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but also an element of experimentation ,” said Pain .
While reporting after the fact remains an important business imperative , the ability to make decisions in real time wasn ’ t supported . While it was great for the C-suite , it didn ’ t help line managers who wanted to be able to make more immediate decisions . As a result , line managers began creating their own systems in Excel or using desktop database applications . The trouble was that different parts of the business could use the same data and , by applying different analysis techniques and their own definitions , end up producing inconsistent results .
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© iStockphoto . com / Evgeny Terentev |
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deliver the data more consistently , in real time and in a form that allows line managers to make real- or neartime decisions with confidence . Rather than working with raw data and then manipulating it manually , they are able to work with data sets that are better tailored to their needs and delivered in a more timely manner .
Collins clarified this saying ,“ All data has a cause and an effect . It ’ s not just about reporting the data , it ’ s about trying to link traditional metrics to corporate performance .”
We are already seeing this in retail where companies can see what you ’ ve browsed and purchased online , use demographic data they ’ ve gathered and then target specific advertising or product recommendations .
The way this works requires a shift in how businesses store and manage data . In the past , most of the organisation ’ s data was held in a structured database and then distributed outwards to the
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data warehouse . In today ’ s world , we ’ re looking at massive volumes of data , from multiple sources , and much of it is unstructured . According to Harrison , this means were more likely to see a Hadoop-style cluster as the main data repository with in-memory processing systems used to extract and manipulate the data for analysis .
However , the data modelling that used to happen at the start of the analysis process is performed after the data enters the database , not before . Harrison calls this “ just-in-time modelling ”. Businesses that aren ’ t able to leverage the unstructured data are “ just going to lose ” in his view .
It ’ s tempting to see the issues around using data as being largely technical . However , “ You can change and manipulate data until the cows come home but unless you have a direct connect to the business that ’ s all you do ,” added Collins .
The good news for the CIO is that many of the skills needed to support the business in using business intelligence
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tools already exist in the IT department . However , they ’ re often channelled towards a different purchase . Using live data from systems to monitor and manage performance is something many systems managers have been doing for some time .
Applying similar techniques , we ’ ve seen companies such as Sportsbet , Coles and iiNet use BI-like tools from Splunk to monitor their systems in real time and manage performance . For example , by monitoring server performance during peak periods , they are able to reassign resources dynamically to ensure that systems not only remain available but perform at optimal levels .
How information comes into a business and is used to deliver benefit to the bottom line is critical . Grant Christian , from Information Builders , says , “ The information delivery chain is much more than just delivery or presentation of information , it extends out into the cloud with social analytics in one direction , but then also extends right back to the
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