The difference between ODS and DW

Background: In this era of rapid development of information technology, the volume of data is also growing, facing such pressure, there will always be a great God to propose some solutions. For example, high-level managers want to see the entire company's development performance, Data Warehouse (DW) is the main solution to this problem, and then the DW Warehouse. But the times are changing, the demand will change, such as the employees of insurance companies want to improve their performance, take more wages, then he first hope is to be able to bring more customers to dig in, in fact, there are many ways. The most basic example, for example, a customer service of an insurance company hope to be able to the highest success rate to customers to recommend the relevant business, once the customer calls, customer service can immediately pull out from the database of the customer related to a series of information, so that the information can be targeted to customers to recommend related business, obviously, This way of recommending can obviously improve the success rate. So the problem is, how to solve such a problem. As a follow-up, the birth of the operational data store (operational, ODS) provides a good solution to such problems. In theory, what is the difference between these two solutions? Now get to the point.

The main differences between ODS and DW are as follows:

1, the current nature of the data

ODS includes current or near-current data, ODS reflects the state of the current business conditions, the design of the ODS is related to the needs of the user or business, and DW is a more historical data that reflects the business conditions.

2. Update or load the data

Data in the ODS can be modified, and data in the DW is generally not updated. The update of ODS is based on the needs of the business and does not need to be updated immediately, so it requires a real-time or near-real-time update mechanism. In addition, data in the DW is collected and loaded at normal or pre-specified times.

3, the summary of the data

ODS mainly includes some detail data, but due to the need for performance, may also include some summary data, if included summary data, it may be difficult to guarantee the data's current and accuracy. Summary data in the ODS has a short life cycle, so it can be called as dynamic summary data, and if the detail data is modified, the aggregated data also needs to be modified. The data in the DW can be called static summary data.

4. Data modeling

ODS is designed at the point of view of record level access, and DW or DM is designed to stand at the point of view of the result set level. The ODS supports fast data updates, and DW is query-oriented as a whole.

5, the query of the transaction

Transaction operations in the ODS are much more, and the same transaction is likely to be performed continuously over the day, and the arrival of transactions in the DW is predictable.

6. Use

ODS is a short term for operational decisions of every day, and DW can obtain a long-term, cooperative, broad-based decision. The ODS is strategic, and DW is strategy-oriented.

7. Users

ODS is used primarily for strategic users, such as the customer service that insurance companies communicate with customers on a daily basis, and DW is used primarily for strategy-oriented users, such as the company's top management staff.

8. Data volume (one of the main differences)

ODS only includes current data, and DW stores a historical snapshot of each topic;

The above image is excerpted from Corinne Baragoin, Marty Marini, Cellan Morgan, Olaf Mueller, Andrew Perkins, Kiho "Henry" Yim. Building the operational Data Store on DB2 UDB Using IBM Data Replication, WebSphere MQ Family, and DB2 Warehouse Manager.