Blogger: Marcus Collins
The traditional view of business intelligence is of operational systems feeding a data warehouse through an extract, transform and load data pipeline. This view has been static for many years – you know when it’s fossilized when switching the order to translate, extract and load is put forward as a major breakthrough and a competitive advantage!
Increasingly organizations are realizing that this retrospective view of data this model supports is not sufficient to meet the demands of companies that need to function at internet speed.
It’s time to lose this one speed fits all business intelligence model and adopt a tiered approach tailored to the organizations business requirements, competitive environment and customer demands.
Fraudulent activity analysis of credit card transactions 24 hours after the transaction occurred will still leave the banking organization financially exposed. The analysis needs to occur in real time so that the transaction can be stopped and the retailer informed. This real-time analysis has historically been the preserve of complex event processing (CEP) vendors in the financial services sector. With the slowdown in the financial sector we are seeing CEP vendors looking to expand out of this niche into fraud detection, intelligence gathering, telecommunications network monitoring etc.
Organizations that need to react to events or analyze the last few hours’ worth of transactions should look at solutions that update their OLAP cubes in near real-time. When you bid on Google AdWords you will want to analyze the new few hours’ worth of clickstream data to see if you bid was successful or valuable to the overall marketing agenda. This requirement has usually been partially met by traditional ETL and data warehouse vendors but we are beginning to see a number of smaller niche vendors entering this medium throughput sector.
There is still a class of analysis where daily or monthly trending is appropriate. Long term trending of inventory levels with a strategy to reduce the working capital requirements of the business,; guiding an expansion into new products, services or investment in existing products, services; gaining a deeper understand of customer behavior, demographics etc. and tailor offerings to gain maximum revenue from all customer interactions or offering tailored products to customers competitors see as too risky and unprofitable. All these require long term trend analysis and the traditional enterprise data warehouse approach is usually appropriate.
So, when you review your BI strategy or embark on a new BI initiative pay close attention to the timeliness of the data updates to ensure that they meet the needs of the business. Timeliness is just one of the factors to consider and in future blogs we look at the other aspects of BI that needs to be considered to maximize the value and realize the promise of analytics in today’s fast moving and competitive environment.
To recap - ensure that your architecture and BI products support the businesses need for speed!