings
Delivery to Remote Servers00 Ratings8.626 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Jupyter Notebook
-
Ratings
Microsoft BI (MSBI)
8.7
52 Ratings
9% above category average
Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings9.651 Ratings
Location Analytics / Geographic Visualization00 Ratings8.748 Ratings
Predictive Analytics00 Ratings7.945 Ratings
Pattern Recognition and Data Mining00 Ratings8.76 Ratings
Access Control and Security
Comparison of Access Control and Security features of Product A and Product B
Jupyter Notebook
-
Ratings
Microsoft BI (MSBI)
9.3
53 Ratings
9% above category average
Multi-User Support (named login)00 Ratings9.549 Ratings
Role-Based Security Model00 Ratings9.447 Ratings
Multiple Access Permission Levels (Create, Read, Delete)00 Ratings8.949 Ratings
Report-Level Access Control00 Ratings9.46 Ratings
Single Sign-On (SSO)00 Ratings9.531 Ratings
Mobile Capabilities
Comparison of Mobile Capabilities features of Product A and Product B
Jupyter Notebook
-
Ratings
Microsoft BI (MSBI)
8.1
42 Ratings
5% above category average
Responsive Design for Web Access00 Ratings8.239 Ratings
Mobile Application00 Ratings8.030 Ratings
Dashboard / Report / Visualization Interactivity on Mobile00 Ratings7.939 Ratings
Application Program Interfaces (APIs) / Embedding
Comparison of Application Program Interfaces (APIs) / Embedding features of Product A and Product B
Jupyter Notebook
-
Ratings
Microsoft BI (MSBI)
8.6
24 Ratings
11% above category average
REST API00 Ratings9.321 Ratings
Javascript API00 Ratings8.921 Ratings
iFrames00 Ratings8.920 Ratings
Java API00 Ratings8.918 Ratings
Themeable User Interface (UI)00 Ratings8.121 Ratings
Customizable Platform (Open Source)00 Ratings7.519 Ratings
User Ratings
Jupyter NotebookMicrosoft BI (MSBI)
Likelihood to Recommend
10.0
(23 ratings)
9.0
(77 ratings)
Likelihood to Renew
-
(0 ratings)
8.0
(25 ratings)
Usability
10.0
(2 ratings)
9.0
(19 ratings)
Availability
-
(0 ratings)
9.5
(2 ratings)
Performance
-
(0 ratings)
7.0
(2 ratings)
Support Rating
9.0
(1 ratings)
8.9
(15 ratings)
In-Person Training
-
(0 ratings)
6.9
(3 ratings)
Online Training
-
(0 ratings)
8.5
(2 ratings)
Implementation Rating
-
(0 ratings)
9.6
(7 ratings)
Configurability
-
(0 ratings)
10.0
(2 ratings)
User Testimonials
Jupyter NotebookMicrosoft BI (MSBI)
Likelihood to Recommend
Open Source
I've created a number of daisy chain notebooks for different workflows, and every time, I create my workflows with other users in mind. Jupiter Notebook makes it very easy for me to outline my thought process in as granular a way as I want without using innumerable small. inline comments.
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Microsoft
Microsoft BI has a lot of features and is a very powerful tool, especially if you have folks on your team that know how to utilize all of its capabilities. To truly unlock all that it can do, it does require people to have a deep understanding of its capabilities. That's where the software really shines. If you are looking for a simpler, more basic reporting tool, there are other programs available that do not require such a steep learning curve.
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Pros
Open Source
  • Simple and elegant code writing ability. Easier to understand the code that way.
  • The ability to see the output after each step.
  • The ability to use ton of library functions in Python.
  • Easy-user friendly interface.
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Microsoft
  • Comparatively easy to use compared to other data analytics solutions, collaborating with other colleagues on data work is simple.
  • Using Visual Studio for database, ETL, reporting, and analytics development save time and money.
  • Transfer of data from one application to another via Excel and comparison of data attributes between applications
  • Dashboard functionality, as well as Python support, are available, allowing you to add additional charts and graphs.
Read full review
Cons
Open Source
  • Need more Hotkeys for creating a beautiful notebook. Sometimes we need to download other plugins which messes [with] its default settings.
  • Not as powerful as IDE, which sometimes makes [the] job difficult and allows duplicate code as it get confusing when the number of lines increases. Need a feature where [an] error comes if duplicate code is found or [if a] developer tries the same function name.
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Microsoft
  • MSBI designs can work on increasing data processing capabilities enough to handle the huge datasets etc.
  • It would be a lot better if it is a little low on cost.
  • it needs to create opportunities little more than they do regarding customization of some very unique visualization effects
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Likelihood to Renew
Open Source
No answers on this topic
Microsoft
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.
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Usability
Open Source
Jupyter is highly simplistic. It took me about 5 mins to install and create my first "hello world" without having to look for help. The UI has minimalist options and is quite intuitive for anyone to become a pro in no time. The lightweight nature makes it even more likeable.
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Microsoft
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.
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Reliability and Availability
Open Source
No answers on this topic
Microsoft
The product has been reliable.
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Performance
Open Source
No answers on this topic
Microsoft
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.
Read full review
Support Rating
Open Source
I haven't had a need to contact support. However, all required help is out there in public forums.
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Microsoft
MSBI natively has a site that allows you to vote on user enhancements and bug fixes. This allows the largest nagging issues to float to the top and the development team can prioritize accordingly. As mentioned earlier, the large community base of MSBI developers assist technical resources in handling technical questions.
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In-Person Training
Open Source
No answers on this topic
Microsoft
This training was more directed toward what the product was capable of rather than actual programming.
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Online Training
Open Source
No answers on this topic
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.
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Implementation Rating
Open Source
No answers on this topic
Microsoft
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.
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Alternatives Considered
Open Source
With Jupyter Notebook besides doing data analysis and performing complex visualizations you can also write machine learning algorithms with a long list of libraries that it supports. You can make better predictions, observations etc. with it which can help you achieve better business decisions and save cost to the company. It stacks up better as we know Python is more widely used than R in the industry and can be learnt easily. Unlike PyCharm jupyter notebooks can be used to make documentations and exported in a variety of formats.
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Microsoft
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.
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Return on Investment
Open Source
  • Positive impact: flexible implementation on any OS, for many common software languages
  • Positive impact: straightforward duplication for adaptation of workflows for other projects
  • Negative impact: sometimes encourages pigeonholing of data science work into notebooks versus extending code capability into software integration
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Microsoft
  • 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.
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ScreenShots