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Four best practices to maximise your cloud analytics

Four best practices to maximise your cloud analytics

The way businesses work with data is constantly changing, and accelerating. As a result, users need Business Intelligence solutions that can keep up with the pace of business decisions and help organisations to become truly data-driven.

One way to ensure that a business has access to the right insights at the right time is to adopt cloud analytics. The benefits of this type of BI modernisation can be far reaching for an organisation.  Analytics in the cloud helps businesses reduce costs, as well as get enterprise-wide insights faster.

There are a few key points to keep in mind when it comes to adopting and utilising cloud analytics that can help to maximise the benefits for your business.

1. Not all analytics solutions are created equal

A lot of data analytics software can be very complicated to install and deploy, and can often require lots of hours from IT and data teams to maintain and optimise.

But with cloud analytics solutions, users get the benefit of:

  • Quick setup speeds – it’s possible to get the whole team up and running in minutes, which can “reduc[e] deployment time by up to 99%” Qlik shares.
  • Saving on their analytics infrastructure costs – with cloud analytics your business only needs connectivity, and you’re ready to deploy and scale your cloud solution immediately. Gartner asserts that the savings could “[a]dd up to tens of thousands in infrastructure.”
  • Easy onboarding and adoption – speed up the time to value with smooth onboarding.

2. Choose the best cloud computing model for your business

Each cloud computing type (Private, Public, and Hybrid) serves a different use case or solves different problems. Each option has its own pros and cons:

Public cloud

Public clouds – like AWS or Google Cloud – are cloud environments that use IT infrastructure that’s generally not owned by the end user. A key benefit of this model is the ability to rapidly scale a service, as the major service providers have heaps of computing power! Plus it’s easy to manage, and implementation costs are the lowest across the three cloud computing models.

Private cloud

This cloud computing model is similar to the public cloud; however, users don’t have to hand over control of their data and services. This means that companies using the private cloud have added control over their data and infrastructure, plus additional security, and often increased network performance too.

Hybrid cloud

A hybrid model is a mix of public and private cloud usage. The benefits of this approach lie in aiding disaster recovery and minimising hardware costs if the business expands their data centre.  Another benefit is that you can still utilise your existing infrastructure, such as an on-premise server, while also using the public cloud for certain operations or tasks.

3. Create a data-sharing culture

It goes without saying that data is critical for helping employees to make decisions. But when an employee goes one step further and shares their data insights with their team or department, the value of that data multiplies.

And on a company-wide scale, the benefits of this approach are even more exponentially increased. Per MIT Sloan, “Companies that succeed at data sharing get more value from analytics initiatives – and chief data officers who facilitate sharing play a more strategic business role.”

When data is no longer locked away in departmental silos, everyone in the business can benefit from, and build on insights, instantly supporting a more data-driven business.

Taken a step further, organisations that share data with external stakeholders, such as other companies in their supply chain, can forge insights that help them personalise their products and services and engage their customers on a whole new, more personalised level.

4. Improving data literacy and technological fluency

Not all employees are digital natives. So to ensure everyone is confident using business tools like cloud analytics, it’s important to also focus on the people side of technology.

McKinsey recently shared that “[a]t traditional companies, the leaders and the organization as a whole lag behind digital natives in their knowledge and comfort with technology and advanced analytics.” Oftentimes the reason behind this is that they’re used to more traditional processes, and possibly even non-digital or stand-alone business resources that keep data stuck in siloes.

For companies to successfully traverse this skills gap, they should look for resources that provide the knowledge and skills needed to help everyone become more data fluent. Deloitte shares a few helpful suggestions in this regard, including:

  • Provide learning programmes that are self-directed, digital, and dynamic
  • Tie these learning initiatives to personal and professional development goals
  • Build data literacy and other technological skills development into the company’s values
  • Recruit candidates that love the challenge and opportunities that stem from modern technology and business tools

With the right approach, it’s possible to modernise your BI  and adopt solutions that are intuitive, that easily integrate with your other business tools, and that help everyone get the most from data instantly.

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