SSIS Reviews

We use the solution for ETL. It helps to move data from one server to another and translate it in the middle. 

I like that this solution is very scalable, accommodating large datasets and various types of servers. It integrates with most common database servers and allows for customization through coding, including complex scripts. Compared to Alteryx Designer, SSIS offers more customization. Its data cleaning capabilities are highly accurate because we can run tests as data is loaded, ensuring it meets all requirements before reaching the final destination. The ability to write custom SQL and C# code within SSIS packages is its greatest feature. 

I use SSIS for data loading ETL processes. I am responsible for the EDW layer and get new data from other data sources into the EDW via SSIS.

SSIS has too many bugs. Sometimes it works, sometimes it doesn't. I try to use a package, and it won't work on my computer, but it will on another user's computer. If I could rely on the program more, it would be better.

We use SSIS for data extraction, transformation, and loading processes. This includes extracting data from various sources like Oracle and SQL Server, and then transforming it for use in reporting tools like Power BI dashboards. While we haven't directly migrated data between databases using SSIS, we have used it extensively for ETL tasks, such as extracting data for analysis and reporting purposes.

Presently, we have decommissioned the solution. Earlier, we used SSIS with the SQL Server.

The most valuable feature of the solution is performance. It works by connecting to the SQL Server.

In my experience with SSIS, I have found its most valuable features to be its package management capabilities and the flexibility it offers in designing workflows. We often use templates, inheriting and embedding scales in SSAS to streamline our processes.

In upgrading SSIS, we encountered challenges fixing SQL Server and performance issues, including problems during a failover in our data warehouse. After resolving these issues and conducting load balancing tests, we proceeded with the SSIS upgrade, anticipating potential complications. 

I use the company's solution to build dashboards and back-end data integration with Microsoft SQL Server and Power BI.

The most valuable features of the solution stem from the convenience it offers, along with the ability to refresh data.

It was used for a couple of purposes, for example, we used it in our data warehouse when we wanted to create a dashboard that would give us an idea about, for example, the data itself. We had a client that would ask about a couple of requirements, like the past data from the last month or last year for a particular region for a particular client, and so on. I was using SSIS to store data incrementally and show the data using SSIS. 

For example, if we have created a couple of tasks or schedules, we would create a couple of packages and schedule them overnight. Every night it could fetch the data incrementally from the data warehouse. Every week, there was a requirement from the client that I need to add particular data to be changed and shared over email weekly. That particular data could be fetched from the data warehouse, and it will be shared with the client every week. 

Many features are very good in SSIS. 

I can create a particular package, and I don't need to repeat it again and again. For example, I can create a package that will fetch all the data from the given data. If my client gives me some data, I can clean some data, perform some transformations, and then store the data in any place. That's quite helpful for me as well. I don't have to do it again and again manually. I just have to create a package, schedule it, and it could be run, and it could be stored in any target I have. It can run for me, again and again, without me having to re-make it manually again and again.

It is easy to set up the product.