Spotfire vs. ThoughtSpot

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.

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It is well suited when the same data is consumed by many different people with different analytics and visualization requirements because, if you have the data available in ThoughtSpot, every user can prepare different views. Also, it is a good reporting tool, you can get rid of slides if you have a good dashboard prepared, gaining flexibility and agility.

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• 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

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• Beautiful visualizations. The visuals are distinct, clean, and easy to discern from one another.
• Intelligent querying functionality. When looking to manipulate the data, the search function makes it easy to manipulate the features in the data, along with aggregating them in the way you'd like.
• Embedding! It has been a smooth process thus far for our product & technical teams to work with ThoughtSpot and bring it into our product.

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• 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

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• It would be great if ThoughtSpot can add the feature to filter by clicking on visualizations. i.e if I click on a particular data point in the chart if the full dashboard can filter just for that particular data point.
• Color coding the heatmap with different colors like green to orange to red.

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-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.

I give it just waiting because passport is brilliant and it has helped our organisation In advancing to the next stage in the age of AI. It has allowed or non-tech people to better service and clients in a cost-effective way. George port has allowed us to create new products for us and for our clients increasing our revenue streams and reducing clients churn

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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.

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The rating is because of the ease of use of the interface as it has a no code interface that makes it easy to setup data pipelines without extensive programming. Cloud native integration: It integrates seamlessly with cloud based data warehouses. Automated data loading, Scalability, Cost Effective, Transformations, Data Governance and security.

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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.

it's available unless there is a server or system update etc. sometimes the timing of this is bad (for example during a month end close)

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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.

It does what it is supposed to. Would be nice to have a bit more insights

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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.

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I give it this meeting because the team is not only help able to help us in the current solutions but also amazing and taking feedback and feeding it back to their development team which includes more products and features into ThoughtSpot

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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).

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inhouse in-person training. Took a bit to long to get the basics.

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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.)

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poor instructions

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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.

Understand use case and model and design accordingly

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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.

We also explored Tableau Ask Data. Tableau is our standard for BI in our organization. We want to use the smallest amount of tools in our company to have the best adaption. ThoughSpot will fill a few gaps that we have with our current set up and will also enhance out offering for our employees in the transition of being more data driven within in near future

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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,

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Because it is very reliable, inside the situation, we need strong internet connection to access a lot of data but easily never had any downtime except during the upgrades

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• 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

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• Time to market ROI is massive vs hiring the full-time dedicated team to build and maintain a frontend multi-tenant SaaS data viz product.
• It will be interesting to see over time how the advanced features play out in terms of usability and end value, such as Natural Search, which we are very excited about, and the machine learning tools.

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