IBM Watson Studio on Cloud Pak for Data vs. OneNote vs. Spotfire

It has a lot of features that are good for teams working on large-scale projects and continuously developing and reiterating their data project models. Really helpful when dealing with large data. It is a kind of one-stop solution for all data science tasks like visualization, cleaning, analyzing data, and developing models but small teams might find a lot of features unuseful.

Incentivized

In my opinion OneNote is a must for anyone who does business. It’s versatile, stable and sustainable. It can keep private information private - like passwords. It can be used for collaborative work - like standard operating procedures. It is fairly easy to use and far superior to pen and paper. When used for meeting notes, it can be flagged with icons that are searchable - like ideas or important items. You can even create Outlook tasks on the fly

Incentivized

A high level of data integration is available here it supports various data sources and so on. Collaborating features allow users to give access to the dashboard and merge data analytics with other team members. It can meet the demands of both small and large size business enterprises. A customized dashboard and reports are provided to meet the specific needs and get support of extensibility through APIs and customized scripts.

Incentivized

• Integration of IBM Watson APIs such as speech to text, image recognition, personality insights, etc.
• SPSS modeler and neural network model provide no-code environments for data scientists to build pipelines quickly.
• Enforced best-practices set up POCs for deployment in production with a minimum of re-work.
• Estimator validation lets data scientists test and prove different models.

Incentivized

• Because of its flexibility and ability to hold different types of content (text, images, tables), it is a great tool for collecting content from different resources and organizing it in one place.
• Technical support analysts are using sections for their support case analysis; they paste pieces of logs, screen-shots, document their steps in troubleshooting etc., all in one section, to get the full picture yet stay organized.
• The logic of content structure; Notebook>Section>Page>Paragraph, allows you to manage and collect all needed information by the areas of the user's responsibility. For example; each of my projects has its own section, in which each page is a task.

Incentivized

• It has the best coding integration (python, R) of any BI product
• The ability to work with very large datasets (10 mil+) is better than competitors
• Export options are more complete and have better functionality
• The data canvas is the best tool to join and transform data vs. competitors

Incentivized

• The cost is steep and so only companies with resources can afford it
• It will be nice to have Chinese versions so that Chinese engineers can also use it easily
• It takes a while to learn how to input different kinds of skin defects for detection

Incentivized

• The table editing tools are too simplistic and lack the features found in other Office products.
• Some content loses its rich text formatting when being pasted into OneNote. A workaround is to paste the content first into Outlook or Word and then copy/pasting that into OneNote.
• Microsoft is moving away from a local install of OneNote, which means notebooks have to be in the cloud in Office 2019. This will actually reduce the usefulness of OneNote in some environments and opens the door to competitor products.
• Update: Microsoft has now announced that it will continue to support OneNote 2016 through 2023. https://techcommunity.microsoft.com/t5/Office-365-Blog/Your-OneNote/ba-p/954922

Incentivized

• The donut chart is I guess a powerful illustrations but I hope it should be done quite simple in Spotfire. But in Spotfire there are lots of steps involve just to build a simple donut chart.
• Table calculation (like Row or Column Differences) should be made simple or there should be drag and drop function for Table Calculation. No need for scripting.
• Information Link should be changed. If new columns are added to the table just refreshing the data should be able to capture the new column. No need extra step to add column

Incentivized

because we find out that DSX results have improved our approach to the whole subject (data, models, procedures)

Incentivized

As this is not a compulsory tool in our organization, I would say all depends on the decision makers, however since this is a part of MS Office, I am sure we will have it for as long as we will possibly need it. However, I would not be so sure, if it was a separate product

-Easy to distribute information throughout the enterprise using the webplayer. -Ad hoc analysis is possible throughout the enterprise using business author in the webplayer or the thick client. -Low level of support needed by IT team. Access interfaces with LDAP and numerous other authentication methods. -Possible to continually extend the platform with JavaScript, R scripts, HTML, and custom extensions. -Ability to standardize data logic through pre-built queries in the Information Designer. Everyone in the enterprise is using the same logic -Tagging and bookmarking data allows for quick sharing of insights. -Integration with numerous data sources... flat files, data bases, big data, images, etc. -Much improved mapping capability. Also includes the ability to apply data points over any image.

The UI flawlessly merges this offering by providing a neat, minimal, responsive interface

Incentivized

I find OneNote incredibly usable. I'm fairly middle of the road when it comes to tech savvy-ness. The platform was very easy to learn and explore. I like that OneNote is no clunky and offers a clean interface. This is important when it comes to deciding if a tool is usable for multiple people.

Incentivized

Basic tasks like generating meaningful information from large sets of raw data are very easy. The next step of linking to multiple live data sources and linking those tables and performing on the fly analysis of the imported data is understandably more difficult.

Incentivized

From time to time there are services unavailable, but we have been always informed before and they got back to work sooner than expected

Incentivized

Even though, it's a rather stable and predictable tool that's also fast, it does have some bugs and inconsistencies that shut down the system. Depending on the details, it could happen as often as 2-3 times a week, especially during the development period.

Never had slow response even on our very busy network

Incentivized

Overall, I rate OneNote's performance highly. In general, notebooks, sections and pages load quickly. OneNote integrates with other apps and info ca easily be shared/copied to and from the tool to other tools. Moreover, Notebooks tend to sync quickly meaning shared notebooks are up to date almost immediately provided there are no syncing issues.

