Data Observability: A Full Guideline for Business Leaders
In this Article:
If a data leak is an issue that might cause sky-high penalties and damage the corporate reputation, data observability is a Chip and Dale that are coming to the rescue. It still doesn’t say anything for most business leaders, but we’re here to change it. Read on to explore:
what data observability is and why it matters
what requirements are crucial to perform data observability
where to start data observability implementation
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What is data observability in plain language?
Data observability is something like data monitoring we’re used to. When performing data monitoring, specialists usually check sources, accuracy, volume, and relevance. The same goes for data observability. Meanwhile, this process is much broader. It includes actions, software, and equipment that allows enterprises to optimize and boost data processing, ensuring a high level of security.
Data observability helps business leaders streamline work with data: track information and manage it using the complete set of technologies. It’s convenient and reasonable, considering that the entire commercial activity is now based on corporate and customer data. The process we’re talking about is a key to ensuring data health by solving any issues in real time with metrics, logs, and traces.
Despite its obvious importance for a business-side specialist, data observability is crucial for developers since it helps them immediately explore the root of problems and keep the infrastructure safe. This approach eliminates the risk of zero-day vulnerability attacks and prevents any attempts to acquire data illegally.
Core business benefits of data observability
The ability to define the root cause of an issue allows for making work with data transparent by showing its entire lifecycle. Due to data observability, developers can determine weaknesses and fix them in real-time regardless of their nature.
The clear data processing and usage of the entire ecosystem of tools for this purpose allow businesses to automate the collection and sorting of data to keep their health on the radar.
With data observability, developers can track enormous volumes of data, dive into its interaction with software, and route inside infrastructure. This approach helps to define and prevent potential risks that might turn into huge problems in the future.
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Top 5 requirements to data observability you should know about
Five pillars make data observability efficient and help companies work with information in the right way. Mostly they are related to data quality features that should be kept. Among these requirements are:
Freshness. This pillar allows you to track how relevant your data is and how regularly they are updated. Using updated information, business leaders can perform decision-making based on accurate and checked information.
Quality. Despite well-designed data processing, the information you collect and use might be irrelevant. Therefore, this metric enables you to define whether you can trust the data used or not.
Volume. This pillar helps to set up a relevant data volume you can use as a pattern. Any deviation from the norm for no reason may indicate a problem.
Schema. Schema allows you to shadow the changes in your information and define broken data. It helps specialists to track the entire history of data usage, providing certain times, names, purposes, etc.
Lineage. This pillar delivers knowledge of how data assets are connected upstream and downstream, what's happened in case of any issue. What sectors are damaged, what users were involved, etc.
How to implement data observability efficiently: top three tips
Transform the data tracking structure
To ensure proper data observability and benefit from transparent and flexible data processing, you should prepare your business process for changes. The starting points are transforming current business processes around data processing and creating a data tracking structure. It’s a core for efficient control and ensuring high data quality.
Make sure your software is integrated
Data observability is always about working with a broad range of software solutions. This is its core feature - ensuring complete control over information regardless of the product used. Therefore, you need to take care of smooth integrations between the components of your IT infrastructure and build an integration with the proper data tracking software of your choice.
Find the data platform
You’ll need a data processing center to make it a core of the entire process. To perform data observability correctly, you need to build the entire infrastructure to create consistent, standardized data. This approach allows for advanced data collection, monitoring of information, and access.
Let us know if you’re looking for more details on how to empower your enterprise with data observability. Our experts will advise you on the most appropriate starting point.