Business Intelligence Definitions Made Simple
I read an interesting article today from Software Advice: BI Buzzword Breakdown | 5 Experts Tackle 3 Business Intelligence Definitions. The article helps new BI users get their heads round some of the acronyms and terminology commonly used when talking about BI. Business Intelligence is not just for the IT crowd anymore. With companies like QlikView making BI more user friendly and encouraging more casual business users, there are more and more people who want to learn about BI.
Acronyms are only useful when everyone involved in the conversation knows what they are. This can be tricky in a BI environment as you can have IT guys talking to non IT guys in what seems like a different language with the amount of acronyms involved. One common offender is OLAP which stands for online analytical processing. OLAP tools enable users to analyse different dimensions of multidimensional data. At the centre of a OLAP system is a hypercube. There are some disadvantages though; OLAP-based Hypercubes limit users to a small number of dimensions. Measures have to be defined when the application is developed and redefinition of a measure is time-consuming. The user interface is complicated for non-IT people to understand. Bottom line is that OLAP-based Hypercubes and Data Warehouses are expensive and time-consuming solutions to install.
It is because of these disadvantages that QlikView uses QlikTech's patented AQL (Associative Query Logic) technology which works in a different way, by building and maintaining a non-relational, associative and highly space efficient database that resides in RAM. The advantage of the AQL architecture is that the source data is retained and immediately available offline for analysis, all the way down to the source transactions. The result is powerful analytical capabilities provided through a highly intuitive user interface that encourages exploration and creativity.
The three BI definitions covered in the article are "Big Data", "Data Warehouse" and "Data Mining". For the definition of big data I agreed most with expert Billy Cripe's definition that "Big data looks for trends, patterns and insights from extremely large data sets. Examples include the entire Facebook Social Graph and years’ worth of Amazon.com buying history. It is from these extremely large and often heterogeneous data sets that new insights emerge"
Big data is a hot topic at the moment with more and more companies wanting to create and manage large data sets. For this companies need to understand the software tools, processes and procedures involved with big data.
The definition of data warehouse I liked most was by expert Jake Freivald who said "Think of a data warehouse as the data equivalent of a massive distribution center for a retail chain: everything of every type for every store goes into a distribution center, and every data item of every type for everyone goes into a data warehouse. And because data warehouses have a lot of data that comes from a lot of places, they're very complex, which means they take time to build and–more importantly–adapt to changes".
Effectively managing data warehouses is something which can be difficult. But unlocking your data from your data warehouse is something which QlikView excels at.
The definition I found best for data mining was by expert Estelle Nicholson who said "The more purist definition is not just analysis, but discovery. It’s taking the data a step further to find correlations and patterns that weren’t seen or maybe weren’t discovered before. For example, a marketing firm could correlate household income and the effectiveness of a specific campaign run, or maybe the delivery method of the campaign and quality of customers it generated. You can come up with answers you never even thought of the questions for"
I really like this definition as it talks about discovery which is something that I feel is crucial when dealing with data. Data mining shouldn't be a rigid task of seeing what you already know, it needs to be about finding out what you didn't know and what you didn't even think to look for and it is this discovery that I like most about QlikView.
To learn more about QlikView Business Discovery