Why you should be moving your data and analytics assets to the cloud and three things to do to get started.
If a significant number of your business applications are not currently in the cloud, I guarantee that you are struggling right now to equip your employees to work from home. You’ll be dealing with not only getting hardware to your employees, but you are likely struggling with training, security, and even just basic connectivity. This is reason enough to move to the cloud, but it not the only reason.
The most important reason to move to the cloud is because cloud infrastructure is specifically designed to scale up and down with great ease – meaning you can move quickly on anything that works and shut down initiatives that don’t work with minimal disruption. You can prototype with very powerful hardware and software for a fraction of the cost and time of buying and managing in-house systems. And if a prototype gets developed into a production-capable system, it is fast and easy to scale it up.
Simplified Infrastructure Management
The second most important reason to move to the cloud is simplified infrastructure management: hardware upgrades, OS patches, and all kinds of “low-level” stuff is handled by the cloud vendors. Security is better (if managed properly). Additional features and an entire ecosystem of software is available easily (though often at extra cost). In every way that matters, the cloud vendors provide a better and simpler IT (and data & analytics) base platform than almost any company can do on their own.
Don’t be misled, though, “simplified infrastructure management” doesn’t mean “no infrastructure management.” Though a cloud vendor does handle the “low-level stuff,” they do not administer and maintain your applications. The cloud platform, itself, needs to be managed or else you’ll leave security holes and potentially have enormous cost overruns when you should be seeing cost savings.
Some folks point to CAPEX/OPEX as the reason to move to the cloud, but more important than expensing or depreciating the costs of a system is the fact that cloud platforms enable much more greater cost transparency and more easily support departmental chargeback models. Flexible pricing models that are based upon systems’ usage usually means cost savings over the lifetime of an effort when considering all costs of an on-prem solution. The vendors all have costing calculators to help figure out the cost differences between on-prem and cloud.
Doing data and analytics in the cloud is routine now. In 2019, our customer-base crossed the 50% threshold for cloud-based architecture – it’s fully mainstream. It has been vetted. It is safe and effective. If you are not on the cloud now (with rare exceptions), you are living in the IT past and your competitors who have adopted cloud infrastructure will have an advantage over you.
I have three suggestions for getting started with data and analytics in the cloud:
1. Pick a Cloud or IaaS Provider
Pick AWS, Azure, or Google. All three are very capable and have a huge ecosystem of both software and expertise. I would not recommend other platforms right now due to the others’ overwhelming market share.
Two other specialty platforms are also worth mentioning 1) Salesforce: Though a platform to itself, it is not general-purpose enough for all of an organization’s analytics needs, even though Tableau is now owned by Salesforce. 2) SAP: SAP is a great choice if your organization is already “all-in” on SAP, but SAP is a much different, much more proprietary ecosystem than AWS or Azure.
You do not need to get all your software from Amazon, Microsoft, or Google. Every mainstream analytics platform/tool is capable in the cloud, though some are optimized for AWS, Azure, or GCP.
2. Get a Cloud Optimized Database
Today, there are very few reasons to not put your data on the cloud. Under almost all circumstances (though there are exceptions) any negatives of putting your data in the cloud are far outweighed by the benefits. Scaling storage and compute (even independently), literally by turning a dial is a revolutionary benefit. Look at Snowflake first. Then look at Amazon Redshift or Microsoft SQL Database or Synapse, depending on your cloud platform of choice. If your data volumes are not massive, Postgres or MySQL are good low-cost, but capable options.
3. Get Some Experts in Cloud Deployments and Cloud Analytics on Your Side
You can build or hire internally given enough ramp-up time or pick a competent analytics consultancy to get you started. The cloud platforms are very secure, very capable, and very cost effective, but it is also very easy to make a mistake in one of these areas if you do not have experience. If you have some of your business apps in the cloud, but not your core data and analytics apps, now is a great time move them to the cloud. If you have not yet adopted cloud technology, moving your data and analytics capabilities to the cloud is a great place to start.
What is going to be the “new normal” for knowledge workers when this pandemic is behind us? For one, a lot more working hours will be conducted from home. Two, they are going to be asked to move a lot more quickly – both your “developers” and your “analysts.” Cloud platforms will enable your developers to develop fast and your decision-makers to make decisions quickly from wherever they are.
Now is the time to get your analytics infrastructure in a good spot to support the changes in your business models that will be coming once society moves to the “recovery” phase of the pandemic. Moving to the cloud or optimizing your cloud analytics infrastructure should be high on your list of priorities. You can use our cloud migration checklist to prepare and guide your migration to the cloud.
To thrive with your data, your people, processes, and technology must all be data-focused. This may sound daunting, but we can help you get there. Sign up to meet with one of our analytics experts who will review your data struggles and help map out steps to achieve data-driven decision making.
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