Many businesses have vast amounts of data, such as sales records and customer information, stored in various formats across different locations. Data transformation is the process of converting this data into a new format that organizations can use to analyze and interpret data to make business decisions and identify opportunities for growth. If you work in the fields of data science or business intelligence, you may want to learn about some data transformation tools to help you perform this process quickly and efficiently.
In this article, we describe how data transformation works, explain who typically performs this process, and provide a list of nine data transformation tools to help you choose one for your organization.
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How does data transformation work?
Data transformation is the process of converting raw data into a different format. It’s one part of the ETL process, which stands for extract, transform, and load. During this process, businesses extract data from various internal and external systems and load the information to its destination, which is typically a centralized collection of data known as a data warehouse. Data transformation, which can take place before or after the loading process, organizes and structures the data in a format compatible with the data warehouse. Businesses can use this newly converted data to make key decisions and accomplish their strategic goals.
Data transformation can be simple or complex depending on the differences between the format of the source data and the required format of the destination. Organizations can complete the data transformation process manually, automatically, or through a combination of both methods. The process of transforming data typically involves multiple steps, which may include:
Data discovery: During this step, data analysts, developers, or others identify the source format of the data to determine how to convert it to the required destination format.
Data mapping: This step involves planning how to transform the data into a new format, such as by using an ETL tool or a scripting language.
Code: During this step, developers or analysts create and execute a code, typically by using a data transformation tool, to convert the data into the desired format.
Review: The final step of data transformation involves reviewing the converted data to make sure it’s formatted correctly.
Who uses data transformation?
Many professionals may use data transformation as part of their jobs. Typically, developers, data analysts, or data scientists perform the process of converting data by using scripting languages, such as Python, or domain languages, such as SQL. In the final step of data transformation, professionals responsible for making key business decisions typically review the data for analysis. These professionals may include business intelligence analysts or specialists, directors or CEOs. They may use charts, reports, or dashboards to review the transformed data to help them understand their customer base, develop strategies to increase revenue, or make decisions related to business operations.
9 data transformation tools
Data transformation tools can help automate the process of converting data to improve efficiency. These tools can transform large amounts of data quickly, often within minutes. Here are nine data transformation tools with an explanation of their features to help you choose one for your organization:
1. IBM DataStage
IBM DataStage, developed by IBM, is a data transformation tool that designs and runs code to convert data. The basic version of the software supports on-premises deployment, which means data transformation can only occur at an organization’s physical location. The upgraded version of DataStage automates data transformation in a cloud-based environment. DataStage can transform data through both ETL and ELT processes, which means it can occur before or after loading the data to its destination. Some of the software’s other features include built-in search, automated failure detection, and continuous delivery from development to testing and production.
2. Informatica
Informatica offers a data transformation tool known as the Intelligent Data Management Cloud. This platform transforms data on cloud or hybrid infrastructures. On this platform, you can map data formats using prebuilt transformations without writing code. The software integrates with traditional databases and other applications to connect various types of data sources in real-time. The platform also works with Informatica’s other data management products, including its data catalog. Informatica has various subscription plans based on different features, such as data sources. It offers a free 30-day trial for organizations.
3. Matillion
This tool consolidates large amounts of raw data to transform it into a usable format for business analytics. It extracts data from applications, files, and databases to convert it quickly without requiring coding. It offers prebuilt connectors to integrate with many industry-recognized data warehouse solutions. You can also download free connectors from other users of the platform or create new custom connectors for various applications. Matillion offers several subscription plans for organizations. Its basic plan includes unlimited read-only users, real-time validation, automation, and job scheduling features.
4. Talend
Talend offers a data integration platform that ingests data from various sources and organizes the information in a structured manner. It integrates with data types from various sources and connects to on-premises or cloud-based data warehouses. A self-service interface allows you to move data quickly and securely to a data warehouse for analysis. It provides scalability solutions for large volumes of data. The platform integrates with multiple recognized cloud service providers, data warehouses, and analytics platforms. Talend has a variety of subscription-based plans and offers a free trial for organizations.
5. SAP Data Services
SAP Data Services, developed by SAP, integrates and processes data from SAP or third-party sources through both ETL and ELT processes. The data management platform has various capabilities for data integration, quality, and cleansing. On the platform, you can develop applications for transforming data. The software supports databases, applications, files, and transports by connecting to new data sources. It integrates with other applications in the SAP Business Suite and connects to other third-party data sources. For information about pricing, contact the company for a quote.
6. Pentaho
Pentaho, which was acquired by Hitachi Vantara in 2015, integrates and analyzes enterprise data. It connects to various data sources and can move data of any size or format. The software supports both hybrid and cloud-based infrastructures. It features a drag-and-drop interface with minimal coding required. There are two versions of Pentaho, including an open-source community edition that’s free to use. The enterprise edition offers additional features, such as an expanded library of connectors and technical support. If you’re interested in the enterprise edition, contact the company for a quote on pricing.
7. Trifacta
Trifacta is an open, interactive cloud-based platform designed for data engineers and analysts. It profiles and prepares data for analytics and machine learning. The software supports data engineering across cloud, multi-cloud, or hybrid environments. Trifacta partners with industry-leading cloud providers to support data preparation workloads. It automates visual representations of data to help organizations analyze and review this information. The platform uses machine learning to guide users through the process of transforming data. Trifacta offers three pricing plans, and each one includes predictive data transformation, offline collaboration, and data profiling. It also offers a free 30-day trial for businesses.
8. RudderStack
RudderStack is a data infrastructure platform that collects, transforms and routes customer data. It’s designed for developers, data analysts, and product teams. It streams data in real-time by connecting with multiple vendors and sources. After collecting the data, you can transform it before delivering it to a data warehouse or other destination. The platform features content recommendations, personalized messaging, and customer support. RudderStack offers a free version of the platform with several features, including more than 150 cloud destinations and support for ETL and ELT processes. It offers two other paid versions with advanced features, such as data masking.
9. dbt
This software, developed by dbt Labs, transforms raw data through an analytics engineering workflow. It develops, tests, and deploys data to create datasets for business intelligence tools and operational analytics. Data analysts, engineers,, or developers who know SQL can use this software to build data pipelines and write code for data transformation. The software also offers in-app scheduling, logging,, and alerting to ensure transparency in transformation workflows. The company offers a free version of the software for one developer and two paid versions for organizations with larger data analytics teams.
I hope you find this article helpful.
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