How to Choose the Best ELT Tool for Your Needs?
Picking the best ELT tool is important to drive your business’s growth and innovation. The right ELT tool will empower your decision-making, improve agility, and contribute to your data-driven organization. This blog post analyzes the critical factors you need to consider before picking the best ELT tool for your specific needs. The image below provides some examples.
What Is an ELT Tool?
ELT (Extract-Load-Transform) is a data integration process. It transfers data from a source server to a data warehouse or data lake on a target server. It uses the target system to perform real-time data transformation.
Since the ELT approach uses raw data, it requires fewer resources and reduces physical infrastructure. Thus, it can be extremely useful for business intelligence and big data analytics.
ELT tools are data integration software platforms that support the ELT process. They allow companies to move and transform large quantities of data quickly. As opposed to ETL tools that are better suited for structured data and legacy on-site data warehouses, ELT facilitates the scalability of cloud data.
- ELT tool use comes with a wide range of benefits, such as:
- Simplifying and streamlining project management,
- Leveraging new technological developments to improve security and compliance,
- Simplifying potential future data warehouse structure changes and lowering costs.
There are many ELT tools available on the market. Therefore, selecting the one that best supports your organization is essential to reap these benefits.
Below, we’ve outlined the top 8 factors you need to remember.
Key Factors to Consider When Choosing the Best ELT Tool for Your Needs
1. Data Source Connections
It is crucial that your ELT tool of choice fully supports your workflows and can connect all the data sources your organization is using. As shown in the image above, our example lists Google Analytics, Shopify, Google Ads, Stripe, HubSpot, and CSV files.
Similarly, list all your data sources and make sure your ELT tool can connect to each. Otherwise, you might need to switch between several tools, increasing maintenance costs.
In addition, it is also crucial that the tool you choose can easily and effectively access data. This will ensure accuracy and consistency.
2. Data Destination Connections
Next, check whether the ELT tool you plan to use can connect to your data warehouse. We haven’t defined any mechanism in our image example, but Google BigQuery, Amazon Redshift, and Snowflake are significant players. So, you’re likely to be using one of these solutions.
3. Data Security and Regulatory Compliance
Check if your ELT tool is regulatory compliant with GDPR, SOC2, HIPPA, and other relevant regulations. It should also facilitate different user roles, from administrator to read-only.
4. Logging Mechanism
After the execution ends, it is crucial to know the details of the execution. This includes information such as: Whether the execution has been successful, in the case of an unsuccessful execution, what the error is, who triggered it, and when it started/ended.
5. Performance
ELT processes handle large amounts of data, and multiple data flows. As the processed data volume increases, it will require more execution time. Hence, it is essential to test how much time it takes to complete the operation. If the transferable data size is less than 1 million rows, it must be done within a few seconds. However, it might require more time if it is over 1 billion. If the operation completes slowly, having a bulk load option might help speed up the process.
6. Incremental Update
The incremental update method is handy since only the new/updated rows will execute. This will reduce the cost of operation compared to a full update. Therefore, your ELT tool needs to detect the changes in the data sources to perform incremental updates.
7. Reverse ETL functionality
Reverse ETL is moving data from a data warehouse into third-party systems like HubSpot, Salesforce, and Google Ads for taking action. Thus, Reverse ETL solutions have become popular and are a useful part of the stack to maximize data usage.
8. Budget
Using open-source ELT tools is free. However, self-service data processing requires more manual work. This increases the amount of development/maintenance by your in-house team of data engineers. Most cloud-based ELT tools provide a pay-as-you-go model to automate data management based on the number of rows added/updated. You can read more about ELT tool pricing on our blog.
Pick the Best ELT Tool for Your Business with Datrick
Choosing an ELT tool that best supports your business goals is vital for you to grow, scale, and innovate. Datrick specializes in helping businesses use ELT tools to best benefit their workflows and processes.
We can help you run your ELT service, build data pipelines, and assist you with its maintenance. Feel free to schedule a consultation to review your ELT needs.
