In my (admittedly limited) experience, you'll probably run into some of the same issues with QlikView being "expensive, ugly, and completely lacking in statistical tools".

I have deep experience in the QlikView (QV) platform, so I can address some of the points in your experience:

> expensive

QV is not free, that's for sure. You'll be spending tens of thousands of dollars for the one-time license fee, as well 20% yearly maintenance. On the other hand, you'll be saving thousands of hours of engineering effort by not reinventing the hundreds of wheels already in the platform. Don't succumb to "not invented here" syndrome.

Check out a few dashboards I designed in just a day total [1], or the vendors demos of Twitter data [2], HealthData.gov data [3], or Salesforce.com data [4].

> ugly

If you are a first time user, the default visualizations are ugly, no doubt. But for someone with design skill, the visualizations can be made quite beautiful. For wanting more tools, just add your favorite JS library and HTML to make a custom visualization.

> completely lacking in statistical tools

Fortunately, QV can link with R, allowing you to all the advanced capabilities you need. Need something more specific? Throw a microservice REST API on top of your desired application, and load that in through a GET request. There are Hadoop connectors also built in.

One thing that people often don't realize when comparing Tableau and QV, is that QV is a platform, as opposed to Tableau being just a visualization tool. QV includes ETL, task scheduling, and an in-memory analytics database.

[1]: https://imgur.com/a/3Tzni

[2]: http://us-d.demo.qlik.com/detail.aspx?appName=Social%20Media...

[3]: http://us-d.demo.qlik.com/detail.aspx?appName=Epidemiology%2...

[4]: http://us-d.demo.qlik.com/detail.aspx?appName=Salesforce.qvw

I have to agree with this assessment. Qlikview does ETL very well.

Regarding the statistics portion of your comment, QlikView has built in functions in the load script for chi squared, t and z tests (including confidence intervals), linear regression, least squares, residuals, r squared, F statistic, etc. It doesn't offer the breadth that you may get from SAS or R (especially with R's CRAN packages), but it should be sufficient for dashboard level reporting.

Can it do histograms easily? I never needed to use it to do this but I had a friend who wanted to use it for this and the process was rather horendous.

Anyone know when the next version of Qlikview is being released? Or is it going to be Qliksense all the way now?

Yes, QlikView can do histograms easily. They're basically bar charts where the expression is counted, not summed, with the width between bars set to zero. They're not labeled as histograms in QlikView, which may be why there was some confusion.

You can hook it up with R though.

I can second this. Qlikview is pretty awesome.

Except when it crashes and loses 5 hours of work, even though I was saving diligently.

Personally, I have never experienced that issue, after 4 years of working with the software. Diligent saving always takes care of the issue. There are also "Backup" and "Auto Recover" settings. You could backup the most recent 5 saves, and have Auto Recover trigger every 15 minutes. Losing 5 hours of work should never happen with all those tools to prevent it.

I did enable auto-recover but Qlikview has a tendency to bring up a prompt asking me if I want to recover files even when this wasn't necessary.

I'm very glad that YOU never experienced that issue. The issue occurred, for some reason, because Qlikview paused after a load and before it refreshed the screens and displayed a prompt that allows you to add select boxes. I thought it was ready, and I saved the file.

The fact remains that I saved diligently, and the software became unstable and lost all my work. But I guess you e never had that experience before, always fun though when some smart-arse tells you that something shouldn't happen but it does happen.

This happens to me in Spotfire any time I'm messing with calculated values. So annoying.