In-memory BI Technology

Business intelligence (BI) refers to computer-based techniques used in identifying,

extracting, and analyzing business data, such as sales revenue by products and/or departments, or by associated costs and incomes

Computers typically store data on the hard disk, and when you want to perform a task, it pulls out the relevant data and applications for the purpose on to the computer's main memory, which is where computations happen.

In-memory computing involves processing data stored in computer memory rather than on a hard disk. Because of the speed at which data can be accessed from computer memory, and other technical innovations such as the use of parallel computer processors to carry out data analysis, in-memory computing can analyse data in a fraction of the time it takes using data stored in traditional relational databases on hard disks.

With the emergence of multi-core processors and the sharp decline in prices of processors and memory, software maker developed a technology that made it possible for even large enterprises to dispense with hard disks and store and perform all operations on the main memory. It boosted performance enormously compared to systems based on retrieving data from hard drives

The concept of in-memory business intelligence is not new. It has been around for many years. The only reason it became widely known recently is because it wasn’t feasible before 64-bit computing became commonly available. Before 64-bit processors, the maximum amount of RAM a computer could utilize was barely 4GB, which is hardly enough to accommodate even the simplest of multi-user BI solutions. Only when 64-bit systems became cheap enough did it became possible to consider in-memory technology as a practical option for BI.

In-memory computing is necessary for two things.

1. The volume of information is growing rapidly. So we need new ways of analyzing these huge amounts of data. Traditional ways will take too long.
2. Companies are moving from annual budgets and quarterly reviews to instant responses.

Famous in-memory BI products

• QlikView from QlikTech

QlikView uses a simple tabular data model, stored entirely in-memory, with basic token-based compression applied to it

• PowerPivot from Microsoft

PowerPivot uses a similar concept, but is engineered somewhat differently due to the fact it’s meant to be used largely within Excel. In this respect, PowerPivot relies on a columnar approach to storage that is better suited for the types of calculations conducted in Excel 2010, as well as for compression

• HANA from SAP