Primarily for enterprise DW data movement from and to sources as well as between architectural layers of the EDW.  We also use it for batch operational integration between applications.  We integrate data from around 20 sources that include both direct connects to sources as well as variety of flat files/formats.  We also feed data to operational systems via flat files and populating external databases.  It's currently all operating 100% Azure IaaS with plans to migrate to SSIS-IR.
Head, Development Chapter (DevOps) at First Bank of Nigeria Ltd.
Real User
Top 5
2024-03-01T11:49:00Z
Mar 1, 2024
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.
We have a consolidated data warehouse. We use an SSIS tool as a pipeline to fetch the data from multiple sources such as Excel, CSV, Oracle database, or APIs. Further, we put the data into the SSIS database. We are using the solution for ETL purposes.
We're SSIS for flat file data ingestion. Our data sources are Excel files, but if the data sources are SQL servers, I use store procedures instead of SSIS packages.
Database administrator at a recruiting/HR firm with 51-200 employees
Real User
Top 10
2022-12-08T12:08:24Z
Dec 8, 2022
Mostly we are receiving files in either XML or Excel and then we collect them in databases. Sometimes it's CSV and sometimes it is also Excel. Mostly, it is XML.
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.
The solution is a business application. It's used for integrations between different databases, migrating from one to one, and importing data from one thing to something else.
We have used SSIS in many ways. Primarily, it has been used for building ETLs for populating data warehouse and staging areas. We have developed a number of data marts that were populated. We build data migration packages, which have been reused a number of times with minimal configurations. Additionally, we build complex data integrations solutions and data hand-offs between different applications. We have even used it for creating and parsing SWIFT messages for data integration purposes. We also used it for email triggers.
I'm using the solution primarily for e-memory and e-database calculation, mostly data blending (ETL) and massive table joining, etc. I also use it for data preparation and modeling.
We are using SSIS for ETL and ELT in a business intelligence context. We bring in data from different sources and use SSIS transform and load it into our intermediate database where we are developing dashboards. There are three people doing configuration and about 50 end-users.
Admin at IEC (Electoral Commission of South Africa)
Real User
2022-06-07T14:58:00Z
Jun 7, 2022
SSIS is helpful when you have tasks in a particular workflow that need to be completed on different schedules. You can start a specific task, and SSIS goes through the workflow to check a few things before it decides whether the task needs to proceed. Right now, maybe a quarter of the company is using it, but we plan to expand use in the future.
We use SSIS to integrate investment data we collect from different places into our portfolio management system. We get results out of portfolio management systems and integrate that into the downstream back-office, risk, and regulatory reporting systems. All the developers at my company use it.
Our company sells contracts when you buy a car. We sell aftermarket insurance for the tyre, wheel, ding, dent, windshield, etc. When somebody buys a contract, we capture all of that data into a legacy database PostgreSQL, and my task is to incorporate that into our financial platform using T-SQL. So, I write queries, procedures, and views. I use SSIS, and I use SSRS. My job is to get the data into our financial system so that we can process claims, payments, cancellations, and refunds.
We are a solution provider and SSIS is one of the products that we implement for our clients. I work as an integrator and a data flow developer. SSIS is primarily used as part of the data flow for loading data into the data warehouse and exchanging data between applications.
Senior Analyst at a tech services company with 1,001-5,000 employees
MSP
2021-12-29T11:01:00Z
Dec 29, 2021
We have data that needs to be migrated. There is also a scan inventory. We create web data, pull it, search it, and then find answers and report stakeholders. So for this process, we use the SSIS.
Data Engineer at a tech services company with 11-50 employees
Real User
2021-05-19T19:43:47Z
May 19, 2021
We are using it in our company and for our clients. I have experience in working with the whole data cycle, which includes data collection, transformation, and visualization. I have worked with the end-to-end process, and I have handled data integration, analysis, and visualization. I specialize in Microsoft tools, and I have used SSIS for data integration and Power BI for data visualization. I have also worked with Tableau for data visualization and Talend for data integration.
We are a software development company and implement solutions like SQL Server SSIS for our clients. We do not use this product ourselves in the company but have experience with it because our client asked for it. Our clients use it to transform data and generate reports. The use cases are generally simple, and not advanced or complex.
We've used the solution to create some data flows for one of the governmental sectors here in Saudi Arabia. I have created some applications for exporting data from Oracle databases to SQL databases.
The primary use case for this solution varies according to the customer, but it typically involves moving data from OLTP systems into a data warehouse and/or data marts.
SSIS is a very flexible solution that allows data to be generated through code or external software. As a result, we can create reproducible patterns and improve code quality.
Movement of data and creation of files. ALl the typical things that you would have a ETL solution do. Data movements were in the millions and no calculations were completed. This means it was always a select * from where ever it was coming from and going to. Light translations like concatenation was being used.
SSIS is a versatile tool for data integration tasks like ETL processes, data migration, and real-time data processing. Users appreciate its ease of use, data transformation tools, scheduling capabilities, and extensive connectivity options. It enhances productivity and efficiency within organizations by streamlining data-related processes and improving data quality and consistency.
Primarily for enterprise DW data movement from and to sources as well as between architectural layers of the EDW.  We also use it for batch operational integration between applications.  We integrate data from around 20 sources that include both direct connects to sources as well as variety of flat files/formats.  We also feed data to operational systems via flat files and populating external databases.  It's currently all operating 100% Azure IaaS with plans to migrate to SSIS-IR.
