etl products

Reprinted ETL architect interview questions 1. What is a logical data mapping and what does it mean to the ETL team? What is Logical Data ing? What role does it play on the ETL project team? A: Logical Data Map) describes the data definition of the source system, the model of the target data warehouse, and instructions on operations and processing methods to conv

Introduction to ETL technology: Introduction to ETL, data warehouse, and etl Data WarehouseETL is the abbreviation of Extract-Transform-Load. It is used to describe the process of extracting, transforming, and loading data from the source to the target. ETL is commonly used in data warehouses, but its objects are not l

ETL TL, short for extraction-transformation-loading. The Chinese name is data extraction, conversion, and loading. ETL tools include: owb (Oracle warehouse builder), Odi (Oracle data integrator), informatic powercenter, aicloudetl, datastage, repository explorer, beeload, kettle, dataspider ETL extracts data from distributed and heterogeneous data sources, suc

the amount of data, which is generally huge, and it is worthwhile to split the process of data flow into E, T, and L. Now there are many mature tools to provide ETL functions, such as DataStage, Powermart, etc., and do not say they are good or bad. From the application point of view, the ETL process is not very complex, these tools to the Data Warehouse engineering and great convenience, especially the dev

ETL scheduling development (5) -- connect to the database to execute database command subroutines and etl Scheduling In ETL scheduling, you need to connect to the database to read and write data. The following subprograms use the input database connection string and database commands (or SQL) to perform the required operations: #!/usr/bin/bash#created by lubinsu

The main indexes of this series of articles are as follows: I. ETL Tool kettle Application Analysis Series I [Kettle Introduction] Ii. ETL Tool kettle Practical Application Analysis Series 2 [application scenarios and demo downloads] Iii. ETL Tool kettle Practical Application Analysis Series III [ETL background process

ETL (extract-transform-load abbreviation, that is, data extraction, transformation, loading process), for enterprise or industry applications, we often encounter a variety of data processing, conversion, migration, so understand and master the use of an ETL tool, essential, Here I introduce a I used in the work of 3 years of ETL tools kettle, the spirit of good t

makes subsequent transformations and loading operations. Full-volume extraction can be done using data replication, import or backup, the implementation mechanism is relatively simple. After the full-volume extraction is complete, the subsequent extraction operation simply extracts the data that has been added or modified in the table since the last extraction, which is the incremental extraction.In a database repository, whether it is a full-scale or incremental extraction, extraction is typic

Etl tool, kettle implementation loop, etl Tool kettle implementation Kettle is an open-source ETL Tool written in java. It can be run on Windows, Linux, and Unix. It does not need to be installed green, and data extraction is efficient and stable. Business Model: there is a large data storage table in the relational database, which is designed as a parity datab

process of data flow, from different data sources to different target data. But in the Data Warehouse, ETL has several characteristics, One is the data synchronization, it is not a one-time rewind data to pull to, it is a regular activity, in accordance with the fixed cycle of operation, and even now some people put forward the concept of the Realtime ETL. Two is the amount of data, which is generally hug

During database management, extraction, conversion, and loading (ETL, extract, transform, and load) are three independent functions that constitute a simple editing task. First, read the data in the specified source database and extract the required sub-dataset. Then, the conversion function uses rules or drop-down lists to process the acquired data or create connections with other data, so that it can be converted to the desired state. Finally, we us

For the Data warehouse and ETL knowledge, I am basically a layman. Everything has to start from scratch, take a note, to facilitate the understanding of learning progress.First, let's take a look at the basic definition:Well, some people also called the ETL simple data extraction. At least before the study, the leader told me that you need to do a data extraction tool.In fact, extraction is the key part of

they require additional operations and database operations from the business system, with little time loss, time stamping, The impact of System log parsing and System log analysis (asynchronous CDC and flashback query) on database performance is also very small. The intrusion of the data source system refers to whether the business system should make the function modification and the additional operation for the implementation of the extraction mechanism, at this point, the timestamp method des

Introduction: Etl,extraction-transformation-loading's abbreviation, the process of data extraction (Extract), Transformation (Transform), loading (load), is an important part of building a data warehouse.Keywords: ETL Data Warehouse OLTP OLAPThe etl,extraction-transformation-loading abbreviation, the process of data extraction (Extract), Transformation (Transform

BI Architecture-bi Key Links ETL related knowledge Main function: Load the data of the source system into the Data Warehouse and data mart layer; The main problem is the complex source data environment, including a wide variety of data types, huge load data volumes, intricate data relationships, and uneven data quality common terminology etl: Data extraction, conversion, loading (extract/ Transform/l

Assembly Area Preparing data, often also called data management, refers to acquiring data and translating it into information, and ultimately submitting that information to the front-end query interface. The background does not provide query services, the Data Warehouse methodology assumes that data access in the background is strictly forbidden, which is the sole purpose of the foreground. The backend part of the data warehouse is often referred to as the staging area (Stagingarea). Data aggreg

ETL: Abbreviation of extraction-transformation-loading. The Chinese name is data.Extract, convert, and load data. ETL extracts data from distributed and heterogeneous data sources, such as relational data and flat data files, to a temporary middle layer for cleaning, conversion, integration, and finally loading data to a data warehouse or data warehouse.Data mart has become the basis for Online Analytical P