Research has shown that the longer you use AWS, the greater the potential benefits. For instance, after three years using AWS, customers can expect to realise $3.50 in benefits for every $1 spent. This figure rises to $8.40 for every $1 after five years using AWS. What these cost savings tell us is that the longer your business and your teams are using AWS, the savvier they get at cost optimisation.
There are a host of strategic benefits to engaging in Cloud cost optimisation conversations. While the primary goal will be to eliminate unnecessary Cloud expenditure and optimise performance, there are strategic wins that can come out of the exercise too.
Lowering costs is one the major reason businesses migrate to the Cloud. While it’s true that Cloud can be cheaper than on-premises data centres, it's not always a given. Simply picking up your workloads and shifting them to AWS might generate initial cost savings. However without ongoing cost optimisation tweaks, the long-term Cloud vs On-Premises cost savings can end up much of a muchness. There's further long-term cost savings that Cloud can provide, but it requires further analysis and reporting.
The next piece of the data science puzzle is looking at taking those first steps. Continuing our data science series, let’s look at how you get started, why the CIO is best-placed to take ownership of data science and then we'll look at the 5 things you need to consider to make data science work.
Following the great turn-out in Auckland for the 2016 AWS Summit, let's take a quick recap of the big news, presentations and announcements and look at our presentation with Xero.
Collecting and analysing data isn't anything new so why do we suddenly have a whole new field and what is it all about anyway? We examine all things data and demystify Data Science once and for all.
There’s a tendency for CIOs to see everything as risk and central to their role is the need to mitigate risk. However, there is an exciting opportunity to step outside of this bubble. A chance to realise significant business value, with the CIO as the owner and champion of the initiative. What we're talking about here is implementing Data Science strategies.
The notion of Retail Agility is underpinned by the idea of four pillars, working in concert, that help the idea of agility take hold and flourish. We've previously examined how culture and the journey play their part. Now let's examine the final two pillars: technology and your partnerships.
The threats for businesses are coming from all angles, meaning that relying on the tried and tested is risky strategy. We know the answer is Retail Agility - let’s examine the importance of culture and the journey to achieving it.
If you think back to how shopping has changed in the last 5, 10 and 20 years you know that the speed of change is getting ever quicker. It's no longer just one change either such as the move from department stores to shopping malls. Instead, the changes are coming thick and fast and from all angles and many retailers are struggling to keep up. The businesses that thrive are blessed with retail agility.