Hot Topics
XBRL
What difference does a markup language make? A lot – and this one more than most.
A company's financial information lives in databases. They're highly structured and very sophisticated. But that makes it very difficult to get information out of them. Data wizards have to interpret the models, reconcile differences among systems, even massage the data (in an auditable way, of course) to change raw data into usable financial statements.
That's why XBRL is so important. Once all of this work has been done, the last thing you want to work with is a hard-copy report or a Word document of the data. The former guarantees data entry errors; the latter requires extreme attention to detail to make sure you're getting the right data out of the right fields. XBRL gives a solid foundation for reporting, comparing, and integrating data.
Of course, Information Builders is all about reporting, which is why we want to make it as easy as possible for you to use XBRL-based financial statements in your business intelligence applications. You can find out more about our support for XBRL here.
Scalability
The BI industry is finally coming around on a point we've been discussing for years: scalability matters.
Why would people think otherwise? Mostly, it seems, because of the overemphasis on OLAP, and client/server OLAP at that, as the term "business intelligence" was coined and developed. People have always been concerned about performance – how quickly the database queries respond to a particular user – but only data wizards use OLAP tools, so scalability doesn't matter much in an OLAP-only environment. Database administrators only had to worry about individual queries for a small number of seats, rather than wide-open database access for thousands of concurrent users.
We've known better all along, and many other people are starting to catch up. Business intelligence has the greatest impact when it affects the greatest number of people, because everyone makes decisions.
This fact has an impact on every aspect of BI: how you deploy BI tools and applications, how your database is structured, whether or not you use a data warehouse, what formats you use, how you allow users to submit queries – every aspect.
Which brings us back to scalability. How can you make sure that your business intelligence application can support hundreds or thousands of concurrent users? We have over thirty years' of experience in building widely deployed BI applications. We run the world's largest BI deployments. Here's how: our high-scalability business intelligence architecture.
Operational Business Intelligence
People often think of business intelligence as an analytical capability. In fact, some of the best deployments of business intelligence (BI) have been operational.
What does that mean, you ask? In a nutshell: instead of having a data wizard focus on what has happened over the past month or year or decade, people on the front lines of your business focus on what's happening right now – on how they can perform better today to achieve business goals.
Someone recently compared the difference between analytic BI and operational BI to rowing a rowboat vs. paddling a canoe: in a rowboat, you're always looking back, seeing where you've been; in a canoe, you're facing ahead, looking out for immediate obstacles and paying attention to long-term goals.
Both operational and analytical BI are important, but we focus on operational business intelligence to show you how it can make a difference to your organization.
