A data solution is just like a car.
Perhaps not an obvious comparison at first, but bear with me and I’ll explain. I’ll also explain why, like your family wagon, it’s important to make sure that your data solution is properly serviced and maintained, lest you find yourself stranded at the side of the metaphorical data highway waiting for an angel in a high-viz jacket to get you going again.
For a modern data-driven business, investing in some kind of data analytics solution brings a lot of value, making it a worthwhile financial venture. A car is very similar: it’s a no-brainer for most families to own one, even though it is typically the second most expensive thing they will buy, after a house. From keeping the fuel tank full to replacing worn down parts, we all recognise that cars need maintenance to keep them working well; so why wouldn’t the same be true for your data solution?
I broadly split data solution maintenance into three areas, which compare nicely with the activities we do to look after our four-wheeled friends.
Operational Maintenance
Operational maintenance is the stuff that needs to happen all the time, day-in and day-out, for the solution to keep working. It’s like checking there’s enough fuel and oil in your car, air in your tyres, or tyres on your wheels. Tasks like making sure your data loads are completing properly, ensuring that you have good backups of your data, and checking that you have enough space on your disks or storage accounts. These are things that are often left to the IT department to take care of or managed by automatic systems or (hopefully) your cloud service provider – but it’s important to make sure that it is happening, and be aware of how critical these things are.
There are many infrastructure-level tasks that happen beneath the surface of any IT system, and due to the complexity and dynamism of many data analytics solutions, it’s a good idea to make sure that your IT teams or service providers are aware of and engaged when developing your solution. Conversely, it’s also wise to have some level of visibility that their services are working as expected once you’re relying on it.
Infrequent Maintenance
Infrequent maintenance tasks have a lot in common with your motor’s annual service. When you look at a car’s service history, you’ll often see that these are performed late, don’t necessarily include all the checks they should, or are simply omitted altogether some years. The reason for this in cars is simple – the car seems to be working fine, and the owner doesn’t have time to manage without it for a few days, or funds to pay for the full task, or even in some cases, proper knowledge of what needs changing and when. We all know, however, the importance of these annual services, as they will help prevent issues arising, or spot the early stages of wear and tear.
It’s just the same with data solutions. While not as clear cut as an annual service, your solution needs to be checked regularly to make sure it still meets the business requirements and performs optimally. These checks can include evaluating your organisation’s needs, reviewing your data sources (and the data itself), as well as assessing your data system’s performance.
We recommend setting up a six-monthly review schedule for key considerations like these, or more frequently if you are a fast-paced organisation.
Strategic Reviews
The third area of tasks I’ve labelled strategic reviews, and I liken them to the thought process we all go through, some with relish, some with dread: is it time to change the car?
It may be brought about by a life event – a new family member, a pet, a new hobby; it may be something unexpected – a crash, or a sudden mechanical failure; or as is common these days, it may be by design, such as the end of a lease agreement meaning it’s time to choose the next one. Whatever the reason, it’s rare that changing a car is as simple as “same again please”.
For data analytics, reviewing the suitability of the current solution should be driven by some of the activities we’ve outlined above, but you should also consider factors such as software lifecycles and unexpected events like mergers and acquisitions, or other business changes. After all, whilst data can steer the direction of the business, it’s the needs of the business that define the data requirements! Strategic reviews are therefore necessary to ensure your data solution is fully meeting your needs, and it may be helpful to seek advice or ideas from an external source. Where you might ask a car garage for their opinion on what would be best for your travelling needs, you can ask a data expert on what is best for your data needs.
What is very clear is that just as the owner of a car will typically depend on a trusted garage or mechanic to make sure it runs sweetly, making sure you get the most out of your data analytics solution can often benefit from the support of a specialist that knows your business and your solution. Where car maintenance solutions vary from fully inclusive lease, to ad-hoc trips to the local garage, or reference to the trusty workshop manual, support options for your data analytics solution cover just as wide a spectrum.
With a wide range of Managed Data Services for data analytics, data science, planning and forecasting, and DBA management, our team can aid you from operational activities through to strategic reviews with our tiered approach. We can support your organisation’s specific needs, just as a garage can repair your car’s specific parts.
Get your business to where it needs to be with regular data maintenance checks – and to remove the hassle of servicing your own data warehouse, rely on Simpson Associates Managed Data Services. If you’d like to talk about anything you’ve read here, feel free to get in touch with one of the Simpson Associates team today.
Blog Author
Andrew Hill, Managed Services and Support Manager, Simpson Associates
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