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Read Part 1: Building the Foundation of How to Transform your Operation into a Smart Factory series.
Part 2: Modernising the data architecture
It was British mathematician Clive Humby who coined Industry 4.0 catchphrase “Data is the new oil” back in 2006. To paraphrase Humby, while a modern factory runs on oil, a smart factory runs on data. Indeed, the effective collection, analysis and application of data is at the heart of any smart factory’s strategy and operations. And if the data is the heart of the smart factory, then the data architecture is its lungs.
“Data architecture is a framework for how IT infrastructure supports your data strategy,” says Angeline Maronese, Managing Director ANZ at Rackspace Technology. “Its goal is to show your company’s infrastructure how data is acquired, transported, stored, queried, and secure and is the foundation of any data strategy.”
In addition to having an effective data architecture in place, smart factories are characterised by digital technology, real-time data-driven systems, automation and sometimes, artificial intelligence.
Here’s how to begin modernising the data architecture for your smart factory transformation:
Chart your current architecture
To improve the way your company is gathering, storing, querying and securing data, you need to understand how you’re managing (or not managing) it right now. It helps to quite literally map or chart all aspects of your data picture, from where it comes from and what it looks like, to how it’s moved around, stored and secured, to what you do with it.
Once you’re clear on this, you can start to think about how to improve your data architecture. Some questions you might want to consider are: Will your storage system be able to handle more data in the years to come? Is your data secure? Is it a data lake, or a data swamp? How do you analyse it? Do you have the expertise you need to make the most of it?
Define and build your future data fabric
You can then chart what your data architecture needs to look like to serve your business, going forward. This is a hugely important stage, as an effectively architected system helps in the definition, design and build of your data fabric – the elements that streamline and standardise data management practices and practicalities across on premises, cloud, and edge devices.
“At Rackspace, we approach data architecture from a first principles perspective, meaning it must be built right, right from the start,” says Maronese. “A well architected system leads to all kinds of benefits. It will be efficient and scalable, which lowers operating costs. It will flexibly meet the evolving needs of the business, will be more resilient, and can be grown quickly in response to business needs.”
Once you’ve charted what your optimum future data architecture looks like, you can begin to build it. This phase includes pipelines and integration, data lakes and warehouses, and the all-important analytics platform.
Focus on generating insights and actions
“While data itself always carries a degree of latent value, its value can never be fully realised as long as it remains raw information,” says Maronese.
“Converting the data to insights through analysis goes part of the way to unlocking its potential, and many organisations are good at doing this. But to truly monetise your data, those insights must be acted upon.”
In essence, your data architecture should be enabling you to identify and realise beneficial actions and outcomes – ones that will help your business create value, evolve and grow. These might be improved customer insights or operational changes that will drive efficiency and business growth.
Start your digital transformation to power resilient smart factories. Download the e-book at Rackspace Technology.
