Coremetrics / IBM Digital Analytics (discontinued) vs. Tableau Desktop

IBM analytics has continued to improve upon the days of being the original core metrics. After using the updated version for quite some time, it has been great at providing the needed analytics to measure ROI and goal performance for our quarterly KPI's. It has resulted in a great increase in web engagements although we are a midsize company, smaller outfits may not need such an expensive option.

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The best scenario is definitely to collect data from several sources and create dedicated dashboards for specific recipients. However, I miss the possibility of explaining these reports in more detail. Sometimes, we order a report, and after half a year, we don't remember the meaning of some data (I know it's our fault as an organization, but the tool could force better practices).

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• IBM CXA comprises an acquisition called Tealeaf. This tool has deep heritage and this is evident in its present-day capabilities.
• The Universal Behaviour Exchange or UBX puts the concept of personalisation at the forefront. The ability to combine physical (analog) and digital transactions to create the complete picture of a customer journey, is a stand out benefit.
• The solution does not have to involve the purchase of software. IBM CXA can be sold as a service bundled with analytics as a service. This not only lowers the cost of ownership, it gets around one of the principal issues. Strong staff with design and analytical capability to drive the solution and deliver tangible benefits.
• The seamless integration of Watson AI services to help with the heavy lifiting. Watson reinforces the analytical focus this solution has and can learn to recognise situations specific to a company.

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• An excellent tool for data visualization, it presents information in an appealing visual format—an exceptional platform for storing and analyzing data in any size organization.
• Through interactive parameters, it enables real-time interaction with the user and is easy to learn and get support from the community.

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• The user interface is in Flash, which can be very frustrating and slow at times. Apparently, this is to be transitioned in a future release.
• Can only segment the last 93 days of data. Any historical segmentation beyond the 93 days must be run in Explore (which is credit based, and has its own limitations with the number of credits per month, based on the initial contract with IBM).
• Reports can only display 93 days of data at a given time for custom date ranges. There are pre-programmed date ranges setup with IBM during implementation (last week, last month, last quarter etc.), but are not flexible enough to answer more specific questions.
• Certain reports cannot have segments applied, making answering some simple questions a bit more tricky. For example, I can create a segment around mobile devices and apply it to the marketing channels report, but I can't create a marketing channel segment and apply it to the mobile reports.
• Built in API calls allows for nice report design and automation.

• Pricing should be more user-friendly and usage-driven
• Making edits to the production reports is fairly tough and has a vast scope of additional capabilities
• Tableau Desktop should be able to differentiate itself from the Tableau server else there is no major meaning of two different products being offered

IBM Digital Analytics is a great solution for our clients and I believe they offer the best solution for the retail space. We have access to IBM support via email or live chat and they can answer many of the reporting questions that come up. IBM is receptive to our feedback of the product so I am confident they will continue making improvements

Our use of Tableau Desktop is still fairly low, and will continue over time. The only real concern is around cost of the licenses, and I have mentioned this to Tableau and fully expect the development of more sensible models for our industry. This will remove any impediment to expansion of our use.

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Very easy to implement and use.

Tableau Desktop has proven to be a lifesaver in many situations. Once we've completed the initial setup, it's simple to use. It has all of the features we need to quickly and efficiently synthesize our data. Tableau Desktop has advanced capabilities to improve our company's data structure and enable self-service for our employees.

Never had any issues

When used as a stand-alone tool, Tableau Desktop has unlimited uptime, which is always nice. When used in conjunction with Tableau Server, this tool has as much uptime as your server admins are willing to give it. All in all, I've never had an issue with Tableau's availability.

As reports are templated, the system is pretty quick. Sometimes you have to wait a bit for a report to render. Or you might have to re-load the page. But there is no real issue here and the system is on par with other similar systems.

Tableau Desktop's performance is solid. You can really dig into a large dataset in the form of a spreadsheet, and it exhibits similarly good performance when accessing a moderately sized Oracle database. I noticed that with Tableau Desktop 9.3, the performance using a spreadsheet started to slow around 75K rows by about 60 columns. This was easily remedied by creating an extract and pushing it to Tableau Server, where performance went to lightning fast

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Overall, the level of support is very good and I would say it is a strong asset of the solution. However, you can sometimes feel that there is a difference of level among the support team.

Tableau support has been extremely responsive and willing to help with all of our requests. They have assisted with creating advanced analysis and many different types of custom icons, data formatting, formulas, and actions embedded into graphs. Tableau offers a weekly presentation of features and assists with internal company projects.

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It is admittedly hard to train a group of people with disparate levels of ability coming in, but the software is so easy to use that this is not a huge problem; anyone who can follow simple instructions can catch up pretty quickly.

Online training is really great. One of the best assets that they have. Lots of great videos, pop quizzes at the end of each module. Fantastic. Other tools have similar features, but not as good.

I think the training was good overall, but it was maybe stating the obvious things that a tech savvy young engineer would be able to pick up themselves too. However, the example work books were good and Tableau web community has helped me with many problems

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See previous comment: reading and understanding the encyclopedic implementation guide is a must.

Again, training is the key and the company provides a lot of example videos that will help users discover use cases that will greatly assist their creation of original visualizations. As with any new software tool, productivity will decline for a period. In the case of Tableau, the decline period is short and the later gains are well worth it.

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Much of the work we did in IBM Digital Analytics could have been answered through Google Analytics, a much simpler, agile and FREE solution set. Not mention, given the vast number of Google Analytics USERS, free and actionable support is simply a click away ... this compared to IBM Digital Analytics fractured and often absent support service.

I have used Power BI as well, the pricing is better, and also training costs or certifications are not that high. Since there is python integration in Power BI where I can use data cleaning and visualizing libraries and also some machine learning models. I can import my python scripts and create a visualization on processed data.

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This solution can support large amount of data and transaction. The way that user management features are built, it shows it is meant for large organizations.

Tableau Desktop's scaleability is really limited to the scale of your back-end data systems. If you want to pull down an extract and work quickly in-memory, in my application it scaled to a few tens of millions of rows using the in-memory engine. But it's really only limited by your back-end data store if you have or are willing to invest in an optimized SQL store or purpose-built query engine like Veritca or Netezza or something similar.

• We spend too much time trying to work around bugs on the new UI.
• We spend too much time trying to figure out how to make certain segments work because support and the knowledge center are lackluster.
• Our sales rep is very unresponsive and leaves us searching for a lot of answers on our own, including what other products we may benefit from that IBM offers.

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• Tableau was acquired years ago, and has provided good value with the content created.
• Ongoing maintenance costs for the platform, both to maintain desktop and server licensing has made the continuing value questionable when compared to other offerings in the marketplace.
• Users have largely been satisfied with the content, but not with the overall performance. This is due to a combination of factors including the performance of the Tableau engines as well as development deficiencies.

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