The desktop or laptop is now in decline, squeezed from one side by mobile platforms and from the other side by the cloud. As a developer of desktop software, I believe it is time to address the challenges to our viability. Is software for the desktop PC now the living dead, or zombieware?
Myth number 1: "The desktop is dead – my tablet can do it all"
It’s true. When most people use a PC, they use it for email, calendar, contacts, Web, social media and entertainment. All of these uses are great candidates to migrate to smart phones and tablets. Tablets are great for other things too, such as reading or playing games. The mobile computing market has exploded in the past 10 years. When I go on a trip, I often don't bring a laptop anymore because my tablet serves me just fine. Mobile computing has taken over. Demand for desktops is declining, replaced by mobile platforms.
But does a tablet work for analytics? Yes, in several important ways. Much of analytics involves scorecard metrics on a dashboard display, and the tablet is perfect for that. Even interactive analytics delivered to a mobile device works great. SAS Visual Analytics provides that. JMP Graph Builder for iPad delivers that for local data.
…And it’s false. But what if you want do deeper analytics, with models and large numbers of graphs? That doesn’t fit on a tablet. Mobile platforms are too small to hold all the data and software, and the display interface is small and not desktop-like. All of the interfaces are too simple – there is no right-click, no fine mouse-control. The file system is crude. The support environment is insufficient. Tablets are just not power tools for data analysis. While tablets have taken over for many of our personal computing needs, they have not taken over for analytics.
Myth number 2: “The desktop is dead – everything is in the cloud now”
It’s true. With the amazing emergence of high-speed Internet and cloud services, much that we used to do on individual computers now happens in the cloud. Services can be provided that are fast and very graphically interactive. Even through the Web, Ajax, Flash and HTML5 provide a rich interface to harness.
Information systems that used to be installed with great pain and effort on a home system can now be spun up quickly in a cloud service. Salesforce.com revolutionized customer information systems. Amazon EC2 and other cloud services can provide a rich set of software and services.
The cloud can also provide much deeper software implementations, making everything available without having to install anything. The cloud versions can be updated often with the latest fixes without any effort by the customer. The cloud has truly revolutionary potential.
…And it’s false. You already have a desktop computer, and probably a pretty powerful one. All you need is good software that installs easily. There is no need for a cloud service, one that you will have to pay for through the usage meter, often more than serving it yourself. The cloud reduces the installation burden associated with big IT systems, but personal analytics software does not have a high installation burden.
Desktop analytics software can provide a much richer and more interactive service, one that is free of usage charges.
Myth number 3: “The desktop is dead – you can’t do big data on the desktop”
It’s true. We live in an age of big data, when the data sets are measured in terabytes, and there are billions of rows. It is impractical to analyze data of this size on a desktop. You need a cluster of servers that can divide the work to be handled in parallel so that it takes only seconds, rather than hours or days to analyze.
Analytics is also more efficient when it is done close to where the data is; so if it is analytics from a database, putting the analytics close to the data speeds things up.
Analyzing big problems on a desktop may be too slow, and if the desktop depends on data being in memory, then you are limited to what fits in memory.
…And it’s false. Most analytic data sets fit just fine on a laptop. They are usually far less than a terabyte, usually less than a gigabyte. We also live in the golden age of desktops, when you can get a very powerful machine that is still inexpensive. You can get a laptop with 16-32 GB of memory and 4-8 CPU cores for a couple thousand dollars. Each additional 16 GB of memory costs less than $100.
Even big data can be done on a laptop if not too big. In my standard demo, I bring up a data set of all the airline flights over a 20-year period from the major US airlines. It is 123 million records. To load it takes 3-5 seconds from an SSD. To build a graph for it takes a few seconds for each drag-and-drop step. I can get a scatterplot of all the points in 10 seconds, and a regression with 65 parameters in 35 seconds. That is big data, and the PC is so capable that it is doing interactive analysis and graphics at this scale.
There are opportunities to use the desktop to be much faster yet. The graphics processing unit of the PC is actually much more powerful than the main CPUs, though most software doesn’t use it. Take the lowest end of the newest Mac Pro. It has 4 cores and 2,560 GPU cores and is rated at 4 Teraflops. The high-end Mac has 12 GB of graphics memory and 4,096 stream processors capable of churning out calculations at 7 Teraflops. This is supercomputer performance in desktop machines that cost only $2,000-$4,000 dollars.
If my problems change from a few gigabytes to a few terabytes, then I would be ready to give up on my laptop and switch to a server cluster. Most analytic problems are smaller than terabytes.
Myth number 4: “The desktop is dead – you don’t need it for good graphics”
It’s true. One of the best graphics presentations I have seen is Hans Rosling’s TED talk, and that was all done with Flash on the Web. SAS Visual Analytics proves that interactive graphics can be done easily through a Web page, and it is almost instantly interactive, even when you have billions of rows of data.
…And it’s false. But real analyses are often not simple dashboards. They are large interactive documents with many graphs and many tables. With big data, scatterplots can have millions of points, and you want to be able to select points interactively. The Web services are just not up to the task. Furthermore, the Web-delivered graphics services are not fully mature. Flash is good, but it is slowly disappearing because it isn’t supported on Apple mobile devices. HTML5/JavaScript works, but it still has yet to mature into a good environment to support a rich complex graphical system.
Dreams do come true
We live in a world of computing where dreams come true. The mainframe bows to the minicomputer. The minicomputer bows to the personal computer. The personal computer bows to the tablet and smart phone. It seems as if these will soon bow to the smart watch or smart glasses. But at each step along the way, some applications find their best home – and other applications as well as new applications find the more convenient and smaller home better.
Data analysis needs a great computing engine and a great large display. The desktop is probably going to remain the best home for rich interactive analytics. There will be other good places to do dashboard analytics, and better places to do massive problems of large complex analytic systems, close to databases. But the desktop remains a completely viable platform for analytics. So let’s keep our desktops and laptops, our PCs and Macs. They are amazingly good at what they do.
Note: This is part of a Big Statistics series of blog posts by John Sall. Read all of his Big Statistics posts.