Incentivized

Generally, the Spotfire client runs with very good performance. There are factors that could affect performance, but normally has to do with loading large analysis files from the library if the database is located some distance away and your global network is not optimal. Once you have your data table(s) loaded in the client application, usually the application is quite good performance-wise.

I received answers mostly at once and got answered even further my question: they gave me interesting points of view and suggestion for deepening in the learning path

Incentivized

Since it is part of Microsoft Office and used across the globe there are a lot of support options available. It's quickest to just do a google search which will have plenty of articles to help you since there are so many OneNote users but as an Office customer you also have access to Microsoft support and I have had good experiences with their support (probably because I'm with a large company who is a large customer to them).

Incentivized

Support has been helpful with issues. Support seems to know their product and its capabilities. It would also seem that they have a good sense of the context of the problem; where we are going with this issue and what we want the end outcome to be.

Incentivized

The trainers on the job are very smart with solutions and very able in teaching

Incentivized

The instructor was very in depth and provided relevant training to business users on how to create visualizations. They showed us how to alter settings and filter views, and provided resources for future questions. However, the instructor failed to cover data sources, connecting to data, etc. While it was helpful to see how users can use the data to create reports, they failed to properly instruct us on how to get the dataset in to begin with. We are still trying to figure out connections to certain databases (we have multiple different types).

Incentivized

The Platform is very handy and suggests further steps according my previous interests

Incentivized

The online training is good, provides a good base of knowledge. The video demonstrations were well-done and easy to follow along. Provided exercises are good as well, but I think there could be more challenging exercises. The training has also gone up in price significantly in the last 3 years (in USD, which hurts us even more in Canada), and I'm not sure it is worth the money it now costs (it is worth how much it cost 3 years ago, but not double that.)

Incentivized

It surprised us with unpredictable case of use and brand new points of view

Incentivized

The original architecture I created for our implementation had only a particular set of internal business units in mind. Over the years, Spotfire gained in popularity in our company and was being utilized across many more business units. Soon, its usage went beyond what the original architectural implementation could provide. We've since learned about how the product is used by the different teams and are currently in the middle of rolling out a new architecture. I suggest:

• Have clearly defined service level agreements with all the teams that will use Spotfire. Your business intelligence group might only need availability during normal working hours, but your production support group might need 24/7 availability. If these groups share one Spotfire server, maintenance of that server might be a problem.
• Know the different types of data you will be working with. One group might be working with "public" data while another group might work with sensitive data. Design your Library accordingly and with the proper permissions.
• Know the roles of the users of Spotfire. Will there only be a small set of report writers or does everyone have write access to the Library?
• ALWAYS add a timestamp prompt to your reports. You don't want multiple users opening a report that will try and pull down millions of rows of data to their local workstations. Another option, of course, is to just hard code a time range in the backing database view (i.e. where activity_date >= sysdate - 90, etc.), but I'd rather educate/train the user base if possible.
• This probably goes without saying, but if possible, point to a separate reporting database or a logical standby database. You don't want the company pounding on your primaries and take down your order system.

The main reason I personally changed over from Azure ML Studio is because it lacked any support for significant custom modelling with packages and services such as TensorFlow, scikit-learn, Microsoft Cognitive Toolkit and Spark ML. IBM Watson Studio provides these services and does so in a well integrated and easy to use fashion making it a preferable service over the other services that I have personally used.

Incentivized

I tried using Evernote and it is an equally usable tool, however, I prefer the interface and capabilities of OneNote. OneNote seems much easier to use and understand. I think that may primarily be because OneNote is a Microsoft application and I am very used to using Microsoft applications such as Word, Excel, etc. I also use OneNote to keep my grocery list. It does as good of a job as the grocery list applications out there, only I like the flexibility I have with OneNote and how I specifically do my shopping.

Incentivized

Spotfire is significantly ahead of both products from an ETL and data ingestion capability. Spotfire also has substantially better visualizations than Power BI, and although the native visualizations aren't as flexible in Tableau, Spotfire enables users to create completely custom javascript visaualizations, which neither Tableau or Power BI has. Tableau and Power BI are likely only superior to Spotfire with respect to embedded analysis on a website.

It helped us in getting from 0 to DSX without getting lost

Incentivized

In an enterprise architecture, if Spotfire Advanced Data services(Composite Studio),data marts can be managed optimally and scalability in a data perspective is great. As the web player/consumer is directly proportional to RAM, if the enterprise can handle RAM requirement accomodating fail over mechanisms appropraitely, it is definitely scalable,

Incentivized

• Could instantly show data driven insights to drive 20% incremental revenue over existing results
• Still don't have a real use case for unstructured data like twitter feed
• Some of the insights around user actions have driven new projects to automate mundane tasks

Incentivized

• OneNote has become our organizational standard method of taking electronic notes (though some still prefer pen and paper.) It has been a zero cost outlay due to its freely available nature.
• Its integration with other Microsoft Office products makes it easy to share notes and content between products, allowing for easy collaboration where needed.
• OneNote's integration with OneDrive ensures that individual's notes are always safe and secure, taking away the tedious responsibility of backup from the user, and makes it happen seamlessly in the background.

Incentivized

• It is costly, so not suitable for small scale implementations.
• Dashboards are as good as the developer, so need experience to get most out of it
• You need to be on Spotfire 11 at least to implement out of the box visualizations
• Integration with Python and R is a game changer, it comes very handy to onboard data scientists without much hassle
• performance is exceptionally well.
• Secure

Incentivized