With the economy decelerating all over, the needs for business intelligence swell; decision-making becomes crucial. It is not about making mega-bucks any longer but rather about survival of the entire business.
Nobody is questioning the vital necessity for a successful business to constantly monitor a company’s performance, its profitability, its best and worst customers, its best and worst products and its overall health especially now, when resources are so stretched. The driving force behind such business intelligence functions is a healthy data warehouse.
Nowadays the question is this: “How to achieve the same – and more for less?” How to build such a brawny data warehouse with a constant shortage of money?
Most of the organizations still start with a data warehousing project, using the ol’ traditional waterfall approach. It worked before but does not cut it any longer …
Groundwork for such a project includes taught questions with no good answers:
• Business users are asked what data they need. But the business generally doesn’t know what it wants. “I’ll tell you what I want when I see it” is their familiar mantra.
• Then business users are asked what reports they use and what is missing in those reports. But reports are “moving targets” they change swiftly, especially when decisions are about the life and death of the company.
• Where to find right people? Well, with a continual shortage of the skilled ETL developers, data- modelers and business analysts – good luck. A decent IT chap costs a fortune.
• How long will the data warehousing project take? Organizations can’t afford the common 6 to 9 months, possibly, longer with painful approvals and rework.
• How do we keep documentation up to date? What is the risk of such lengthy warehouse project? How to find an enthusiastic sponsor of the business intelligence effort?
• And many more questions…. Oh stress, the spice of life!
That is the alternative? Not to life it is – to stress!
A different approach that presents a true unique business value for a stressed out business that includes:
• Built-in methodology that supports the entire data warehouse lifecycle an Iterative approach. The Ability to stay focused on the goals.
• Spiral-like rapid “prototyp–>iterate–>deploy” venture. Quick response to changing business needs. The only questions asked: how to make the right business decisions right and what are the measures of the truth?
• Integrated, metadata-driven data warehouse development environment. All that the developer needs is on his/her fingertips, Auto-generation of procedural code and documentation.
• A low risk, proven, pragmatic approach to data warehousing. An instrument to get business users and stakeholders involved earlier.
• Effective use of time & money; quicker ROI. A process for trimming off 2-4 months a year from the development and support costs; reducing time to deliver.
• The data warehousing as a process – not a project. Well-timed accommodation to changing business needs.
• Leveraging existing, readily available SQL skills in market. Theory and best practices are in the tool, not in developer’s head.