Managing Time in a Data Warehouse

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Video: .MP4, 916x514, 30 fps | Audio: AAC, 44.1 kHz, 2ch | Duration: 1h 31m
Genre: eLearning | Language: English | Size: 332 MB

Recorded live at Data Modeling Zone!

Follow along with data modeling expert Dirk Lerner and learn the approaches for managing time and history in a data warehouse.

"Over time, things change - things like customers, products, accounts, and so forth. But most of the data we keep about things describes what they are like currently, not what they used to be like. When things change, we update the data that describes them so that the description remains current. But all these things have a history, and many of them have a future as well, and often data about their past or about their future is also important." - Tom Johnston

Today, most data warehouses already store the history of the data. But what about events that took place at a different time than what the data warehouse represents to us? Or data that will be valid in the future? For example, generally planned prices for products and goods in the future or special prices for discount battles around "Black Friday".

The speaker will focus in this session on the method and techniques for storing temporal and bitemporal data in a Data Warehouse. He will show bitemporal basics for a better understanding of loading data as well as the concepts to develop SQL Queries to insert and update temporal data within a Data Warehouse.

What attendees will learn in this session:
Basic bitemporal concepts
Examples of data modeling a bitemporal Database Object
Load bitemporal data into a Data Warehouse
Examples of SQL Queries to insert and update temporal data
Screenshots

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