NetApp FAS series vs. Tableau Desktop

It is very easy to use with NFS. Creating new volumes and mounting to servers such as ESXi or Linux is a breeze. It does also support CIFS but it is far less intuitive and requires much more effort. Replicated data is also very simple and robust in the form of SnapVaults or SnapMirrors. This data is either immediately or periodically replicated to a peer FAS in the cluster for retention.

Tableau Desktop is one the finest tool available in the market with such a wide range of capabilities in its suite that makes it easy to generate insights. Further, if optimally designed, then its reports are fairly simple to understand, yet capable enough to make changes at the required levels. One can create a variety of visualizations as required by the business or the clients. The data pipelines in the backend are very robust. The tableau desktop also provides options to develop the reports in developer mode, which is one of the finest features to embed and execute even the most complex possible logic. It's easier to operate, simple to navigate, and fluent to understand by the users.

• The selling point for NetApp FAS is the application and data protection integration capabilities they provide.
• We have been able to use NetApp FAS in a variety of use cases with a standard set of management tools.
• NetApp FAS has evolved over the years from just NAS to also include block protocols. At this time they support almost all industry standard protocols.

• 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.

• Deduplication job runs at certain times and creates a large CPU overhead for the system
• Management of a volumes, disk groups, LUNs, etc. is a burden to manage and is not efficient with storage capacity
• Upgrades are complicated and not "non-disruptive"

• Formatting the data to work correctly in graphical presentations can be time consuming
• Daily data extracts can run slowly depending on how much data is required and the source of the data
• The desktop version is required for advanced functionality, editing on [the] Tableau server allows only limited features

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.

It does have a really nice and easy to use web interface to do pretty much anything you need with it. It was very simple to configure our volumes and luns and connect them to our VMWare environment using the interface. It has options to rename, shrink, grow, and other things with our luns and volumes. It was nice and easy to read graphs to see where you stand on your storage usage at a glance.

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.

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.

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

NetApp support in Brazil is managed by its partners. We know in other countries, such as the US and NO, they have support directly from Netapp. We have a very good NetApp partner working with us since the beginning, on both the implementation and daily support. Very few cases needed to be escalated to NetApp support, most of the cases are handled and satisfyingly closed by the partner.

I have never really used support much, to be honest. I think the support is not as user-friendly to search and use it. I did have an encounter with them once and it required a bit of going back and forth for licensing before reaching a resolution. They did solve my issue though

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.

The training for new users are quite good because it covers topic wise training and the best part was that it also had video tutorials which are very helpful

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.

NetApp stacked nicely and gave enterprise-level usability for snapshot-based backups. Our previous RPO was several hours. It was selected prior to me arriving at the company, but It was selected for the hardware refreshes due to its compatibility with several other vendors, like CommVault and VMware.

If we do not have legacy tools which have already been set up, I would switch the visualization method to open source software via PyCharm, Atom, and Visual Studio IDE. These IDEs cannot directly help you to visualize the data but you can use many python packages to do so through these IDEs.

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.

• The speed of file recovery is the biggest positive impact. Recovering from a ransomware attack in minutes is something you can certainly brag about.
• Integration with products like Exchange and SQL can certainly speed up normal day to day processes. Not just in backup recovery situations either.
• Redundant paths make migrations and updates very easy with no downtime.

• 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.