Waterfalls Can Be Dangerous. Try Agile Data Integration For Agile BI.

Most organizations will admit that it takes much too long for the business to get the data they need.  IT projects take too long to deliver — from the time business requirements are defined until the project go-live.  With traditional waterfall-style project management there is a tendency to throw requirements and deliverables over the fence to the next phase so that by the time the project is delivered the business has moved on and the requirements may have changed.  It is a well-known fact that most IT projects fail from the customers’ perspective.  That doesn’t mean the project was not delivered but instead means that the project failed to deliver the expected business value.

The desire to plan everything at the beginning of a project followed by design, then development and testing makes projects inflexible to change.  Change is imminent — market conditions change, business requirements change, and customer preferences change.  The complexity of IT projects makes it difficult to do all requirements, schedule, and resource planning up front.  Unfortunately, all too often If you do try to plan and scheduled everything up front the project becomes doomed from the start because of the inability to quickly adapt to changes.  As IT projects fall behind schedule, project teams are often forced to dramatically cut scope or take short cuts that tend to sacrifice the quality of the initial rollout due to insufficient test coverage, lack of data quality, and poor collaboration between the business and IT.

According to the Standish Group, 16 percent of waterfall projects succeeded as opposed to 41 percent of Agile projects.  The business people on a project team at a large telco reported that the project would have taken three times as long if they had not adopted Agile.  A large network of lending institutions used to average one hundred or so defects per rollout of waterfall projects whereas Agile projects averaged zero to two.   Agile Data Integration increases the business value of projects (e.g. Business Intelligence, Data Warehousing, ETL, Data Migration, etc.), delivers projects faster, and reduces project defects.

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