Are you confused about What is an ETL Tool? Do you want to gain a clear idea about how ETL Tools work and how they come in handy for a business? Well, look no further! This article aims at providing you with an in-depth guide about ETL Tools. It will help you gain knowledge about their use cases, types and why they are a must for any business!
Upon a complete walkthrough of the content, you will have a clear idea about ETL Tools work, about their features and how you can evaluate them before making a choice.
Table of Contents
- Introduction to ETL
- Understanding the use of an ETL Tool
- What is an ETL Tool: Use Cases for ETL Tools
- Understanding the need for an ETL Tool
- What is an ETL Tool: Types of ETL Tools available in the market
- What is an ETL Tool: Factors to consider while evaluating an ETL Tool
Introduction to ETL
ETL stands for Extract, Transform and Load. In simple terms, ETL would perform the following steps:
- Data is extracted from one or many sources into a staging area
- Within the staging area, data is transformed into usable formats by converting data types, combining fields, etc. depending on the business use case
- Finally, the transformed data is loaded to a destination – often a data warehouse
Just this definition would not help completely understand what is an ETL tool. However, the answer to the next question will.
Understanding the use of an ETL tool
Data is often scattered across different systems and applications. Companies may have client and product information in a CRM, such as Salesforce, the accounting data may be in Quickbooks, legacy data stored in Excel spreadsheets, and the website transactions may be in a database like MySQL.
In order to derive meaningful insights that can grow the business, it would be necessary to bring data from all these disparate data sources together in a useable format, to a single source of truth – a Data Warehouse.
ETL tools have been developed in response to a clear need for methodologies to simplify and enhance the process of getting the raw data scattered across multiple systems into a data analytics warehouse.
To be able to help you understand what is an ETL tool, this article will dive into some of the use cases where an ETL tool will be used. The article also gives an overview of the ETL tools available and end with a checklist of what you need to look for when evaluating an ETL tool.
What is an ETL Tool: Use Cases for ETL Tools
Here is a list of some of the most popular use cases where ETL Tools come in handy:
Building a Data Lake
A Data Lake is a central repository used to store data in its raw format. For instance, some of the key sources of data are unstructured or semi-structured. For example, text messages, web pages, video, other multimedia are all examples of unstructured data. A data lake is built for a use case where there is no need to define a schema prior to getting the data into a data lake. This means companies can store all the data for future use without having to know what kind of business intelligence questions they may have to answer.
An ETL tool can help bring data from disparate data sources into the data lake in a hassle-free fashion.
Building a Data Warehouse
In today’s world, this has become one of the most common use cases for ETL.
Data Warehouse is a structured environment. Data from the various data sources used by the business will need to be cleaned, enriched and transformed before it can be loaded to the warehouse. Once in the warehouse, this data becomes a ‘single source of truth’ for the company. The key step in setting up a data warehouse is to ensure that the data loaded is indeed accurate and up-to-date and will function as the needed ‘single source of truth’.
An ETL tool can facilitate the above use case with ease and produce trustworthy data load.
Setting up Data Migration
When businesses decide to move from Legacy systems to an updated infrastructure, they rely on an ETL tool to help with the heavy Data Migration involved. This might include extracting the data from source systems, transforming it to a format the new system understands, and loading this to the new infrastructure. Data migrations are often a one-time affair.
Simplify ETL with Hevo’s No-code Data Pipelines
Hevo Data, a No-code Data Pipeline helps to transfer data from 100+ sources and load it in a data warehouse of your choice to visualize it in your desired BI tool. Hevo is fully-managed and completely automates the process of not only loading data from your desired source but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.
Check out what makes Hevo amazing:
- Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
- Schema Management: Hevo takes away the tedious task of schema management & automatically detects schema of incoming data and maps it to the destination schema.
- Minimal Learning: Hevo with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
- Hevo Is Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
- Incremental Data Load: Hevo allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.
- Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
- Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.
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Understanding the need for an ETL Tool
Now that you understand what is an ETL tool, the next step is to understand – Why are they needed?
All the above use cases can be achieved without using an ETL tool as well. Many businesses attempt building a custom solution to solve this problem. However, there are many reasons that make it hard to be 100% successful at it. Here is why ETL tools prove to be a better alternative.
- Building custom code for ETL is not a straightforward process. However, there are way too many caveats, complexities, and difficulties in monitoring the accuracy and consistency of data. Any misses there can cause irreparable data loss
- As the business expands, new data sources come on the radar and will need to be added to the data warehouse. This adds to the engineering workload and would be hard to achieve in an ad-hoc fashion
- Cost and overhead of resources needed to maintain custom ETL scripts and infrastructure is super high
A powerful ETL tool streamlines all the ETL process and minimises the overhead. A reliable ETL tool will also come with built-in monitoring and alert system which keeps the data infrastructure abreast of any breakdowns or hitches. All of this combined will give reliable, consistent and accurate data so that businesses can focus on deriving meaningful insights.
What is an ETL Tool: Types of ETL Tools available in the market
The ETL tools that are available today can be classified based on two dimensions: Batch Vs Real-time and OnPremise Vs Cloud. Each of these serves a unique purpose. You can learn more about them from the following sections:
Batch ETL tools Vs Realtime ETL Tools
A traditional method of getting the data to a destination is to use batch processing. The data will be extracted, transformed and loaded into the data warehouse in batches of ETL jobs. This is cost effective as it consumes limited resources in a time-bound manner. Some of the top batch ETL tools are:
Today, the need to collect and analyze the data in the shortest possible time has increased. Whatever be the data source, it needs to be cleaned, enriched and loaded to the destination in real-time. This is where the need for a real-time data integration tool came into play. Real-time ETL tools help get the most efficient time-to-insight ratio.
The top Real-time ETL tools available are as follows:
On-Premise Vs Cloud ETL Tools
Many businesses run on legacy systems that have both the data and the warehouse set up on premise. This is mostly implemented from a data security perspective – where the data does not go out of the network of the organization. In such cases, businesses prefer having an ETL solution that is compatible to run on-premise. Here are some of the top on-premise ETL tools:
On the other hand, new-age businesses have all their data residing on various applications hosted on the cloud. Given the data now resides on the cloud, businesses are increasingly moving to cloud data warehouse that allows them to leverage the flexibility and agility that the cloud infrastructure offers.
A cloud ETL tool is built to enable easy data movement from the data sources used by new-age businesses to a cloud destination. Here are some of the top cloud ETL tools:
What is an ETL Tool: Factors to consider while evaluating an ETL Tool
A strong ETL tool will be an invaluable part of the data analytics stack of a data-driven business. The ETL tool selected should connect to all the data sources used by the company; have a glitch-free work interface, and provide a reliable, accurate and secure data load.
The following set of questions will help you select an ETL tool:
- What are the different data sources that the tool can bring data from?
- Are there any limits on the scale/volume of data the tool can handle?
- How does the tool handle errors? Does it ensure data consistency and accuracy?
- How smooth and efficient are its data transformation capabilities?
- How easy is the tool to use?
- How smooth is the and how soon can the project see the light of the day?
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Tell us about your experience of learning about ETL Tools! Let us know in the comments section below.