You're facing complex database errors. How do you convey solutions to non-technical stakeholders?

I also got in this position one time, where we need to query in multiple tables and group their data source with some complex calculations and respond them via API. Here, we were querying on some array field in different collections, and need to explain this to the PMs and other business team who were using that API and it was taking time to respond. I just told them, imagine you have a road full of speed breakers and you want to drive over there and imagine a smooth road like an highway, which one will make you reach to the destination faster ?? Then they were able to get that, so I suggested them the data structure we are using needs to be flattened , which will make our road smooth and easier to query in DB.

Database errors can be very critical for the businesses which require real time data like operational or transactional data. This can impact their overall business process. To convey a solution to non-tech stackholders, a simple example can be given - Consider the database as a library with a lot of books in different sections. Some of the sections got unorganised and it is very hard to find the books. A solution to this problem could be to organise those sections properly again with some strict rules to track down the books and ensure books are placed correctly.

Know the person in context and his area of work in context. Pickup an example from his work area, whether its a spreadsheet, or a bedsheet make sure the example very much understandable to the person in concern. Tell about the enormity of problem with comparison with what area he works in. Most of the time, we get support. In the event when no supportive words comes out, then just tell "We are taking care of the situation, situation is under control, we know the solution, we are implementing the after validation, do wait for xyz time, once solution is in place we will talk about the impact."

Many of the suggestions below regarding using non-technical terms and analogies are very good. I would also pay attention to the audience... Do they look like they understand or are they glazed over? If the latter, backtrack a bit and restate the situation. Ask for questions so that you can clarify. If on a phone call, is the someone who is normally engaged who is not now? That could be indicative of a lack of understanding as well

Les suggestions faites dans cet articles sont très bonnes. En tant qu'expert, il est très important de tenir compte de ces points quand nous présentons à une partie prenante non technique. J'opte très souvent pour la représentation visuelle de scénarios avant et après. Cela aide les parties prenantes à saisir le concept plus facilement qu’une explication verbale seule.

In my experience as a BI engineer working with ETL pipelines and data warehouses, I've found that it's crucial to highlight specific scenarios. Eg: If a database slowdown is causing service delays, I emphasize that this can lead to customer dissatisfaction and potential revenue loss, just as a misconfiguration in an ETL pipeline can delay critical business reports. By linking the technical problem to tangible business outcomes, such as reduced operational efficiency, I help stakeholders understand why a solution is imperative and how it will benefit the organization.

When we say impact, there are three things to keep in mind. 1. Business Impact: - State the situation with respect to the business, like slow response or timeout, or complete blank page, or infinite load screen, loss of revenue 2. Application Impact - increase in application load, crashes of the application, loadbalancer issues, wrong decisions, hung services etc. 3. Database impact: - Impacted operations, Resolution plan, root cause, options to solve, proposed option, estimated time for resolution.

this is most tricky thing. Everyone thinks there is a magic wand with DBA, he will swing and everything will become ok in miliseconds.... Do note, a change in production database comes with lot of approvals, testing and validations, risk identification and mitigation process, communication chains, then the change, machine executing the change, machine facing issues, service facing issues, dba fixing the issues, then machine finishing the task. So manage the expectations wisely. Quickfix, CTO/CEO or similar position approval, without testing, change in production after a safe backup.

most organisations with the appropriate monitoring framework should not find issues in providing the visualization of the impact. However to magnify the given scenario custom built graphs are required.