etl data warehouse concepts

system. This involves operations such as data cleanup and aggregation. Loads data into a data warehouse or data mart. The process of fetching data from OLTP and legacy data sources a

Welcome to the Oracle community forum, and interact with 2 million technical staff to access the data warehouse. different data sources must be obtained from different data sources, in addition, this huge amount of data is converted into available

, respectively: (1) Information Model of Data Warehouse (DW), such as Data Warehouse dimension table and fact table; (2) System Management information model, such as: System User table, User rights table, etc.; (3) Operational data Storage (ODS) information model; (4) Me

dimension 9 series of data warehouse-Dimension Data Processing Methods -- Snowflake About Data Warehouse ETLA series of articles on data extraction and data SummarizationSimula

Data warehouse and data mining are two big concepts. They are very mature in foreign countries. In China, with the accumulation of enterprise data and the maturity of ERP in the past few years, data

: The time base change is difficult to grasp. The existing operational data is usually the current value, precision controllable, can be updated, but the data in the data warehouse can not be updated, so these data must be accompanied by time elements, when the actual operat

data for the cycle requires the highest efficiency and requires 24 hours or even 12 hours, the customer can see yesterday's data analysis. Some enterprises often encounter problems with poorly designed data warehouses because of their large daily data volume. data can only

The common dwh architecture is as simple as figures 2 and 3. Generally, for an enterprise, the data lifecycle is 5-7 years, especially for detailed data. The lower the data granularity level, the shorter the lifecycle, the higher the data granularity and the longer the lifecycle. For the flow account

About star schema In the construction of the Data Warehouse, the star pattern shown in the following illustration is almost the most commonly used. It is called star mode because the E-R graphic in the pattern is like a star (it feels strange to say). NBSP as shown in the figure, the center is a large fact table with some dimension tables around it. The fact table contains the primary information fo

of the data download to local, to provide users with local multidimensional analysis. Represents a product that has brio designer,business Object. DSS Decision Support Systems (Decision Support System) are equivalent to data warehouse based applications. Decision support is the collection of all relevant data and inf

Data Warehouse scheme is to provide front-end query and analysis as the basis, because there is a large redundancy, so the need for storage is also large. In order to better serve the front-end application, the data warehouse must have the following advantages, otherwise it is a failed

the data Warehouse, but a small number of reversal vouchers can affect operations in recent months. The original total Delete+insert, or the Insert new Data + Time range update operation, in the merge where time overrides the scope of the possible reversal can occur. Parameters:1.alter session set workarea_size_policy=manual;alter session set sort_area_size=1073

Differences between OLAP and OLTP Environments 1 The performance tuning in the DB2 data warehouse environment is different from that in the OLTP environment, mainly manifested in the following aspects: 1.1 transaction length. Transactions in the OLTP environment are usually short transactions, including multipleSQLStatements, which can often be completed within several seconds. In a