Great Tool For ETL Design
January 19, 2020
Great Tool For ETL Design
Business Intelligence Consultant
EMO A.ŞInformation Technology & Services, 501-1000 employees
Score 9 out of 10
Overall Satisfaction with SQL Server Integration Services
In my department, we design and manage ETL processes. We use SQL Server Integration Services (SSIS) to design a data warehouse. To create a data warehouse, we can make the stage layer and DWH layers with the SSIS ETL tool. We create data marts using aggregate functions in the SSIS ETL tool. In addition, we use the SSIS ETL tool to move data between databases.
- Data migration is pretty fast.
- SQL Server is highly compatible with the database.
- We receive errors in moving JSON data to the database. It does not work efficiently in JSON-related data.
- ODBC connections give a connection error after a certain period of time.
- Paying a license fee to the SSIS ETL vehicle for our enterprise projects increases our costs.
- Because it is a powerful and performance ETL tool, data increases our business productivity.
I used the Pentaho Data Integration (PDI) ETL tool. The PDI ETL tool does not have a public user collection like the SQL Server Integration Services(SSIS) ETL tool. Therefore, you may not be able to find instant solutions for your problems. But it has advantages over the SSIS ETL tool. The PDI ETL tool is open source software and does not charge a license fee.
The SQL Server Integration Services (SSIS) ETL tool has a very strong user community. With the error codes, I get access to solutions in the forums. In addition, Microsoft products offer a wide range of consulting services.
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For enterprise business intelligence projects, the SQL Server Integration Services ETL tool is a logical choice to move your data to the data warehouse on a daily basis. The SSIS ETL tool has enough functions and capabilities to design the data warehouse. If you want to send your JSON data to the database, SSIS does not work here.
SSIS Feature Ratings
Connect to traditional data sources
Connecto to Big Data and NoSQL
Data model creation
Business rules and workflow
Testing and debugging
Integration with data quality tools
Integration with MDM tools