What is Extensible Data Observability?

You’ve seen the headlines—data breaches are becoming more and more common. In the past year alone, we’ve seen major data breaches at companies like Equifax, Yahoo, and Uber. And with GDPR now in effect, data privacy is more important than ever before. So how can you protect your company’s data? The answer is extensible data observability.

Extensible data observability is a methodology for tracking the quality of your data. By monitoring your data for changes, you can be confident that your data is accurate and up-to-date. In this blog post, we’ll take a look at what extensible data observability is and how it can help you increase confidence in your data.

What is Extensible Data Observability?

Extensible data observability is a methodology for tracking the quality of your data. By monitoring your data for changes, you can be confident that your data is accurate and up-to-date.
There are three main components to extensible data observability:

1. Data discovery: identify which data sets need to be monitored
2. Data monitoring: track changes to the data sets over time
3. Data analysis: interpret the results of the monitoring to identify quality issues

Why is Extensible Data Observability Important?

Extensible data observability is important because it helps you increase confidence in your data. In today’s world, data quality is more important than ever before. With GDPR now in effect, companies must be able to demonstrate that they are taking steps to protect their customers’ personal data. By monitoring your data for changes, you can be confident that your sensitive information is accurate and up-to-date.

How Can I Implement Extensible Data Observability?

There are a few different ways to implement extensible data observability:
1. Use an existing tool: there are a number of tools on the market that can help you with extensible data observability. Some examples include Alation, Infogix, and Tamr.
2. Build your own solution: if you have the resources and expertise available, you can build your own solution from scratch. This option gives you more control over how your system works and how it integrates with other systems in your company.
3. Use a combination of tools: depending on the size and complexity of your organization, you may find that a combination of existing tools and custom solutions works best for you. This option allows you to take advantage of existing tools while still being able to tailor the solution to meet your specific needs.

Extensible data observability is a valuable tool for any organization that wants to increase confidence in itsdata. By monitoring yourdata for changes, you can be confident that your information is accurate and up-to-date—which is especially important in today’s world of heightened concern overdata privacy. There are a number of different ways to implement extensible dataobservability, so there’s no excuse not to start using it in your organization today! https://dqo.ai/