TELEMETRY PIPELINES & DATA TRANSFORMATION:
THE KEY TO
BETTER OBSERVABILITY
Observability data can be complex and difficult to analyze. Telemetry pipelines offer a powerful and cost-efficient wayto combine, analyze, and enrich your data, making it easierto spot patterns and gain valuable insights. However, youneed to be able to transform your data to get actionableinsights, better visibility, and make informed decisions tooptimize system performance and user experience.
Here's what you need to know to get started with datatransformation and take your observability to the next level.
WHAT IS DATA TRANSFORMATION?
Data transformation is the process of converting data fromone format to another. Common transformations includereducing, aggregating, enriching, compacting, flattening,deduplicating, dropping, encrypting, sampling, and parsing.
Combine multiple events over time into one basedon a set of criteria.
Merge multiple data sources into one.
Add contextual information to make it easierto interpret
Merge two or more fields within a data set together.
Take data that currently exists as a single field andbreak it into separate fields.
Remove redundant information from a data set.
Remove certain types of information from a data set.
Encrypt specific fields within a data set.
Extract only a certain portion of data from a largerdata set.
Convert data from one format to another.
Automate data transformation
Transform within your pipeline
Establish data governance rules
Don't compromise quality
Assess data transformation costs
WANT TO LEARN MORE ABOUT TRANSFORMING YOUR DATA WITH TELEMETRY PIPELINES?
Check out this blog for a deeper dive into datatransformation and how it can help your businessgain deeper insights, reduced costs, and improved overall efficiency.