Top 10 World-class Data Transformation tools for 2023
- Ndz Anthony
- January 18, 2023
The only way to survive in this constantly changing and emerging tech environment is by updating our skills, tools, and strategies effectively for the optimum performance of our organization. That’s why we came up with the latest and updated list of “Top 10 world-class data transformation tools for 2023”.
Here is a brief list of all the data transformation tools mentioned in this post before drilling down into evaluating each one:
- AWS Glue
- Data Build Tool (dbt)
- Hevo data
- Apache airflow
Data analytics is centered on data transformation. However, data must first be retrieved from various sources, processed, improved, and turned into the necessary format before it can be used for analytics.
There are several kinds of tools, depending on how you wish to alter the data:
Batch: Large amounts of data are sent in batches at a certain (planned) period.
Real-time: They process real-time information as it streams into your system.
That’s some basic concepts regarding the types of tools used in the Data transformation process. Now let’s move into our main topic, “Top 10 world-class data transformation tools for 2023”.
AWS Glue works well with other products in the suite, including Amazon S3, Amazon RDS, Amazon Redshift, and Amazon Athena, as it is a component of the Amazon Web Services ecosystem.
This tool enables you to manage hundreds of ETL operations in a single catalog and transport data across several data stores.
Because AWS Glue is serverless, you just pay for the resources you use and don’t need to worry about infrastructure costs.
- Users may utilize a drag-and-drop editor in AWS Glue Studio to easily build up and manage ETL tasks.
- AWS Glue automatically detects the data format and proposes suitable schemas when you use it for data from diverse sources.
2. Data Build Tool (dbt)
DBT makes it possible for data teams to work like software developers when it comes to transferring reliable data at a quicker rate. The teams may use this platform to create reliable ML modeling, reporting, and operational procedures datasets.
To make governance simpler, dbt provides version control, testing, logging, and alerting. SOC2 Type II, ISO 27001:2013, ISO 27701:2019, GDPR, PCI, and HIPAA compliance are all met.
- SQL SELECT statements can be written to modify the data in your warehouse.
- Automatically generate dependency graphs and data dictionaries.
- Also provides scheduling, logging, and alerting within the software.
A SaaS data transformation solution called Datameer was created for the leading data cloud provider Snowflake. In this outstanding tool, Snowflake cloud handles every step of your data life cycle, including discovery, transformation, deployment, and documentation, making it one of the favorite and most trustworthy tool on the list.
You may use SQL, No Code, or both to examine and manipulate your datasets using Datameer. Both tech-savvy teams and teams with prior SQL familiarity will find this ideal.
One of its greatest and most distinctive features is its search capability, which enables Google-like database scans. Additionally, the platform offers audit trails, data lineage, and complete administration for metadata, including tags, descriptions, and attributes.
- Data Catalog: You may search throughout the entire data environment with a built-in data catalog—quick access to documentation and asset metadata to aid with movement.
- Advanced-Data Pipelines: Capabilities for versioning, deploying, and monitoring your work that is advanced. Without needing to write any code, Datameer enables you to use a developer’s capabilities.
- Full Access: Complete control of metadata, including tags, descriptions, and attributes, as well as rigorous data lineage and audit trails.
Companies use EasyMorph to arrange their data in the searchable Data Catalog, which enables easy and controlled self-service. With the help of this platform, you may get data from anywhere and automate sophisticated data conversions. Its UI is simple and entirely visual. Like Datameer, this software does not require programming or SQL knowledge.
- This program can pull data from web APIs, remote folders, spreadsheets, text files, and cloud apps, so there is no need to bring the data into a file or database.
- You may automate and alter visual data using the 150+ built-in actions that are included.
- ETL process scheduling for data transformation and retrieval, collecting, writing, and disseminating data.
Data virtualization is a feature of the Denodo Platform that combines multi-structured data sources from document management systems, database management systems, and a broad range of additional big data, cloud, and business sources.
Centralized control of data query executions for full security and complete governance and
Enabling legacy replacement, cloud migrations, and multi-cloud deployments with minimal disruption and cost.
