Afterwards, we load the data into a data warehouse, or the data stay in the data lake to be used by data scientists to train their ML models. We also use ETL tool to load data into data lake, such as ADLS, S3 and BigLake. Then we use the ETL to run SQL script on that data warehouse. ![]() So today, we use ETL tool just to load the source files (or from databases) into the cloud/MPP data warehouse. In Informatica, the word “mapping” means data pipeline. Meaning that Informatica’s Integration Service will translate the transformation logic into SQL queries and sends the SQL queries to the target database for execution. For example, in the Informatica PowerCenter when we create mapping we can opt for pushdown. This way, the ETL server doesn’t need to be powerful.Ģ0 years ago, this technique of utilising the database engine computing power is called “Pushdown”. We load the data into those MPP engines, then use that powerful MPP engine to perform transformation. MPP stands for Massively Parallel Processing (basically parallel computing, many servers running in parallel). Many of these data platforms are MPP (Snowflake, BigQuery, Synapse Dedicated/PDW, Redshift) or Spark (Databricks, HDInsight), which are well known for their computing power. Today, the target are all cloud data platform, such as Snowflake, Databricks, Redshift, Aurora, BigQuery, Azure SQL, Synapse and Microsoft Fabric. ![]() ![]() It connected to a data source, did the transformation in memory of that ETL server, and loaded it to the target data warehouse. All the others were acquired by another company, or changed their names.Įach of these ETL tools was installed on a server (such as Windows 2000). Of them all, only Informatica PowerCentre and DataStage still exists. I provide their links below if you’d like to have a look at them (Ref #1 to #9). In early 2000s the popular ETL tools were Microsoft DTS (now SSIS), Informatica PowerCenter, Hummingbird Genio (now OpenText), DataFlux (now SAS), Cognos DecisionStream (now IBM), BusinessObjects Data Integrator (now SAP), Cadis (now SAP) and IBM DataStage. Last night at the Astera webinar about ETL pipelines we discussed ETL vs ELT a bit.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |