Object sqlconnection oconn = new SqlConnection (sconn);
Create a new DataAdapter using the Connection Object and SQL statement SqlDataAdapter oDa = new SqlDataAdapter (sSQL, oconn);
Create a new dataset Object to fill with Data DataSet oDs = new DataSet ();
Fill the DataSet with Data from the DataAdapter Object Oda.fill (oDs, "Ewdataset"); Return ods.tables[0].DefaultView;catch (SqlException oerr) {sess
1. Do not use Oracle. JDBC. Driver. The extended JDBC of Oracle is placed in the Oracle. JDBC package. The classes and interfaces described in this package are very similar to the methods described in Java. SQL. I think this should be a kind of Oracle sorting out JDBC, adjusting the original structure to make it more compliant with the specifications. From 9i, Oracle. JDBC. Driver package is not recommended. The code should use the Oracle. JDBC package. Although it continues to support the old p
ETL is a process of extracting, cleaning, and transforming data from a business system and loading it into a data warehouse. It aims to integrate scattered, disorderly, and standardized data in an enterprise, providing analysis basis for enterprise decision-makingETLYesBiThe most important part of a project, usuallyETLIt takes 1/3 of the total project time,ETLThe quality of the design depends on the success or failure of the Bi project.ETLIt is also a long-term process. Only by constantly discov
Private sub command5_click ()
'Create a topic Layer
Dim ODS as mapxlib. DatasetDim olayer as mapxlib. LayerDim otheme as mapxlib. ThemeDim ofields as new mapxlib. FieldsDim ofield as mapxlib. FieldDim ocoordsys as mapxlib. coordsysDim strlayername as stringDim ntype as integerDim s as integer 'Change the projection systemSet ocoordsys = map1.displaycoordsys. CloneSetcoordsys'Set topic LayersStrlayername = getthemelayername ()If strlayername = thenS
transformation server.ETL design is divided into three parts: data extraction, data cleaning and transformation, data loading. In the design of ETL, we also start from these three parts. The extraction of data from various data sources to the ODS (Operationaldatastore, operational data storage)-This process can also do some data cleaning and conversion, in the process of extraction needs to select different extraction methods, as far as possible to i
real-time data, this does not affect Bi applications. 90% of Bi applications do not require real-time performance, and data delay is allowed, this is the application feature of the Decision Support System. This lagging interval is the time for data extraction tools and OLAP.
Iv. Data Processing
(1) ODS (Operational Data Store) is an optional part of the data warehouse architecture. ODS has some feature
Data Warehouse data volume is generally very large, we need to back up every day? This point I still do not understand, just feel that the data warehouse at the very least from the production library flow of data does not need to do a complete backup, but the backup is still needed, such as our ETL process is as follows1: Environment understandingEnvironment: SQLSERVER2008R2The Data Warehouse extraction process is as followsImage analysis:Production Library →
ETL design and consideration in Bi Projects
ETL is a process of extracting, cleaning, and transforming data from a business system and loading it into a data warehouse. It aims to integrate scattered, disorderly, and standardized data in an enterprise, it provides an analysis basis for enterprise decision-making. ETL is an important part of Bi projects. In bi projects, ETL usually takes 1/3 of the time of the entire project. The quality of ETL design is directly related to the success or failu
molap can view real-time data, this does not affect Bi applications. 90% of Bi applications do not require real-time performance, and data delay is allowed, this is the application feature of the Decision Support System. This lagging interval is the time for data extraction tools and OLAP.
Iv. Data Processing
(1) ODS (Operational Data Store) is an optional part of the data warehouse architecture. ODS has s
ETL is the process that the data of business system is pumped into the data warehouse after being cleaned and transformed, the purpose is to integrate the data of the enterprise in the scattered, messy and standard, and provide the analysis basis for the enterprise's decision. ETL is an important part of BI project. Typically, in BI projects, ETL spends at least 1/3 of the time of the project, and the ETL design is directly connected to the success or failure of the BI project.
ETL design is div
purpose is to integrate the data of the enterprise in the scattered, messy and standard, and provide the analysis basis for the enterprise's decision. ETL is an important part of BI project. Typically, in BI projects, ETL spends at least 1/3 of the time of the project, and the ETL design is directly connected to the success or failure of the BI project. ETL design is divided into three parts: data extraction, data cleaning and transformation, data loading. In the design of ETL, we also start fr
A developer sent a statement asking me to check whether the results of ods and the source are consistent. If the execution fails, ask the developer to run the statement for 2-3 minutes. Because they use dblink locally to connect to ods, I will remove dblink and view the execution plan directly from ods. SELECTXSY_CODE, -- Development salesman code SLY_CODE, -- Su
to display the ' ASCII filteR Options "dialog//alternatively filtername could is" Text (encoded) "and filteroptions used to set encoding if
Needed txt.setimportoption ("FilterName", "Text");
Txt.setexportfilter (Documentfamily.text, "TEXT");
Adddocumentformat (TXT);
Final Documentformat wikitext = new Documentformat ("MediaWiki wikitext", "Text/x-wiki", "wiki");
Wikitext.setexportfilter (Documentfamily.text, "MediaWiki");
Adddocumentformat (wikitext); Fin
Why layer data warehouses?
Use space for time and a large amount of preprocessing to improve the user experience (efficiency) of the application system. Therefore, a large amount of redundant data exists in the data warehouse;
If there is no hierarchy, changing the business rules of the Source Business system will affect the entire data cleansing process, resulting in a huge workload.
Data cleansing can be simplified through hierarchical data management, because the previous step i
operations will also generate overhead on the client; none: default value, you can also specify to disable the failover Function
2. FCF (Fast Connect Failover) oracle11g provides the FCF method to Connect to the database. It supports JDBC Thin and jdbc oci drivers; and connection cache (implicit connection cache) collaborative work provides higher connection performance and high availability. You can set it in the application code without the need to configure additional conditions: the i
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