ETL, is a three-step data integration process used by organizations to combine and synthesize raw data from multiple data sources into a data warehouse, data lake, data warehouse, relational database, or any other application.

ETL tools help you move data from one system to another. It is a convenient alternative to manually used extract, convert, load (ETL) operations.

Organizations create and use a large number of data from many different sources, in different formats and at different speeds. Capturing this data and converting it into an actionable format is the most challenging part of this whole process.

ETL tools solve this problem by:

• It collects large volumes of raw data from many data sources.
• Converts the collected data into understandable formats.
• It makes transformed data ready for use for specific business analytics or business intelligence applications.

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So why do you need ETL tools?

You can choose not to use any ETL tools and instead code by hand. Manual coding may seem like a cheaper and easier option, but as the amount of data increases and tasks become more complex, it is clear that manual coding is not a viable and cost-effective solution.

ETL tools are easier and faster to use than manual coding in the long run. ETL tools are key to processing large volumes of raw data because they provide businesses with a wide range of benefits:

Ease of use: Graphical interfaces help you to use drag and drop functions. This ease of use speeds up your process of mapping tables and columns between source and destination storage.

Advanced processing: By automatically tracking changes to your data, you can process the changed data without having to perform a full data refresh.

Advanced data cleaning and profiling: ETL tools allow you to apply and maintain complex universal formatting standards and semantic consistency across entire datasets.

Ready-to-use automations: Functions such as filtering, reformatting, sorting, merging and aggregating are ready to use.

Further control: Provides support for conversion planning, version control, monitoring, and unified metadata management.

Operational durability: Automation of various parts of the integration process is provided. Thanks to this, the possibility of manual intervention and errors is reduced.

What are the types of ETL tools available today?

ETL tools have been in use for over a decade. As technology and data integration processes change, different types of ETL solutions have also taken their place in the market. Solutions, some designed to work in an on-premises data environment and others in the cloud, today have many options for different budgets and needs.

Here is a summary of the available ETL tools:

Old ETL tools: These tools extract, convert and upload data to the target data warehouse or data lake. Batch processing tools were until recently a cost-effective option in ETL processes because they use limited resources in limited time.

Real-time ETL tools: Today, most organizations need real-time access to data from different sources. Let's say your customers visit your website for your products. You need to be able to recommend relevant products to them as soon as possible. Real-time ETL tools are designed to provide solutions to these and similar real-time needs of companies.

Open source ETL tools: These ETL tools have free source code. This method also helps organizations keep costs down while offering similar functionality to other ETL tools. Most open-source ETL tools create a modern management layer for planned workflows and bulk transactions. These tools differ in quality, integration and ease of use.

ETL tools running locally in the cloud: With the increasing number of businesses migrating to cloud systems, businesses need a solution to extract, convert, and upload data from different sources directly into a cloud data warehouse. ETL tools that run locally in the cloud allow organizations to gain significant cloud benefits such as flexibility and agility in their ETL needs.

Determining the right ETL tool: 5 key factors to consider

There are many ETL tools to choose from. So, how do you know that your wife is the best for your business?

Here are some of the key factors to consider when reviewing ETL tools:

Define your need: Your need should be one of the most critical factors in your decision. If you don't think you need real-time updates, you can opt for an existing batch ETL tool. But if you're planning to move to the cloud, ETL tools running locally in the cloud will be a much more useful choice for you.

Scalability: As your business grows, so will your need for ETL processing. Needs such as data volume, various data sources and formats, processing steps, simultaneous data uploads, third-party calls will guide you in this choice.

Error management: Sometimes unexpected issues can lead to problems in your workflow. For example, corrupted data or network failures can create an error situation. Your ETL tool should be able to handle errors. This will greatly contribute to data accuracy and consistency.

Yield improvement: ETL processes deal with large amounts of data and manage workloads through many different data streams. As the volume of data grows, so does the execution time. Your ETL tool should have features such as built-in optimization to meet changing business needs.

Cost optimization: Cost is one of the most important factors for any purchase decision. Look for ETL tools that can also offer ELT. This helps you reduce costs by using the resources at your disposal and transforming data in the data warehouse.

ETL in a hybrid and multi-cloud world

According to the Flexera 2021 Cloud Status Report:

• 92% of organizations have a multi-cloud strategy in place or in progress.
• 82% of large enterprises have adopted hybrid cloud infrastructure.

Informatica offers AI-powered cloud-native data integration that helps you build sequential layouts in a multi-cloud environment of leading-edge technologies such as AWS, Azure, Google Cloud Platform, Snowflake, Databricks.

Accelerate your ELT and ETL use cases with Informatica's free cloud data integration on AWS and Azure. Informatica's unique technology simplifies data access, allowing you to start projects faster with significant advantages:

• No-Code: Create data sequential layouts with automated data integration
• Enterprise-scale: Build and run complex integrations with high-performance data acquisition
• Connected: Harness the power of metadata sensitive connectors for the most common data model

A faster, more cost-effective cloud-based solution for your data integration needs

With AI-powered, cloud-native data integration, Informatica provides best-in-kind ETL, ELT and Elastic Spark-based data processing for any cloud data integration need. You can contact us for our industry-leading ETL and ELT tools.

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