Are Desktop BI Tools Worth Having - And Which One Should I Use?

We are in a world where cloud is king. All of the major business intelligence software providers (Oracle, Qlik, Microsoft, Tableau etc.) have ramped up their cloud offerings – meaning that thousands of employees across many time zones can access a “single version of the truth” for an extremely fair price. With serverless computing stampeding ahead, we don’t really take time to think about desktop data exploration using tools such as Oracle Data Visualization Desktop, Qlik Sense Desktop, or Tableau.

There is a lot of value in desktop data exploration – here’s a possible scenario;

A marketing team has just run a trial for a potential campaign on a selected focus group. This means there’s a small amount of data that needs to be analysed in order to test the efficacy of the campaign. Does it make sense to invest hundreds of pounds in business analysts/BI Consultants in order to build a dashboard for this trial on existing cloud infrastructure? Probably not! But with some training, the marketing team can use a desktop solution in order to quickly put together some dashboards that can be used to present and share the results of their trial in an easy to read format.

So, although cloud infrastructures are amazing at large scale deployments, in some instances it’s just not worth clogging up your architecture for every small-scale project – this is where desktop tools come into their own.

As far as which tools to use are concerned – there are a variety of desktop tools that are worth looking at, some of the more popular being; Oracle Data Visualization Desktop, Qlik Sense Desktop, Tableau Desktop, and Microsoft Power BI Desktop.

Oracle Data Visualization Desktop

Oracle Data Visualization Desktop (ODVD) is a great add-on for organisations that already have existing Oracle architecture. I have used it in a few projects, and it is definitely a powerful tool. It has 4 sections; Projects (where users create their dashboards), Data (where users load and create data sets), Machine Learning (where users can upload ML scripts), and a Console (where users can upload plugins and skins).

The standout feature of ODVD is the data flow section. Using data flow, users can add, remove, transform, and create columns as well as unioning or joining data sets together. This makes queries run more quickly and is a simple way of aggregating data.

There are only a couple of issues that I have run into with ODVD one being that it is quite resource hungry (like Google Chrome on steroids), and the other being that it’s not exactly straightforward to share/collaborate on projects (but for individual exploration, this isn’t massively problematic).

Qlik Sense Desktop

Qlik Sense has a beautiful interface and is extremely quick. One of the major benefits of Qlik Sense Desktop is that you can get it for free when you sign up for a Qlik account. It is also majorly customisable – you can code most things (such as colour schemes, themes etc.) and there is also a guide on Qlik’s website on how to build your own visualizations.

Sharing-wise, it’s really easy to share projects with other users within a team, using something called a stream.

The only downside to using Qlik would be the language used – it’s not as widely used as Oracle SQL and is a little bit tricky to understand, but once you get used to it, it’s simple enough! For me, the speed and UI more than makeup for the language.

Tableau Desktop

Tableau Desktop is an extremely popular desktop data visualizer. Tableau has evolved since it’s inception in 2003 to become a market leader in the data visualization area. It’s no surprise because it’s a great tool – users connect to common data sources or load local files and then it’s a case of dragging and dropping visualizations onto canvases. For sharing, you can upload your projects to Tableau Server where others can access the visualizations you create.

Data transformation wise there is a small “data flow” section which isn’t as robust as the one in ODVD, but it’s definitely very effective for making small changes to the data sets that you load into the application.

Again, Tableau’s language isn’t as commonly used as SQL but it’s quite easy to get the hang of. It also has a really effective and useful mobile app, that is as functional as it’s desktop counterpart.

Microsoft Power BI Desktop

Power BI is rapidly leapfrogging it's competition as a market leader. You can get a free version of Power BI from Microsoft’s website; this includes projects that have less than 2GB of data – however, you can’t share those projects without getting a pro license.

When using the full stack of Microsoft’s analytics tools (e.g. including Azure) Power BI comes into it’s own as it easily plugs into any Microsoft architectures.

I find that the data transformation facilities available in Power BI desktop aren’t as powerful or as simple to use as it’s counterparts, and navigation isn’t as easy – however it is cheaper and produces just as effective visualisations as the others. It’s also much easier to integrate with a large variety of data sources and isn’t greedy with computing resources.

So what happens when you need to migrate from your desktop tool to your existing cloud infrastructure? Have no fear, all the above tools have cloud counterparts. You can upload projects that you build within these tools to the cloud for others to access.

Let this article be a reminder that although cloud and serverless computing is a wonderful thing that’s saving us lots of money and time, the desktop counterparts also have their place in your BI solution!

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