The concept of data compression has been around for nearly 200 years. It has been refined over the years to meet an increasing drive for efficiency. This advancement is fortunate since individuals and organizations now collectively create more digital data than ever before. Data compression can have a significant impact on not only the costs of storing this data but the efficiency of processing it.
In this article, you’ll learn some tips for compressing your big data. These tips can help you reduce costs, increase efficiency, and hopefully gain greater insights.
5 Tips for Compressing Big Data
Big data can be challenging to compress due to the volume of data, the limitations of tools, and the need to retain fine detail. The following tips can help you overcome some of these hurdles.
1. Choose File Formats Carefully
A large portion of big data is collected and stored in a JavaScript Object Notation (JSON) format. Particularly, data that is collected from web applications, as JSON is the format commonly used to serialize and transfer this data. Unfortunately, JSON is not schema-ed or strongly typed, making it slower when you use it with big data tools, like Hadoop. To improve the performance of your JSON files, you ...
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