How To Set Up Microsoft SSIS ETL: 7 Easy Steps

SSIS (SQL Server Integration Services) is a powerful tool that simplifies the ETL process, making it easier to extract, transform, and load from various sources efficiently. Its intuitive drag-and-drop interface allows you to build complex data workflows without needing deep coding skills. With SSIS, you can streamline your data integration tasks, automate processes, and ensure that your data is accurate and ready for business insights.

In this article, we will briefly discuss ETL and its advantages. Then you will learn about Microsoft SSIS ETL and how you can set up your ETL Pipeline with Microsoft SSIS.

Most Important Features of SSIS

SSIS comes with a plethora of features that help users manage data. A few features of SSIS are listed below:

1) Built-in Data Connectors

With the release of the new version of SSIS, it supports many built-in connectors that allow users to establish connections with data sources using connection managers. 

It supports Text, XML, Excel sheets, Relational Databases that have reference data, and Analysis Service Databases. SSIS can connect to WMI (Windows Management Instrumentation), SMO (SQL Server Management Objects), messaging queues, and mail servers. SQL Servers are used for transfer tasks and temporary work tables.

2) Transformations and Functions

SSIS offers many transformations and functions that are built-in, and developing software is easier to use. It comes with various types of transformation that include BI (Business Intelligence) Transformations, Row Transformations, Split and Join Transformations, Rowset Transformations, Auditing Transformations, and Custom Transformations.

Each transformation also provides different kinds of transformations for cleaning and mining data, creating and updating columns, etc. Split and Join transformations can distribute rows in various outputs.

3) Fuzzy Grouping and Lookup Transformation

Users can use Fuzzy Grouping to clean data by detecting near-duplicate data and canonical rows to standardize the data. The Fuzzy Transformation looks for near value based on the score value provided by the user. 

The Fuzzy Lookup Transformation performs data cleaning activity by standardizing it, correcting the data, and filling the missing values. The SSIS uses Fuzzy Lookup Transformation to locate the similar near values in a reference table.

4) Data Profiling Tools

The Data Profiling Tools that SSIS offers are the Data Profiling task and Data Profile Viewer. The Data Profiling task is used to profile data in the server and perform data quality checks. All this process is accomplished by computing profiles so that users can learn more about the data source.

The Data Profiling Viewer allows users to review the Data Profiling task and it supports drill-down capabilities that help users understand data quality.

Prerequisites

You need to make sure that you have the below software installed and set up before creating an SSIS ETL:

• Microsoft SQL Server
• Microsoft SSIS software
• Microsoft Visual Studio

Steps to Set up an ETL Package in SSIS ETL

Follow the below-given steps to create an SSIS ETL package:

• Step 1: Creating a New Project and Package
• Step 2: Configuring the Flat File Connection Manager
• Step 3: Configuring the OLE DB Connection Manager
• Step 4: Configuring the Data Flow Task
• Step 5: Configuring the Source
• Step 6: Configuring Lookup Transformations
• Step 7: Configuring the Destination

Step 1: Creating a New Project and Package

Open Microsoft Visual Studio. In the window go to File, then go to New and click on Project. A Project Dialog Box pops up.

You can use existing templates or create a new one. In the Name box, provide the name for your project and browse the file location, and set your project location. Now click the OK button. By default, an empty package with the name Package.dtxs is created. Right-click on it to rename it.

Step 2: Configuring the Flat File Connection Manager

Flat File Connection Manager will help you extract data from Flat Files. Configuration of Flat File Connection Manager is different for different file formats.

To add the Connection Manager to your SSIS ETL project go to Connection Manager in the Solution Explorer pane and right-click on it and select New Connection Manager. Select Flat File from the dialog box that pops up and click on Add.

Now add the Connection manager name and browse the Flat File source. Configure the source in the Solution Explorer pane and click on the OK button.

Step 3: Configuring the OLE DB Connection Manager

OLE DB Connection Manager is used to connect to the data destination.

To add the OLE DB Connection Manager to your SSIS ETL, go to the Solution Explorer pane, right-click on the Connection Manager and select New Connection Manager. Select OLEDB from the dialog box that pops up and select Add.

