This article explains both the SSIS term extraction and term lookup components. Besides, it illustrates the use cases of each one of them.

This article explains the SSIS Script task and Script component, the scripting tools available in the SQL Server Integration Services (SSIS).

This article compares the SSIS OLE DB Destination SQL command with the “Table or View” data access mode. In a previously published article, SSIS OLE DB Destination vs SQL Server Destination, in this series, we explained the OLE DB Destination component in SSIS and illustrated how it differs from the SQL Server Destination component. So, in this article, we will focus on the OLE DB Destination data access modes, not the component itself.

SSIS Merge Join and Merge transformations are two similar components used to combine two input data sources into one output. This article explains both transformations and illustrates when and how to use each one of them.

This article explains the SSIS pivot transformation and how it differs from the unpivot transformation.

This article will explain how to use the SSIS lookup transformation and how it differs from the fuzzy lookup. This is a continuation of the SSIS features face-to-face series that we published previously on this website.

In this article, I am going to demonstrate about implementing the Modular ETL in SSIS practically. In my previous article on Designing a Modular ETL Architecture, I have explained in theory what a modular ETL solution is and how to design one. We have also understood the concepts behind a modular ETL solution and the benefits of it in the world of data warehousing. We have also related the concept of microservices architecture in software development to that of the modular ETL solution.

In this article, I am going to demonstrate in detail the Modular ETL Architecture. ETL is a vast concept which explains the methodology of moving data across various sources to destinations while performing some sort of transformations within it. This is an advanced article that considers that the user has a substantial amount of understanding about how ETL is implemented using different tools like SSIS and the underlying working principle along with how to deploy multiple packages using SSIS. It is extremely important to implement a well-designed ETL architecture for your organization’s workload, otherwise, it might lead to performance degradations along with other challenges. To keep things simple, I will just explain the Modular ETL Architecture in this article which will be followed by a detailed hands-on tutorial in the next article – “Implementing Modular Architecture in ETL using SSIS”.

In this article, I am going to discuss SSIS data lineage concepts, which are often used while designing ETL workloads on a data warehouse. Although this article is focused on implementing data lineage using SSIS, it does not only confine to SSIS but to any ETL tools in the market using which data is moved from one source to a destination. In my previous article, Understanding Data Lineage in ETL, I have already discussed the generic importance of data lineage concepts for any ETL tool. I would definitely suggest you have a look at it if you want to understand in general how data lineage helps to track the source of a single record in the warehouse.

In this article, I am going to explain what Data Lineage in ETL is and how to implement the same. In this modern world, where companies are dealing with a humongous amount of data every day, there also lies a challenge to efficiently manage and monitor this data. There are systems that generate data every second and are being processed to a final reporting or monitoring tool for analysis. In order to process this data, we use a variety of ETL tools, which in turn makes the data transformation possible in a managed way.