- Connect, introspect & govern any data source with zero data replication.
- Consume & secure data views in multiple formats.
- Active Data Catalog and self-service capabilities for data & metadata discovery and data preparation.
6. Hevo Data
For databases, cloud-based programmers, and streaming services, Hevo Data provides over a hundred integrations. Data transformation pipelines may be built up quickly and without code.
Setting up a pipeline is simple since Hevo creates the data flows for you after you select your data source, provide your login information, and select the destination warehouse to load data into.
The fault-tolerant design of Hevo scales with the least delay adheres to end-to-end encryption and complies with all key certifications.
- Thanks to the user-friendly, no-code interface, anyone can create data pipelines, eliminating the technical bottleneck and saving time.
- Hevo manages all pipeline operations, reducing the expense of infrastructure installation and maintenance.
Similar to dbt, Dataform is a free and open-source data transformation solution that enables you to manage any aspect of your cloud data warehouse operations (including Panoply, Snowflake, Redshift, and BigQuery).
Dataform creates solutions for data teams to manage their data architecture. It is an open-source, free solution that aids in the management of your whole data pipeline in cloud data warehouses. You may create, test, and distribute a centralized data model among your teams with Dataform.
- You can arrange complicated tables, dependencies, and views using its intuitive browser-based integrated development environment (IDE).
8. Apache airflow
This software is an open-source workflow management tool to assist you with your data engineering pipelines. It was first developed within Airbnb in 2014 and released to the public for the first time in 2015.
In terms of data transformation technologies, Airflow is the Audi R8 that simplifies the management of massive, complicated data flows. However, consumers of Python ETL tools mostly gain from their versatility.
- As a topological representation of data flows inside the system, directed acyclic graphs (DAG) are another way complicated data operations may be organized, monitored, and scheduled using Airflow.
- It is completely developed in Python, and you can utilize all of its capabilities to build workflows without dealing with the command line or XML.
- It is the only ETL tool in this whole list which is completely free and trustworthy.
The Talend data integration platform collects data from many sources and organizes it for use in business analytics. The technology also offers scaling options for massive data volumes.
Offering three distinct models (SaaS, hybrid, and elastic), Talend Integration Cloud offers extensive connection, integrated data quality, and native code creation to support big data technologies. Hadoop, NoSQL, MapReduce, Spark, machine learning, and IoT are some big data components and connections.
- Project data flows are transformed into useful business information via Talend Project Audit. It presents an auditing methodology for assessing different Job implementations in your Talend Studio.
- In addition to using the graphical Job design interface, Talend Studio also allows you to build data integration processes using Job scripts.
Because Nexla’s no-code interface makes self-service data preparation possible, removing the need for engineers to set up data pipelines or maintain lineage. Even business users may conduct data transformation with its extensive library of transformation functions.
To help you understand how data sets have changed and who made those changes, Nexla provides automated versioning and logging. This simplifies compliance and increases the reliability of your data.
- Streaming, ETL, ELT, reverse ETL, API integration, and integration are all combined into one process.
- There is no need to enter a code or wait. Connectors that produce themselves based on setup, leading to ready-to-use data products that bring data into the application you use in the format you want.
Best Use-case tool for your Organization:
Before completing the list, do consider these quick tips for selecting the best data transformation tool for your organization or company:
- The quantity of data you have and how it is kept.
- Your current data infrastructure.
- Identify the people who use your data. Are they mostly engineers and scientists, or do you have citizen data integrators, scientists, and business users?
- Your financial situation.
- Your application scenarios.
- Ease of installation and use.
- Security and adherence to local and regional regulatory requirements.
- Reviews and testimonies on renowned review sites such as Gartner, G2, and Capterra.
Rethink data transformation with Datameer.
Datameer is an essential tool for any company that uses Snowflake for data processing, storage, and analytics. Financial services, telecommunications, healthcare, retail, travel & hospitality, and energy companies are all adopting Datameer to transform data and improve analysis and collaboration.
Book a quick call with us and we’ll get you set up asap!