Why Data Reliability Should Be the Top Priority: Understanding the Importance and Benefits
Reliability is an important aspect of our daily lives. We rely on many things and people to function smoothly and consistently to achieve our goals and complete our tasks. Here are some examples of reliability in daily life;
- Transportation: We rely on public transportation, such as buses, trains, and planes, to get us to our destinations on time and safely.
- Technology: We rely on our electronic devices, such as computers, smartphones, and tablets, to work consistently and without interruption.
- Healthcare: We rely on healthcare providers, such as doctors and nurses, to provide us with accurate diagnoses and effective treatments.
While there are hundreds of things that we rely on in our daily lives to proceed, how much do we trust the data we consume and produce?
In this article, I will walk you through reliability in the software engineering domain, how they manage it elegantly, how it is related to data reliability, and things data teams can do to achieve data reliability in their organizations.
Reliability in Software Engineering
In software engineering, reliability refers to the ability of a software system to perform its intended function without failure under specified conditions and for a specified period. A reliable software system behaves as expected and is available when needed, without errors or crashes.
Every software engineer should pay attention to scalable and reliable software architecture. In a world aiming for 100% uptime is less likely to happen compared to meeting with Smurfs, we should be prepared for downtimes. But who should be prepared for the unpredicted? Who are the firefighters in IT?
How was Site Reliability Engineering (SRE) founded?
Site Reliability Engineering (SRE) was founded by Google in the early 2000s. Google faced significant challenges in managing its large-scale, complex systems and services, which were growing rapidly and becoming increasingly critical to the company’s business operations.
Traditional IT operations approaches were not sufficient to address these challenges, so Google began to develop a new approach that combined software engineering and operations to create a discipline focused on reliability, scalability, and maintainability. This new approach became known as Site Reliability Engineering (SRE).
What are the most important responsibilities of the SRE team?
Overall, the responsibilities of an SRE team are focused on ensuring that the systems and services they manage are highly reliable, available, and performant and that they can scale to meet current and future demands. Below we can deep dive into the details;
Ensuring reliability: The primary responsibility of an SRE team is to ensure that the systems and services they are responsible for are highly reliable and available. This involves monitoring system performance and identifying and resolving issues quickly, as well as designing and implementing fault-tolerant architectures and redundancy mechanisms.
Automation: SRE teams automate as much of their work as possible to reduce manual effort and ensure consistency and repeatability in operations. This includes automating deployment, monitoring, and recovery processes.
Incident response: SRE teams are responsible for responding to incidents and outages, identifying the root cause of the problem, and implementing fixes to prevent similar incidents from occurring in the future.
In a nutshell, SRE teams are the superheroes and superheroines that keep our applications running 7/24/365.
From Application Downtime to Data Downtime
Application downtime refers to the period when a particular application or software system is not available for use or experiences a significant reduction in functionality.
Downtimes can happen anytime due to any reason. Even though organizations make enormous amounts of investments in their IT infrastructures, many of them face catastrophic downtimes. Below you can check out the top 10 outages of 2022;
Data downtime refers to a period during which data is not accessible or unavailable. During data downtime, users may be unable to access or use the data, which can result in disruptions to business operations, loss of productivity, and missed opportunities. Is data downtime important?
Why is Data Downtime the Next Big Thing?
From self-serve analytics to ChatGPT, from autonomous cars to skin cancer detection, data products are the future. No one wants to use a product that requires additional effort from the user. We want everything personalized and automated with the most updated information in our reach.
The competitive advantage of a data product is the data behind the product. Either data is consumed or produced, doesn’t matter. If the data is the core of the data product, just imagine what happens during data downtime. There will be no competitive advantage for that product. If that is the case why don’t we think about data reliability?
What is Data Reliability?
Data reliability refers to the accuracy, consistency, and dependability of data. Reliable data is trustworthy and can be used effectively for business decision-making, research, and other purposes.
Data reliability is important for several reasons;
- Business decision-making: Reliable data is essential for making informed and accurate business decisions. If the data is unreliable, decisions based on that data could lead to mistakes, lost opportunities, or even damage to the company’s reputation.
- Operational efficiency: Reliable data is necessary for organizations to operate efficiently. Inaccurate data can lead to delays, errors, and increased costs, while reliable data helps ensure that operations run smoothly and effectively.
- Compliance: Many industries and organizations are subject to regulations that require them to maintain accurate and reliable data. Failure to comply with these regulations can result in fines, legal liabilities, and other consequences.
Overall, data reliability is critical for the success of organizations in today’s data-driven business environment. It is essential for making informed decisions, operating efficiently, complying with regulations, satisfying customers, and gaining a competitive advantage.
Conclusion
Even though software reliability and software reliability engineering are well-known and applied concepts, we are far away from perfection in data reliability. With the speed of AI getting into our jobs, organizations, and lives, we need to establish more trustworthy and reliable data products. In this regard, the data reliability topic should be the top priority for any organization that is relying on data to build its competitive advantage.
Thanks a lot for reading 🙏
In the upcoming articles, I will focus on how to ensure data reliability in our organizations with various methods ranging from developing SLAs to data observability.
If you want to get in touch, you can find me on Linkedin and Mentoring Club!
