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Top 5 Frequently Answered Questions about Modern ETL Tools

Conventional on-premise ETL solutions come bundled with a set of migraines. Usually built in-house, such tools are complicated, fragile, time-consuming, and expensive. They work on batch processing principle as opposed to real-time processing, and so can quickly become obsolete.

Modern ETL tools, on the other hand, can seize, transform, and load data from a plethora of transactions across a variety of data sources and streams to provide a wealth of new opportunities: moving information to the cloud, enabling lightning-speed analysis of historical records to optimize the sales process, adjusting prices and inventory in real-time, improving productivity, and developing new revenue streams.

But what is Modern ETL and how does it stay relevant even in today’s time? For better understanding, we have enlisted a stream of frequently asked questions and their answers about modern ETL tools.

1. What is ETL?

ETL, extract, transform, load, is a common paradigm that involves combining data extracted from multiple systems to a single database warehouse or data repository for legacy storage or analytics.

2. How ETL works?

ETL process includes 3 important steps – extraction, transformation, and loading.


Extraction, the first phase of the ETL process, is the process of retrieving data (structured and unstructured) from myriad sources, including:

·Existing databases and legacy systems

·Cloud, hybrid, and on-premises environments

·Sales and marketing applications

·Mobile devices and apps

·CRM systems

·Data storage platforms

·Data warehouses

·Analytics tools

After the retrieval process, ETL tools load data straight into a staging area and prepare it for the next phase i.e. transformation.


Generally considered as the most important phase, transformation paves way for integration. It is the segment of the ETL process where rules and regulations are applied to the extracted data to ensure data quality as well as accessibility. ETL Transformation phase includes many sub-processes such as cleansing, deduplication, sorting, verification, standardization etc.

Cleansing: In this process, missing values and inconsistencies in data are detected and resolved.

Deduplication: This is the process where redundant data is discarded.

Sorting: In this process, data is organized or sorted according to the required format.

Verification: Data is verified in this process. Unusable data is eliminated and anomalies are flagged.

Standardization: In this process, formatting rules are applied to the data.

Apart from this, the transformation phase may also include some additional tasks where rules are applied to improve data quality further.

Data transformation not only enhances data integrity but also ensures that data travels safely to its new destination.


Loading is the final step of the ETL process where the newly transformed data is loaded into a new destination. The transformed data can be loaded either all at once or at scheduled intervals.

3. What are the different types of ETL tools?

Depending on how and where you want to transform the data, ETL solutions can be of several types:

  1. Batch: These types of ETL tools are exclusively designed to transfer humongous data streams at a scheduled time. Batch processing is usually carried out when network traffic is low.
  2. Open-source: These types of ETL software can be shared and modified easily as their design is accessible. Open-source ETL tools are available at a lower cost than commercial alternatives.
  3. Cloud-native: Cloud-native ETL tools are stored in the cloud. They allow organizations to leverage the expertise and infrastructure of the vendor. To boot, these tools are optimized to function with cloud-native data.
  4. Real-time: Real-time ETL tools are equipped to process data in large batches. These tools can be used to process real-time streaming data for better decision making.

4. What are some common ETL use cases?

ETL data integration tools can be used for various functions such as:

  1. Cloud Migration: Cloud migration is a process where data and applications are moved from their premises to the cloud for increased scalability and security. ETL tools are commonly used to transfer data to the cloud.
  2. Marketing Data Integration: In this integration process, marketing data, including consumer data, web analytics, and social networking information, is moved into one place for analysis. ETL solutions are employed to bring all marketing data together.
  3. Data Warehousing: Data warehouse is a repository in which data is piped to be collectively analyzed for business needs. ETL tools are often employed to transfer data to a data warehouse.
  4. Database Replication: This process takes data from various source databases, such as MySQL, PostgreSQL, Oracle, etc, and copies into an enterprise’s cloud data warehouse. ETL software is normally used to replicate data.
  5. Business Intelligence: Business intelligence involves a set of processes, technologies, and mechanics that help analyze information to allow business users make informed business decisions.

5. What are the benefits of ETL tools?

Moving data from a source database to a target data repository with the help of ETL tools has a number of benefits.

  1. Ease of Use: ETL integration tools are easy to use as they rely on an automatic course to extract, transform, and load data. Hence the need for manual coding is eliminated, making this tool easy and efficient.
  2. Improved Operational Resilience: Data warehouses are fragile and may end up as an operational disaster. With built-in-error-handling functionality, ETL tools allow enterprises to build resilient and well-instrumented data warehousing systems that are stable.
  3. Better IT Productivity: ETL tools enhance data access as they streamline extracting, transforming, and loading process. As a result, the company’s ability to make strategic and operational decisions improves greatly which, in turn, reduces IT operational work and places them on a governance role, thereby boosting productivity.
  4. High Return on Investment: ETL transforms the business intelligence landscape by offering increased access to information, thus enabling businesses to generate higher revenue.

All set to see what a modern ETL platform can do for your business? Get started today!