What to expect from cloud data analytics in 2021
security, privacy, and data sovereignty. So much of the digital transformation that we’ll see in 2021 will happen out of necessity, but today’s cloud is what makes it possible. Google Cloud is a platform built ground-up based on these foundational requirements, so enterprises can make the transition to the cloud with the assurance that data is protected.
By 2021, we’ll see 80% or more of enterprises adopt a multicloud or hybrid IT strategy. Cloud customers want options for their workloads. Open infrastructure and open APIs are the way forward, and the open philosophy is one you should embrace. No business can afford to have its valuable data locked into a particular provider or service.
This emerging open standard means you’ll start to see multi-cloud and on-premises data sources coming together rapidly. With the right tools, organizations can use multiple cloud services together, letting them gain the specific benefits they need from each cloud as if it was all one infrastructure. The massive shift we’re seeing toward both openness and cloud also brings a shift toward stronger data assets and better data analytics. If you’ve been surprised over the past year about how many data sources exist for your company, or how much of it is gathered, you’re not alone. An open infrastructure will let you choose the cloud path that works best for your business.
Data solutions like Looker and BigQuery Omni are specifically designed to work in an open API environment on our open platform to stay ahead of continually changing data sources.
Data science, with all of the expertise and specialized tools that have typically been involved, can no longer be the purview of just the privileged few. Teams throughout an organization need to have access to the power of data science, with capabilities like ML modeling and AI, without having to learn an entirely new discipline. For many of these team members, it’ll bring new life into their jobs and the decisions they need to make. If they haven’t been consuming data, they’ll start.
With this capacity to give the whole team the power of analytics, businesses will be able to gather, analyze, and act on data far quicker than those who are still using the traditional detached data science model. This improves productivity and informed decision making by giving employees the tools to gather, sort, and share data on demand. It also frees up teams with data science experience that would normally be assembling, analyzing, and creating presentations to concentrate on tasks that are more suited to their abilities and training.
With Google Cloud’s infrastructure and our data and AI/ML solutions, it’s easy to move data to the cloud easily and start analyzing it. Tools like Connected Sheets, Data QnA, and Looker make data analytics something that all employees can do, regardless of whether they are certified data analysts or scientists.
We’re quickly getting to the point where data residing in the cloud outpaces data residing in data centers. That’s happening as worldwide data is expected to grow 61% by 2025, to 175 zettabytes. That’s a lot of data, which offers a trove of opportunity for businesses to explore. The challenge is capturing data usefulness in the moment. Following past stored data can be informative, but more and more use cases require immediate information, especially when it comes to reacting to unexpected events. For example, identifying and stopping a network security breach in the moment, with real-time data and a real-time reaction, has enormous consequences for a business. That one moment can save untold hours and costs spent on mitigation.
This is the same method that we use to help our customers overcome DDOS attacks, and if 2020 has taught us anything, it’s that businesses will need this ability to instantly respond to unexpected problems more than ever moving forward.