We use the solution for ETL. It helps to move data from one server to another and translate it in the middle.
Presently, we have decommissioned the solution. Earlier, we used SSIS with the SQL Server.
I use the company's solution to build dashboards and back-end data integration with Microsoft SQL Server and Power BI.
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.
The solution is primarily used for the ETL process. Another use case is transforming data from one format to another format.
We have a consolidated data warehouse. We use an SSIS tool as a pipeline to fetch the data from multiple sources such as Excel, CSV, Oracle database, or APIs. Further, we put the data into the SSIS database. We are using the solution for ETL purposes.
We're SSIS for flat file data ingestion. Our data sources are Excel files, but if the data sources are SQL servers, I use store procedures instead of SSIS packages.
Mostly we are receiving files in either XML or Excel and then we collect them in databases. Sometimes it's CSV and sometimes it is also Excel. Mostly, it is XML.
One of our primary use cases is working with issues related to the electronic components of cars.
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.
SSIS orchestrates data transformation in the environment, which includes Oracle and SQL Server databases.
The solution is a business application. It's used for integrations between different databases, migrating from one to one, and importing data from one thing to something else.
We have used SSIS in many ways. Primarily, it has been used for building ETLs for populating data warehouse and staging areas. We have developed a number of data marts that were populated. We build data migration packages, which have been reused a number of times with minimal configurations. Additionally, we build complex data integrations solutions and data hand-offs between different applications. We have even used it for creating and parsing SWIFT messages for data integration purposes. We also used it for email triggers.
We use this solution to ingest data to a data lake that is built on SQL Server.
I'm using the solution primarily for e-memory and e-database calculation, mostly data blending (ETL) and massive table joining, etc. I also use it for data preparation and modeling.
We use this solution as an ETL tool to move large volumes of data from one server to another.
We are using SSIS for ETL and ELT in a business intelligence context. We bring in data from different sources and use SSIS transform and load it into our intermediate database where we are developing dashboards. There are three people doing configuration and about 50 end-users.
We use SSIS to migrate from an old server to a new one and to add some services.
I am using SSIS for a primary database.
I am an ETL developer working as an information zone leader. We are an outsourcing company to our customers.
SSIS is helpful when you have tasks in a particular workflow that need to be completed on different schedules. You can start a specific task, and SSIS goes through the workflow to check a few things before it decides whether the task needs to proceed. Right now, maybe a quarter of the company is using it, but we plan to expand use in the future.
We use SSIS to integrate investment data we collect from different places into our portfolio management system. We get results out of portfolio management systems and integrate that into the downstream back-office, risk, and regulatory reporting systems. All the developers at my company use it.
Our company sells contracts when you buy a car. We sell aftermarket insurance for the tyre, wheel, ding, dent, windshield, etc. When somebody buys a contract, we capture all of that data into a legacy database PostgreSQL, and my task is to incorporate that into our financial platform using T-SQL. So, I write queries, procedures, and views. I use SSIS, and I use SSRS. My job is to get the data into our financial system so that we can process claims, payments, cancellations, and refunds.
We are a solution provider and SSIS is one of the products that we implement for our clients. I work as an integrator and a data flow developer. SSIS is primarily used as part of the data flow for loading data into the data warehouse and exchanging data between applications.
We have data that needs to be migrated. There is also a scan inventory. We create web data, pull it, search it, and then find answers and report stakeholders. So for this process, we use the SSIS.
We primarily use SSIS to collect data from one system and transfer it to another. The Classical ETL processing of data.
We are using SSIS for all of our relational database management systems (RDBMS) data.
We are using it in our company and for our clients. I have experience in working with the whole data cycle, which includes data collection, transformation, and visualization. I have worked with the end-to-end process, and I have handled data integration, analysis, and visualization. I specialize in Microsoft tools, and I have used SSIS for data integration and Power BI for data visualization. I have also worked with Tableau for data visualization and Talend for data integration.
We are a software development company and implement solutions like SQL Server SSIS for our clients. We do not use this product ourselves in the company but have experience with it because our client asked for it. Our clients use it to transform data and generate reports. The use cases are generally simple, and not advanced or complex.
ETL and data warehousing
Our primary use for this solution is to move data between points and applications.
We primarily use the solution for integration packages for ETL in order to build data warehouses.
We use this solution for extracting data from various databases and saving it in our data warehouse. We use the on-premise deployment model.
We use the on-prem version of this solution. Our primary use case of this solution is for integrated data on the SQL server.
We've used the solution to create some data flows for one of the governmental sectors here in Saudi Arabia. I have created some applications for exporting data from Oracle databases to SQL databases.
We use this solution for data warehousing. We are using the on-premise deployment model.
We use this solution for ETL, which includes data summation and cleaning. This solution used in an on-premise deployment, for now.
Our primary use is as an ETL tool to move data across our various environments.
We primarily use the solution for data transformation.
I use this solution to create BI reports. I have used SSIS in more than twenty projects over the past six years.
The primary use case for this solution varies according to the customer, but it typically involves moving data from OLTP systems into a data warehouse and/or data marts.
SSIS is a very flexible solution that allows data to be generated through code or external software. As a result, we can create reproducible patterns and improve code quality.
Movement of data and creation of files. ALl the typical things that you would have a ETL solution do. Data movements were in the millions and no calculations were completed. This means it was always a select * from where ever it was coming from and going to. Light translations like concatenation was being used.