An occasional series in which a review of recent posts on SmartData Collective reveals the following nuggets:
To make the most of analytics…
In-database/in-warehouse analytics will become more and more important and the analytical processing of streaming data likewise. However, the way data is stored in warehouses will have to change, too, not just the way analytics are done. Too many warehouses and marts today store summary data, rollups or data where the crucial time dimension is obscured. No matter how powerful the analytic engines get, this will have to change and warehouses will have to store the low-level transactional data that analytics need.
C’mon Google, what’s the algorthm?
Google makes 99% of their revenue by selling text ads for things like plane tickets, dvd players and malpractice lawyers. Many of these ads are syndicated to non-Google properties. But the anchor that gives Google their best “inventory” is the main search engine at Google.com. And the secret sauce behind Google.com is the algorithm for ranking search results. If Google is really committed to openness, it is this algorithm that …
An occasional series in which a review of recent posts on SmartData Collective reveals the following nuggets:
To make the most of analytics…
In-database/in-warehouse analytics will become more and more important and the analytical processing of streaming data likewise. However, the way data is stored in warehouses will have to change, too, not just the way analytics are done. Too many warehouses and marts today store summary data, rollups or data where the crucial time dimension is obscured. No matter how powerful the analytic engines get, this will have to change and warehouses will have to store the low-level transactional data that analytics need.
C’mon Google, what’s the algorthm?
Google makes 99% of their revenue by selling text ads for things like plane tickets, dvd players and malpractice lawyers. Many of these ads are syndicated to non-Google properties. But the anchor that gives Google their best “inventory” is the main search engine at Google.com. And the secret sauce behind Google.com is the algorithm for ranking search results. If Google is really committed to openness, it is this algorithm that they need to open source.
It’s a data world
In the corporate world, it’s much of the same and even more important to our society. Marketing teams are addicted to information from web analytics and use marketing automation tools to track the success of their programs. Operations teams track assets like computers, buildings, trucks and people with data. Sales has been and will continue to track customers with data. Finance relies on the collision of credit scores data, invoice and payment data as well as making sure they have enough money in reserves to meet regulations. Executives will continue to rely on business intelligence and data. In fact, it’s hard to find anyone in the business world who doesn’t rely on data.
Spread the word
Business intelligence, data integration and data warehousing have become mainstream, but that does not mean most people know the how and why of them. They may be commonplace, but they aren’t necessarily pervasive. The usual scenario is that a separate IT group built them, and only a select few business people use them. So, it’s no surprise that BI knowledge is in short supply.
You say either, I say either
On reflection, perhaps it comes down to our different worlds. I’m only interested in data warehouses because of the opportunities they give me to drive greater insight and better decisions in the business. I think my data warehouse friends have the more modest aim of giving the business the data that makes insight possible – but it’s up to the business to make smart use of this data. Isn’t this just like a scientist inventing a cure and the drug company making it available to people? Sounds like a big enough challenge to me.
Doing it right
No, data perfection isn’t practical. But we should be able to guard against lost data and protect our users from formulas and equations that change. All too often these issues are thrown into the “post development” bucket or relegated to user acceptance. By then reports aren’t always corrected and data isn’t always fixed.
As math, so computer science?
The paradox is that we’re heading into a century in which computer science will be the key to just about everything, from operating businesses to scientific discovery. It’s vital. And somehow some of our schools are sending the message that it’s boring. (Of course, they’ve been doing that with math for eons…)
Connecting here, there, everywhere
In the developing world and the OECD countries alike, mobility is not only redefining the telecom sector, as major as that may be. In addition, the notion of always being reachable, or becoming accustomed to connecting to people rather than fixed locations, is becoming commonplace so fast that we may not realize all that is happening. Worldwide, the number of cellphone subscriptions per 100 people has soared from just over five in 1998 to nearly 60 in 2008. In the midst of it, this change can be lost in fashion wars (RAZR vs. iPhone vs. Blackberry Pearl, or whatever), but eventually, in hindsight, we will see the magnitude of what we lived through.
Meanwhile, out on the social networks
One of my favorite fallouts of my involvement in Twitter has been the Tweetups and the people I’ve transitioned from just a Twitter connection to a real, face-to-face connection. I’ve met some very interesting people and connect with many of them both here in San Francisco and when I visit other cities. The community grows all the time and more and more I am able to connect on and off line with some great people.
