The future of data and analytics is in the cloud, according to Gartner Research. It predicts that by 2022, public cloud services will be essential for 90 per cent of data and analytics innovation.
Shifting analytics to the cloud can open the door for powerful capabilities to solve problems and to act quickly to meet market demands. The pandemic has turned that need into an urgent imperative. “In the last six months, companies have had to pivot to provide more holistic online customer experiences,” said Diane Hatcher, Senior Direction, Solution Engineering with Core Compete, a SAS Platinum Partner. “Being able to scale and to make automated decisions is extremely important.”
Not all Canadian organizations are on board yet, with estimates suggesting that about 20 per cent of workloads have been moved to the cloud. At the same time, the CanadianCIO Census showed that 78 per cent of IT leaders have accelerated their transformation plans, or certain aspects of them, because of the pandemic. “We’re seeing the timelines on cloud roadmaps shrink this year,” said Tina Schweihofer, Director, Customer Advisory Team for SAS Canada. “Organizations are pivoting from plans for a cloud-first approach to a cloud-now mentality.”
Agility and scale are the top drivers
A global SAS survey of over 1000 organizations reveals that agility is the primary driver for moving to the cloud. “Moving analytics to the cloud removes an obstacle that is slowing down progress towards true digital transformation–the inability to deploy analytics quickly at scale,” said Schweihofer.
Legacy systems are designed for stability, not innovation. Traditionally, organizations have sized their on-premises infrastructure to accommodate peak analytic workloads. It takes significant time and effort to scale up or down. “The reality is that computing demands are unpredictable,” Schweihofer said. “They change with the complexity of the data and swings in business needs.” With analytics in the cloud, organizations have ready access to elastic computing and storage resources, allowing them innovate much faster.”
Organizations also struggle to get the results they need from their on-premises infrastructure because of limitations on data and computing power. Machine learning algorithms are data-hungry, requiring large volumes of data from multiple sources, said Schweihofer. Artificial intelligence also requires massive compute power. “Investing in hardware to accommodate these types of workloads has been very expensive,” she said. The cloud model solves that problem. If the demand is a huge analytic workload that runs infrequently, but regularly, having scalable computing resources could help manage costs better, said Schweihofer.
Cloud analytics is a game changer for organizations to be able to adapt to the kind of unprecedented market shift caused by COVID-19, said Hatcher. Core Complete recently worked with a large global bank to develop an online credit processing application. The SAS app decides whether to grant a loan after analyzing the loan request along with other data sources such as credit history, said Hatcher. It even sets the interest rate and credit limit. “The cloud allows the analytics to scale to automatically handle thousands of transactions in seconds,” said Hatcher.
View the Related Infographic – Are you ready for analytics in the cloud?
The power to the people
The cloud is instrumental in “democratizing” analytics, said Schweihofer. It makes it easier to put data analytics into the hands of those who need it to make informed business decisions. As well, it helps data science teams collaborate, no matter where they are. According to Gartner, organizations that offer users access to a curated catalog of internal and external data will realize twice the business value from analytics investments than those that do not. “It’s the people that drive the value,” said Hatcher. “Analytics is a tool and it’s the people who wield the tool that drive the business decisions.”
For example, in Norway, beekeepers are using visual analytics and machine learning to help protect bees. Researchers around the world are trying to figure out why bee populations are rapidly declining, a serious problem given that bees pollinate most of the plants we use for food. In Canada, one in every two colonies of Canadian bees, which might contain up to 80,000 bees, dies for no apparent reason. Now, SAS analytics on the Microsoft Azure cloud is providing clues on what can be done about it.
To survive, bees need access to a diverse set of plants that bloom all year round. Farming that focuses on limited types of crops may be part of the problem. Analysis of data from cameras and sensors revealed patterns in what’s known as the “waggle dance” of bees when they return to the hive. It turns out that the bees are telling their hive mates where to find the best food, something the beekeepers could never have discovered through observation. This information is shared via an interactive map with the beekeepers who can move the hives closer the food source at different times of the year. By getting better access to food, the bees live longer.
Vendors are increasingly offering this kind of “people literate analytics” to help solve complex problems, whether they are in the environment, business or elsewhere. This year, SAS and Microsoft Azure announced a strategic partnership to enable organizations to easily run their SAS analytics in the cloud. The solution integrates SAS analytics across Microsoft cloud solutions, such as Microsoft 365 or Dynamics 365, to put the make insights available to more people throughout an organization.
How to get there from here
Everyone’s journey to the cloud will be different, said Tina Schweihofer. “My most important piece of advice is that you should start with an honest assessment of where you are today and where you want to go.” Hatcher agreed. “There’s no reason to move to the cloud just because,” she said. “You have to understand why.”
Detailed planning is also a key to success. “It’s important to be thoughtful about phasing the movement,” Hatcher said. “Analytics is part of a larger process to deliver business outcomes. Moving analytics to the cloud can help you get more mileage in that context. It’s not about why you should move analytics to the cloud, but why you should move decision-making to the cloud. That’s where the value is.”
Learn more about the steps for success in “What will it take to make analytics cloud-ready?”