In the Configure Connection Manager dialog box, click on New. Enter localhost as Server name. Set your connection and test the connection using Test Connection. Click on the OK button when done.

Step 4: Configuring the Data Flow Task

Data flow Task helps in cleaning, transforming, and moving data using SSIS ETL.

To add a Data Flow task go to the Control Flow tab. Now in the SSIS Toolbox pane, expand Favorites. In the Control Flow tab drag a Data Flow Task onto the design surface. Right-click the new Data Flow Task, select Rename and provide a new name.

Right-click on the Data Flow task and select Properties. In the Properties window, verify that the LocaleID property is set to English (United States).

Step 5: Configuring the Source

Select the Data Flow tab and go to the SSIS Toolbox. Expand OtherSources and add the Flat File source by dragging it into the design surface of the Data Flow tab.

Right-click on the newly added Flat-file source and rename it. Double click on the Flat File source and go to the Flat-file connection manager field from the editor dialog box. Select Flat File source data and select the required columns and check the column names and click on the OK button.

Step 6: Configuring Lookup Transformations

A lookup transformation performs a lookup by joining data in the specified input column to a column in a reference dataset. The reference dataset can be an existing table or view, a new table, or the result of an SQL query.

Go to the SSIS Toolbox and expand Common. Now drag lookup onto the design surface of the Data Flow tab. You can now configure the lookup on the design surface to perform transformations.

Step 7: Configuring the Destination

When you reach this step your data is in a transformed format compatible with the destination. To configure the OLE DB destination go to the SSIS Toolbox. In the toolbox expand Other Destinations and drag the OLE DB Destination onto the design surface below the lookup transformation.

Connect all the components together on the design surface to define the flow. Navigate to the Input Output Selection dialog box. In the Output list box, select Lookup Match Output, and then click on the OK button. Rename your destination component. Now double-click on the component and configure the destination in the Editor dialog box. Now click on the Ok button.

Pros and Cons of SSIS

Companies should choose SSIS as per their business needs. Many companies today use SSIS. A few advantages and disadvantages of SSIS are listed below:

Pros

• It has a user-friendly graphical interface that makes it easier to use.
• It is easy to deploy and configure.
• It allows developers to save time by reusing the script across multiple projects.
• It offers connections to many data sources.
• It is easy to set up, manage and configure projects and packages.

Cons

• It is not quite efficient with JSON.
• The learning curve is high for new users.
• Limited Excel connections.
• There are very few 3rd party tools that support SSIS.
• It involves complex coding and requires experienced developers.

Best Practices for SSIS ETL

• Keep packages modular: Break down large tasks into smaller, manageable packages.
• Use configurations: Externalize configurations to make packages easier to deploy across environments.
• Optimize data flow: Minimize the use of blocking transformations and optimize performance.
• Log everything: Set up logging to monitor the ETL process and quickly identify issues.
• Secure sensitive data: Encrypt sensitive information and use secure connections.

Why is SSIS a Good ETL Tool for You?

SSIS is used by many big enterprises and can easily manage complex data. Working with SSIS requires very skilled SQL developers because it involves coding in Visual Studio with big margin errors.

SSIS is a good choice for your company has large and complex volumes of data. Apart from SSIS, there are many ETL tools available in the market with much less complexity such as Hevo. 

Conclusion

Though you can create your pipeline with Microsoft SSIS ETL, it is a long and tedious process and you can easily be stuck despite following tutorials. It also houses support for limited source and destination options. So, use Hevo Data and spend your valuable time analyzing your data instead of working on these menial configurations.

Integrating and analyzing your data from a huge set of diverse sources can be challenging, this is where Hevo comes into the picture. Hevo is a No-code Data Pipeline and has awesome 150+ pre-built integrations that you can choose from.

Hevo can help you integrate your data from numerous sources and load them into a destination to analyze real-time data with a BI tool and create your Dashboards. It will make your life easier and make data migration hassle-free. It is user-friendly, reliable, and secure.

Check out the Hevo Pricing details here. Try Hevo by signing up for a 14-day free trial and see the difference!

FAQ on SSIS ETL