Healthcare organizations are generating a massive volume of data annually. The amount of new healthcare data generated globally in 2020 was estimated at 2,314 exabytes. Suppose your team has to perform DB extraction for business intelligence or analysis. In that case, you may struggle with a host of challenges, from slow data extraction to network congestion and complaints from other network users. Fortunately, you can improve the performance of your ETL process by applying the following tips.

1. Locate the Sources of Congestion

Ensure that you log all the performance metrics for your extraction queries. Your logs should include the CPU and memory usage, the number of records processed, and the time required. Also, observe the resource usage of each phase of the process.

Then sort the processes in descending order of resource usage. Use the 80/20 rule to address the heaviest one. You should also look into your SQL and application code to see how you can find a more efficient route for the process.

2. Reduce Table Sizes

As tables grow large in a relational database, they can become resource hogs. This is particularly true when you have to join multiple tables in a query.

To reduce processing time, break up large tables into smaller ones. A good rule of thumb is to partition tables by date. Since the smaller tables will have their own indices, your application will have quicker access to the data.

3. Leave Out Unimportant Data

While your information systems may capture almost every piece of data possible, you don’t have to put all of that into your data analytics warehouse. For example, certain large images may not be helpful for analysis.

To boost the performance of your database extraction, define the data fields that you need to process and eliminate irrelevant rows/columns.

You may even create views with limited columns for reports. These views will be processed quickly. As the need arises, add more rows and columns to your view.

4. Use Parallel Processing

A significant bottleneck in database operations is serial processing. Many popular databases like MySQL still use a single CPU core to process queries. However, many tools take data from the database and carry out processing operations using multiple cores.

5. Upgrade Your Hardware

If you notice that your ETL process is causing the machine to run at 100% CPU all the time, you need to upgrade the hardware. Changing the CPU and adding more RAM should offer some performance improvement. Installing a CPU with more cores can improve the performance of distributed or parallel processing.

You may also move your processing to the cloud, where you can scale your hardware resources rapidly. With a cluster of machines available to you, you can execute sort and aggregate functions in parallel.

Connect to a DB Extraction Expert

MediQuant is a specialist in healthcare data migration and archiving. Contact us at 844.286.8683 or visit our contact page today to book a free consultation session.