In the early 2000s, the Gartner Group coined the term zero latency enterprise (ZLE).
In its words, ZLE was “the instantaneous awareness and appropriate response to events across an entire enterprise.” This response was later renamed the real-time enterprise (RTE).
An ODS is designed for relatively simple queries on small amounts of data (such as finding the status of a customer order), rather than the complex queries on large amounts of data typical of the data warehouse.
As these technologies proved their worth, data replication was added to move the technologies to real-time business intelligence systems, thus expanding their reach.
Though RTBI systems exist today in many applications, each RTBI system generally supports a single purpose such as fraud detection, instant customer promotions, or just-in-time inventory.
Considerable effort was invested by some companies to consolidate a multitude of RTBI systems into a single ODS supporting enterprise-wide tactical and strategic decision-making or enterprise content management (ECM), shown as the final step in Figure 2.
The cost and disruption imposed by conversion to an ODS has so far resulted in little progress in expanding RTBI systems to support both tactical and strategic decision-making for any particular corporate function, much less the enterprise.
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Some co-workers and I got into a debate on the best way to store historical data.
On the other hand, the ODS must be capable of online transaction processing (OLTP) at an extremely high transaction rate, as it is being fed transactions in real-time from many enterprise systems.
The database structures suitable for OLTP are characterized by skinny keys that require a minimum of updating as data is added to the database.
If no warehouse currently exists to act as the stepping stone to an ODS, companies may find it more economical to simply interconnect their systems in a mesh network using existing EAI technologies, instead of following a more planned and fruitful, but expensive path to an ODS.