What business technology decisions do I need to make right now (and why)?

In my last blog, I used the luxury of hindsight to give my younger self some great advice (if I must say so myself). But if I was sitting looking at my reflection right now, having a serious – if slightly disconcerting – conversation with the man in the mirror, what advice would I hand out? And why?

What technology decisions should I be considering to achieve critical business objectives like cost optimisation, security, flexibility, scalability and more?

Well, they are all around the most precious business asset of all – data.

1. Future-proof your data security strategy

From an industry perspective, there’s a huge increase in and evolution of what are considered best practice data security standards. And it’s not just to do with the growth of cybercrime, but the need for businesses and organisations to modernise and  structure their data in ways that allows them to manage and report on it – so it drives more value.

As a reflection of this, one major Australian enterprise is currently looking at both its data management and governance and determining its (data) domains as part of its data strategy. This will allow them to logically segregate data by transaction type and the individual product/s they need to support that domain.

Note: If you haven’t come across the term ‘data domain’ before (aka subject area or data concept), it’s defined (in the context of data governance) as: “A logical grouping of items of interest to the organisation, or areas of interest within the organisation”.

This is a step forward from the traditional monolithic approach to managing data, where all data operations are carried out from and to a single, centralised data platform. For smaller businesses or organisations, adopting a monolithic data architecture from the outset has been the traditional go-to approach – for good reason. It’s comparatively easy to set up and is ideal for handling small-scale data analytics and storage without losing performance. However, as the volume of data and the demands on it grow, this way of storing and managing data becomes degraded, and your data management team can become a business bottleneck.

So, if your organisation plans to offer a range of customer products or services, my advice is to start now as you mean to go on rather than reengineering your data management and governance later. Your architecture framework should be created in a way that scales to accommodate other data products or domains that you bring on.

Start with a clear goal. You need to choose a platform that will accommodate large or incremental changes over at least the next decade, is easy to onboard other products and data domains into and has inbuilt security and governance.

Which brings us to the door of two ‘hot’ data framework options: data mesh and data fabric. Each takes a different approach to handling data, storage mechanism and data governance. Very quickly:

  • A data mesh creates multiple domain-specific systems. Each system is specialised according to its functions and uses – and so brings data closer to consumers.
  • By comparison, data fabric governs and manages multiple data sources from a single, virtual centralised system. It consists of a single source of truth containing high-speed clusters that grant your users access via network endpoints.

I suggest you start by checking out data fabric platforms. They’ll transform how you manage your data – at will and at your own pace – without stress. Of note, is that NetApp’s data fabric offering differentiates itself from others by being omnipresent (hybrid multicloud: on-premises, AWS, Azure, Google Cloud and software-defined). And it’s also multiprotocol.

And (although we’re sure you probably don’t need to be told), don’t forget to invest in training and adoption sessions so your people know how to use your platform and you get more benefits, more quickly.

2. Don’t hold on to technical debt

One of the most common mistakes I see is a reluctance to let go of old technologies, often due to a perception that the cost of replacement is too high.

A common description of a yacht is a hole in the ocean that you keep pouring money into. And likewise, that can apply to monolithic architecture. Internal political pressure can be a force to be reckoned with in cases where the investment is already significant, and the technology heavily entrenched. This, despite its apparent limitations.

Hanging on to old technology is a tactical, not a strategic move. The scary thing is seeing organisations spending millions upon millions of dollars trying to scale old platforms to handle the unprecedented volume of data created and kept today, let alone in two, five, or ten years. The irony is that the same budget could have paid for a new scalable platform, and the organisation could be reaping the rewards of seamless data analytics and reporting and higher productivity levels.

Often the hardest thing to do when dealing with technical debt is to build a case for a new platform. Sadly, a new platform often doesn’t become a priority until it also becomes a problem.

What’s also frightening is when the problem prompts the (knee-jerk) adoption of a new platform without knowing what good looks like. What tools are useful, and how the organisation should structure data in a meaningful way? I’ve seen organisations sign up for a $5 million a year subscription to a cloud data warehouse to hold all their data – and not know what to do with it.

My advice? Be brave and stick to your guns when asking the business to invest. But don’t start without a strategy that details the fundamental gaps you need to fill, your non-negotiables, a vision for how you will use your data, and the roadmap you plan to follow. And stick to it.

3. Take the value of your data seriously, everywhere

While my first two pieces of advice tackle major big-picture topics, this one may seem less so. But it can save you a world of grief.

Data is a business asset that’s almost impossible to put a price on. Until it’s lost, corrupted, stolen, ransomed, or sold. At that moment, its price is beyond gold. Your organisation can be crippled or even fail as a result. We don’t need to look far to see some significant examples of this.

It must be said, we are all in the same boat regarding compliance with data retention legislation. And for most of us, the importance of protecting old and new data isn’t a difficult concept. (Although deciding how and where to store it can be a challenge – and a whole new blog.)

However, there are multiple facets to consider with data security. There’s the infrastructure side of your data, involving firewalls and encryption. And then, there are your endpoint devices (laptops, smartphones, tablets, remote desktops, etc.), which consume data from multiple locations.

So, you’re in transit in an airport café in a high-risk, hackers-at-the-ready country. And, as you do, you’ve got your laptop out to keep working while you wait for your next flight. But before you join that airport or café wi-fi, your geospatial security policy settings should detect that you are in a high-risk situation and automatically apply other layers of protection to your endpoint. Shouldn’t it?

The mistake here is to assume that it’s enabled.

So, my advice – you need to take the security of your data and your entire environment extremely seriously. You need to be aware of what role you have to play in keeping it secure and ALWAYS be responsible and accountable, wherever, whenever.

The here and now

Every decision we make has an impact. And while we can only make the best possible decision based on the information at hand, it’s critical that we consider it from every angle. So, as times change, we’re not backed into a corner but have the capability and capacity to flex, adapt, secure, and grow.

Next time, I’m giving advice to my older self. And probably pulling myself up on a few mistakes I’ve made over the years as well.

If you need support in developing a technology roadmap, get in touch to discover how we can help.

In partnership with NetApp