Google Says: Americans More Patriotic Since 9/11

America is a patriotic nation. Notwithstanding the definite upsurge in the period following 9/11/2001 ten years ago, overall the level of American patriotism tends to remain remarkably consistent. Polls support this statement, as reported in a Forbes article last year:

Patriotic attitudes are generally very stable. In a question Gallup asked in January 2001, 87% said they were "extremely" or "very" proud to be American. When Pew repeated the identical question last year, 86% gave that response. In 2001 and 2009, only 1% said they were "not at all proud." The 9/11 tragedy produced more overt displays of patriotism and heightened sentiment, but responses soon returned to the norm.

So how did 9/11 impact American patriotism? Back in 2005, an MSNBC article reported the results of a poll conducted by the Roper Reports unit of NOP World. NOP’s vice president of consumer trends was quoted as saying:

“We tracked patriotism, spirituality and religion, and giving to charities and volunteerism right after 9/11,” Silvers said. “All three popped up. Within about nine months, volunteering was down and so was religion, but what has stayed with us is patriotism, and it’s obviously fueled by a couple of things. The shift point was 9/11.”

As are most of the folks working at my BI software development company (SiSense), I could be called obsessed when it comes to applying business intelligence methodologies to anything. In this spirit, I automatically started thinking about how I might be able to uncover some trends showing if and how actual data might support the articles and surveys I saw about American patriotism and 9/11, as the ten-year anniversary of the 9/11 tragedies approached.

I decided to take a look at Google search data and see if and how online searches reflect the “patriotism effects” of 9/11 in America. After looking around and reading some more, I came up with two searches to check out: flag sales and volunteering.

What led me to check out flag sales? I saw a recent article that says that, “One response to the catastrophic events of Sept. 11, 2001, came quickly in a traditionally American way -- flag sales soared.” The article quotes the president of Gettysburg Flag Works in New York State as saying, “‘On 9/11, 12, 13, 14, we sold out everything that was red, white and blue. We had lines out the door,’ recalled Mike Cronin, president of Gettysburg Flag Works. “I was in flag shock for a couple of weeks.’”

Not surprisingly, a sharp increase in searches related to flag sales can be seen in Google search data in the month of September 2001. For the years following 2001, however, searches for flag sales were relatively flat.

 Flags Sales 2001

 Flags Sales 2007

Interestingly, though, this year’s tenth anniversary of the 9/11 attacks seems to be resonating more with Americans than on previous anniversaries: flag sale searches increased significantly over the past few weeks.

 Flags Sales 2011

When I went looking for articles which might discuss the increase in community service and volunteering among Americans, I didn’t find much. However, a look at Google search data for “volunteer USA” shows an interesting consistency with what I saw for flag sales searches: significant spikes in searches after the original 9/11 and then again this year.

US Volunteers 2001

US Volunteers 2009 

US Volunteers 2011

From the graphs above it is quite clear that the 10th anniversary of 9/11 has a great impact on patriotism, even more so than years before.

In any case, it’s hard to believe that ten years have passed since thousands of Americans died on 9/11. Hopefully, America is stronger as a country for it and its people are stronger as a nation. In case you feel like reading more about how patriotism has increased in the US since 9/11/01, I leave you with the following article, published this week in a Florida newspaper, which talks about American patriotism (and the difficulty in measuring it with surveys): Since 9/11: Patriotism - Ten years after the deadliest terrorist attack inside the United States, love of country remains as strong as ever, if not a little stronger.

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By: Roi Hildesheimer | The ElastiCube Chronicles - Business Intelligence Blog

The In-Memory Technologies Behind Business Intelligence Software

If you follow trends in the business intelligence (BI) space, you’ll notice that many analysts, independent bloggers and BI vendors talk about in-memory technology.

There are technical differences that separate one in-memory technology from another, some of which are listed on Boris Evelson’s blog.

Some of the items on Boris’ list are just as applicable to BI technologies that are not in-memory (‘Incremental updates’, for example), but there is one item that merits much deeper discussion. Boris calls this characteristic ‘Memory Swapping’ and describes it as, What the (BI) vendor’s approach is for handling models that are larger than what fits into a single memory space.

Understanding Memory Swapping

The fundamental idea of in-memory BI technology is the ability to perform real-time calculations without having to perform slow disk operations during the execution of a query. For more details on this, visit my article describing how in-memory technology works.

Obviously, in order to perform calculations on data completely in memory, all the relevant data must reside in memory, i.e., in the computer’s RAM. So the questions are: 1) how does the data get there? and 2) how long does it stay there?

These are probably the most important aspects of in-memory technology, as they have great implications on the BI solution as a whole.

Pure In-Memory Technology

Pure in-memory technologies are the class of in-memory technologies that load the entire data model into RAM before a single query can be executed by users. An example of a BI product which utilizes such a technology is QlikView.

QlikView’s technology is described as “associative technology.” That is a fancy way of saying that QlikView uses a simple tabular data model which is stored entirely in memory. For QlikView, much like any other pure in-memory technology, compression is very important. Compressing the data well makes it possible to hold more data inside a fixed amount of RAM.

Pure in-memory technologies which do not compress the data they store in memory are usually quite useless for BI. They either handle amounts of data too small to extract interesting information from, or they break too often.

With or without compression, the fact remains that pure in-memory BI solutions become useless when RAM runs out for the entire data model, even if you're only looking to work with limited portions of it at any one time.

Just-In-Time In-Memory Technology

Just-In-Time In-Memory (or JIT In-Memory) technology only loads the portion of the data into RAM required for a particular query, on demand. An example of a BI product which utilizes this type of technology is SiSense.

Note: The term JIT is borrowed from Just-In-Time compilation, which is a method to improve the runtime performance of computer programs.

JIT in-memory technology involves a smart caching engine that loads selected data into RAM and releases it according to usage patterns.

This approach has obvious advantages:

1. You have access to far more data than can fit in RAM at any one time
2. It is easier to have a shared cache for multiple users
3. It is easier to build solutions that are distributed across several machines

However, since JIT In-Memory loads data on demand, an obvious question arises: Won't the disk reads introduce unbearable performance issues?

The answer would be yes, if the data model used is tabular (as they are in RDBMSs such as SQL Server and Oracle, or pure in-memory technologies such as QlikView), but scalable JIT In-Memory solutions rely on a columnar database instead of a tabular database.

This fundamental ability of columnar databases to access only particular fields, or parts of fields, is what makes JIT In-Memory so powerful. In fact, the impact of columnar database technology on in-memory technology is so great, that many confuse the two.

The combination of JIT In-Memory technology and a columnar database structure delivers the performance of pure in-memory BI technology with the scalability of disk-based models, and is thus an ideal technological basis for large-scale and/or rapidly-growing BI data stores.

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By: Elad Israeli | The ElastiCube Chronicles - Business Intelligence Blog