The Biggest Mistakes You'Re Making With Batch Data Processing
Posted on: 28 November 2022
Many businesses will make batch data processing mistakes that cost them time and money. Batch data processing is the process of performing a series of tasks on a group of data items, all at once, instead of one item at a time. This can be done in-memory or by writing the batch to disk.
However, most businesses don't take advantage of the benefits of data processing because of a few common mistakes. This post highlights three batch data processing mistakes and how to avoid them.
Not Taking Advantage of Parallelism
When batch processing data, it's important to take advantage of parallelism. This simply means running multiple tasks in parallel instead of one after the other.
For example, when batch processing a large dataset, you can break it up into smaller chunks and process each chunk in parallel instead of sequentially. This can dramatically speed up batch data processing, allowing businesses to process data faster and more efficiently.
However, if your batch processes lack multi-threading and batch size optimization features, you're likely missing out on the benefits of parallelism. To take full advantage of batch processing, make sure your batch data processing systems support multi-threaded batch processing and batch size optimization.
Incorrect Data Inputs
Batch data processing relies on the quality and accuracy of the data inputs. Errors in batch data input can lead to incorrect batch processing results, which can cost time and money. Remember that even a small error can result in a cascade of processing errors that can take a long time to clean up. They might even go unnoticed in some cases, which can leave you at a huge disadvantage.
To ensure batch data processing accuracy, always double-check your batch data inputs for any discrepancies. This includes checking for corrupted or missing data, as well as ensuring your batch input data is in the proper format and order. Make sure you have a robust batch data input validation process in place to catch these errors before they make things worse.
Not Utilizing Database Indexes
Database indexes are a great way to speed up batch data processing, but many businesses fail to take advantage of them. Database indexes help batch processes run faster by quickly locating data in the database without having to search through every row and column for a particular record. Without a database index, batch processes can be extremely slow and inefficient, resulting in huge time losses.
To ensure batch processes are running efficiently, always create database indexes on batch data tables. This will drastically reduce batch processing times and boost overall batch process performance.
If you need extra help, seek out a batch processing consultant who can help you optimize your batch data processes. They can even help you create batch data-specific indexes to speed up batch processes even further.
For more information, contact a local company, like Data Science & Engineering Experts.
Share