There are plenty of good reasons why many retailers haven’t moved data processing to the cloud yet. Many have decades of legacy systems built up, including data processes that may have taken years to architect. It’s been challenging to connect on-premises systems and processes with new public cloud infrastructure.
The cloud is also a different operating environment for enterprises, with new pricing models, security controls and optimization tactics. Often, retailers have piloted the cloud, but found it challenging to put into production. This is changing, however, as enterprise services make the cloud much easier to use.
In my previous piece for Multichannel Merchant, I covered the importance of moving data processing to the cloud. Now, I’d like to offer a few key steps to get started with big data and the cloud:
Understand or benchmark your existing Time to Analytics: An emerging metric for data-driven companies, Time to Analytics (TTA) measures the time between a) when a company gets access to a dataset to b) when the right workers (often analysts) have access to that data so they can use it to add value. For companies with on-premises data infrastructure, this is often measured in months. Consider recent data projects and their approximate time to analytics – and set a goal to improve that.
Evaluate cloud services that accelerate deployments. For example, Big Data as a Service is a new cloud category, recognized in recent analyst reports by both Forrester and Gartner:
“Enter the concept of ‘big data as a service,’ where vendors are combining components of analytic platforms in the cloud with multiple processing engines, hybrid on-premises integration, and secure data movement. The use of such services can speed up the adoption of analytics in the cloud, address skills shortages within the enterprise, and make it easier to transition from, and integrate with, existing on-premises investments.” — Gartner, Inc. Cool Vendors in DBMS. April, 2016.
As you evaluate options, consider how services will work with existing systems, as well as specific security and governance requirements. Big data as a service can give retailers the security controls of private cloud, but with the agility and lower costs associated with public cloud.
Determine which data projects will make the biggest impact, culturally, operationally and strategically. Every organization is different. For some, the cloud may enable fast delivery of a critical new capability. For others, the cloud may streamline operations. Or, analytical access to a new dataset may unlock innovative ideas from workers. Consider: now that cloud data processing is easy, available and cost-effective, which projects will reduce unnecessary costs, inspire your workforce and delight customers?
At Cazena, we’ve seen the impact that transitioning to the cloud can have on retailers. One leading retailer turned to big data in the cloud to uncover competitive insights from massive amounts of publicly available data including social media (Twitter) feeds, building permit applications and competitive website scraping. The cloud enables retailers to use their existing analytical tools on external data like this but without the extensive time, effort and cost that would be required to bring all of the data into their data center. As a result they can uncover competitive moves earlier and react faster and more effectively.
The cloud can be a game-changer for your business as well. By adhering to these steps, you can ensure a successful cloud implementation and begin using the ideal platform for big data.
Prat Moghe is CEO of Cazena