Getting out of the Weeds

Warning: This blog is more technical than our usual blog entries, but it serves to explain the value (and power) of Birst.

Ok, now that we understand that calculations in Birst occur at two different levels, what does Birst expression flavor #1 for physical queries and pre-aggregation expressions buy us?

Off the Beaten Path (In the Weeds)

Warning: This blog is more technical than our usual blog entries, but it serves to explain the value (and power) of Birst.

Sometimes answering a simple question can lead us into the weeds. And that can be a good thing—as long we have a good weed whacker.

I spend entirely too much time in airports and on airplanes. If you do as well, you’ve no doubt seen the “10 of the top 10 [insert industry] firms run on [insert vendor]” ads papering airport billboards and inflight magazines.

Those smart marketers at [insert vendor] are relying upon your ability to draw some sort of cause/effect conclusion and to consider them for your next IT project.

The biggest gift in Silicon Valley this Christmas was the one given by the stock market to Oracle Computer for the latter’s ‘promising’ new Cloud Computing service. As the San Jose Mercury-News reported on December 19th:

The power of foresight

On December 21st, 2012, the more than 5,000-year old Mayan calendar comes to an end. Many doomsday believers predict that this day will mark the end of the world. That’s certainly powerful foresight if it turns out to be true.

“Cloud Computing” was the hot technical term in 2012. Everywhere you looked, articles were being written, conferences held. . . and it seemed as if every company you knew was announcing that it was moving its information storage program from in-house servers up to the ‘cloud.’

Ask Different.

It’s hard to get creative about reporting. Analysis is, by its very nature, a standard set of processes, so drawing innovative conclusions from something so notoriously static can be incredibly difficult.

The way to break through this impasse is by thinking less about the data you are collecting and more about the questions you are asking.

Generally, when we think about data and data analysis, we think about complex cross-relational insights, slicing and dicing data hoping to learn how to shave microseconds off of a production time, or something equally complicated and seemingly out of reach.

Surprisingly, some of the most insightful and effective implementations of business analytics are in customer-facing departments, like marketing.

Big Data has reached a tipping point. It is now officially the hot new technology industry of the second decade of the 21st century. And there were 70,000 witnesses to the moment it happened.

How do you know when a new technology becomes cool? When everybody who is anybody in tech feels obliged to attend its trade show.

According to Gartner's recent 2012 Hype Cycle for Emerging Technologies, Big Data is just about to hit its "peak of inflated expectations." For those unfamiliar, Gartner's hype cycle purports to "highlight the common pattern of over-enthusiasm, disillusionment and eventual realism that accompanies each new technology and innovation”. Meaning, when a technology is just nearing the top of the hype curve, such as Big Data is, we're all about to be disappointed. With the big buzz around big data, what can we truly expect? Big returns or truly big hype?

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