Lumar vs. Tableau Desktop

If someone is looking for a SEO tool that excels in finding technical issues for a site, Lumar is a fantastic choice. Not only does it outline everything that's wrong, it does a much better job than other tools as to showing you how it the issue is presented. For instance many tools could outline a temporary redirect on your site, but Lumar will show you where that redirect starts, if there's a chain involved, and why it's worth fixing

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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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• Really good to understand when and where any issues are on the website
• Helps full breakdowns for each website, to understand where to improve
• Helps work out where content etc needs to be optimised, which can then be passed to the content team

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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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• I find the loading panel during a crawl to be a bit deceptive. It's very hard to tell how long a crawl will take—a more accurate estimate would go a long way.
• I love the "fetch time" tab in theory, but I have a hard time believing it—not that the figure they give is untrue, but I find it at wide variance with other tools. PageSpeedInsights will have a site looking disastrous and DeepCrawl will log it all fetching "quick". But perhaps page speed is just notoriously difficult to assess.

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• 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

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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It's great once you know how to use it... That being said there can definitely be some hiccups trying to learn the program. Even when writing this review i originally gave it an 8 and realized how many things I didn't even know existed after using it for a couple of years. Not the best 'usability' if you can't even find all the features you might want to use.

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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

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I liked the platform overall. It is a good crawler. I no longer use because it's duplicate of what I get with seoClarity. I did not give it 10/10 because sometimes I had a hard time isolating site areas that I wanted and didn't get much technical support from Conductor on how to use the tool

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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.

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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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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All of the products I have used have been amazing in their own way, but DeepCrawl makes it easier to put it into visuals. Sometimes when you look at results, it can be quite difficult to get something easy to understand. DeepCrawl gets rid of that, the results are so easy to comprehend. I would recommend it to any data consultant (DC).

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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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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.

• Saves hours within the week on repetitive reporting and analytics
• Initial time was invested in setting up the account and trackers
• Suggestions and insights has helped improve digital marketing efforts from seo to sem

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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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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info