A Reliable Data Preparation Tool.
May 06, 2016

A Reliable Data Preparation Tool.

Tom Jaskula | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User

Overall Satisfaction with SQL Server Integration Services

SSIS is used by the IT department for extracting, transforming, and loading data. The most common application for SSIS would be for cleansing and restructuring data while it is being loaded into a data warehouse.
  • Providing developers with a wide range of architectural options.
  • Providing the ability to connect to a wide array of data sources.
  • Proving many different deployment options.
  • While SSIS does provide a plethora of architectural options, all of these options can at times be overwhelming. Some competing products offer a more straight forward and streamlined approach.
  • SSIS does not currently provide any templates, although this is supposed to be addressed with the upcoming release of SQL Sever 2016
  • Connecting to Oracle databases is not easy, SSIS still requires the installation of other tools.
  • Data preparation is the majority of the effort involved in data warehousing projects. The amount of time it takes to prepare data is the same now as it was when the product was introduced in 2005. There are more features now, but the amount of time that you are spending with the tool has still remained the same.
  • SSIS is a very widely used tool, making talent easy to find.
  • Because its included with SQL Server, you don't have to go through any additional effort to purchase this tool. If you own SQL Sever then you already own SSIS.
SAP Data Services is a very good tool and overall its easier to use than SSIS, but SAP is at a much higher price point than Microsoft. Microsoft can be a good fit for businesses of any size, but SAP tends to be a better fit for larger businesses.
SSIS is a good fit when you have structured data. If you're looking to prepare unstructured data for doing text analytics, this is not the right tool.

SSIS Feature Ratings

Connect to traditional data sources
Connecto to Big Data and NoSQL
Simple transformations
Complex transformations
Testing and debugging
Integration with data quality tools
Integration with MDM tools