Spotfire vs. TARGIT

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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Targit is very strong when the data is presented to the system. Because of this, we are able to report on almost all of the information that is valuable to us. When we have questions or ideas on how to better leverage Targit, they are great to work with. We track our sales progress/process in Targit and AP tracks things such as outstanding invoices, open invoices, etc

• 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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• Quick start-up and report turnaround time.
• Easy drag and drop capabilities as well as user friendly command options.
• Ability to share reports among other users making it easy to use an already created report and simply changing the criteria to suit your own needs.
• Ability to save a base report that can be modified as needed repeatedly, instead of recreating from scratch.
• Easy visual for final layout.
• Ability to run multiple reports within one screen without jumping around.

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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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• Probably one of our biggest complaints from the user community is the inability for the user to see the details behind the data. I know with the tool you can write reporting services reports that would allow users to see the detail by right clicking on a measure and selecting Actions, but for a very lean IT shop there simply has not been time to build these Actions for every possible scenario a user might want to see detailed reporting on.
• Another complaint I've heard is the inability for the user to know exactly what the data represents from the source. If Targit had maybe some type of capability to hover over a measure or dimension and see a pop up of a more detailed description this might help resolve that issue.
• The most difficult concepts to teach our users is how and when to use comparisons and the syntax for calculations. Creating comparisons has become much simpler with the 2k11 release but it is still difficult for my users.

-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.

It is very easy to use and I am proficient at this point to be able to figure out how to run most of the reports I need. I have had the time to "play around" in TARGIT and really teach myself about the visibility settings and other aspects - though other users have needed help with some of these aspects - but once you conceptually understand how to build the reports, it is very simple from a power user perspective.

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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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Everything on the back end needs to be correct, which sometimes it may not be set up or missing some variables. Some of the more difficult parts of Targit require a lot more attention and object creation to work properly

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.

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.

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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Everyone I've dealt with at Targit genuinely cares about me and my success, and they respond to questions quickly and accurately. There is literally nothing more I could ask for from their support.

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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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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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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.

Make sure all of the back end work is done prior to getting Targit set up. Every variable you may need for calculations needs to be correct and every item needs to be uniform so it is read properly.

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 really met our business requirements when we were searching for a reporting/Bi tool and the flexible business model of being able to introduce additional functionally as your organization grows and requires it made the investment decision the right one for us. The functionality available in comparison to the investment is well worth it.

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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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• 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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• We have been looking at our Product Hit Rate by Customer instead of just looking into Customer hit rate and adjusted our offerings accordingly.
• Giving people the ability to run their own ad-hoc reports rather than to request them from IT is a great benefit to my department.