Are data migration challenges hampering ‘Possibility’?

Are data migration challenges hampering ‘Possibility’?

Data is a funny old thing. Sure, it’s valuable, but not for the first time, it is a good analogy to compare it with oil. Like crude, data in its plain state is heavy, difficult to move around and hard to use. And this reality can mean that while you have lots of it, your data isn’t really of much use. In other words, the ‘Possibility’ part of ‘Datability’ is stuck in the mud. The sheer overhead of moving around and organising data makes for so much inertia that the great ideas which rest on working with data, simply can’t see the light of day.

Datability is the term we give to the ability to extract powerful insights from data. There are four pillars to Datability – Possibility, Buildability, Scalability and Profitability. Possibility refers to the potential that data holds: like crude oil, data can be used for many things and can, when properly harnessed, power modern business.

But also, like crude oil, if data remains buried, potential is all it has. And that’s remained a fact of life for many businesses. There are massive stores of data but because they are so siloed and inaccessible it’s like being a prospector who has identified a substantial deposit, but doesn’t have a rig, a drill or a pumpjack.

What this data has in common is a) that is has latent Possibility and b) that whether it is the latest transactional data or stuff that’s been around for years, it is difficult to pull together to perform comprehensive analysis on.

Now, without implying an oversimplification, things are changing. And like a lot of things in the modern era, the change is coming because of the availability of cloud services which help overcome the limitations of on-premises infrastructure, software and services.

It starts with shuffling data into the cloud. With a migration off on-premises infrastructure and into a cloud Platform like Microsoft’s Azure, the scene is set for more easily doing something with that data. Think of this as the sinking of a well to tap into the oil deposit.

But once the data is in the cloud, there’s still a problem. With multiple data types and classifications, it still isn’t ready for analysis (which is really where Possibility starts taking form).

Here’s where WhereScape RED is indispensable. As a comprehensive data warehouse automation solution, RED does the work of multiple tools and removes around 80% or more of the need for manual coding. It even automates one of the biggest bugbears for programmers, documentation, too.

Combined with data in the cloud. RED means you can start doing meaningful things with data faster. The cloud delivers flexibility and low cost, along with scalability, providing the headroom to experiment and explore Possibility. RED accelerates the process by streamlining build time, increasing agility and allowing for people to think and explore Possibility, rather than occupy their time with tasks that add little value.

So, WhereScape RED is really like the crude oil refining process. From the pumpjack, drawing the crude from the ground right through to the refining process where different grades of fuel, (read data) can power the world. WhereScape RED manages the whole process from raw material to finished data product.

With processed data products, Possibility is realised through advanced analytics, AI, insights and potential new business models, new markets or new products. With analytics and AI built on the Azure platform, it means the barriers to entry are all but gone. It means working and experimenting with data is so ‘low cost’ that any employee is empowered to explore the Possibility of their data to the great benefit of the business.

In a nutshell with the right tools and platforms in the cloud, you can turn Possibility into jet fuel for the business without breaking too much of a sweat.

If you’d like to find out more about how we can help companies explore the Possibilities in their data, please visit www.azurenow.co.nz or feel free to message me on LinkedIn.

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