Modernizing our data platform
Accenture is unlocking the promise of advanced analytics with Google Cloud
Running a business today is all about managing dynamic data. Accenture wanted to make better use of platform services that could develop, run and manage applications in the cloud and make data more visible and secure. Data is what empowers our people and drives innovation for our evolving business.
After just three years of use, the Accenture global IT organization recognized its analytics platform was fast becoming obsolete. The platform was managed by Accenture but hosted in cloud. Yet, increasingly, it was becoming difficult to upgrade and grow, creating greater overheads for managing storage, and presenting a high learning curve for developers. We were struggling to stay technologically current. Our people were spending valuable time on operations, troubleshooting, and maintenance instead of generating insights to drive our business.
In May 2019, the Accenture global IT Applied Intelligence team made the strategic decision to move to Google Cloud’s Platform-as-a-Service (PaaS) model to support our IT strategy to be platform powered, cloud first and intelligence driven. The program team needed to determine how to create a secure, cost-effective and scalable architecture in the cloud while also driving the migration of data and applications from the legacy system. Using Google Cloud, we could modernize data capabilities to unlock the promise of advanced analytics, increase cost savings via a pay-as-you-go model and drive cutting-edge performance that enables a digital Accenture.
"We decided to migrate our data platform to Google Cloud for sustainability and performance reasons. But the platform does so much more—it gives us enhancements and capabilities that are delivering new business value."
As a result of COVID-19, cloud has turned from an aspiration into an urgent mandate. Cloud is the foundation that helps organizations become digital businesses, be more resilient and develop new experiences and products. With cloud, companies have the speed and cost reduction that is fundamental to growth and success. Recognizing the need for organizations to shape, move and operate their businesses in the cloud, Accenture announced the formation of Accenture Cloud First—a US$3 billion investment in a new multi-service group that helps clients across all industries migrate rapidly to the cloud.
Without doubt, technology—and how the world uses it—has changed dramatically in the last five years. So, too, has the demand for data insights. Accenture began the journey to improve its analytics platform by assessing if cloud-hosted PaaS offerings could address the cost, performance, and scalability challenges of the legacy data lake. Today, 95 percent of the Accenture IT infrastructure operates in the public cloud to take advantage of its scale efficiencies. Yet, to achieve the latest scion of cloud services, Accenture required a partner to help design a different set of principles. The architecture needed to be:
The global IT team selected Google Cloud as the platform for its new analytics data lake, taking advantage of its established solutions and technologies, and its flexible cloud platform offerings that power applied intelligence. Google Cloud enables options for deploying the right server sizing and configuration to meet the analytics’ job requirements. The global IT team, partnering with Google, was able to design a modernized platform with the ability to deploy services faster, realizing improved performance and stability for the applications powered by the data lake.
As part of the transformation journey, the platform architecture and processes had to be created to align with our security needs to make sure that the data coming in and the data going out was secured at the enterprise level. With the move to Google Cloud, Accenture has created a foundation to store and analyze its enterprise data in the data lake—with room to grow.
To take advantage of the architecture, we needed to address how to manage access within Google Cloud—who could access the data, and who and how we deploy analytics into production. A new data security model, along with project governance was created while adhering to our data compliance and audit requirements. In line with industry standards, Accenture adopted a Site Reliability Engineering (SRE) model where teams can build, operate, and run their own environments and services. Cloud native services, driven via code, meant that the cloud could optimize efficiency.
Moving to this model means that teams could use repeatable infrastructure deployments, avoid manual configuration and introduce greater consistency. Compliance and security checks before deployment meant teams were able to work with a unified set of practices and tools to deliver applications and their supporting infrastructure rapidly, reliably, at scale and while minimizing vulnerabilities to the systems.
Accenture is now entering the transformation stage of our new analytics platform. This phase advances our cloud capabilities with self-service analytics, real-time integration across various platforms, such as ServiceNow and Salesforce, and takes us into a PaaS model with a cloud native infrastructure.
As we shift to a modern data architecture at Accenture, we strive to support cloud native technologies, such as serverless and container services, for our own agile scale and to help client implementations.
In addition to setting up the new architecture, Accenture needed to drive and execute a migration strategy to move hundreds of terabytes of data from the existing infrastructure to Google Cloud. Sitting on top of the existing analytics platform were more than 50 applications driving insights to users all over the globe. The team needed to manage a seamless transition with minimal impact and no downtime to the 40,000 global consumers of those analytics applications.
Accenture wanted to quickly take advantage of cloud native components and reduce the administrative complexity, so the migration team reshaped the current applications to use on-demand infrastructure concepts and on-demand resources optimized for cloud computing. In a phased, targeted approach, applications were evaluated to reimplement the data ingestion and store strategy. Processing code remained the same, but data warehouse interfaces were moved fully to Google BigQuery and Google Cloud Composer to run workflows.
When Accenture made the decision to move to Google Cloud, the leadership team recognized this would represent a major change touching all our processes and the skills of our team. Cloud transformation requires people to work with technology differently.
The team chose to tackle head on the culture, talent, and change barriers to successful cloud adoption. The focus was on preparing the teams to transition to the cloud, assessing the current and desired cloud skills, developing tailored learning paths and creating and enabling a continuous training plan. Transformation leaders were selected across roles, locations, and functions to provide 360 degree feedback loops and accelerate the time to development.
The global IT team knew it wanted to live the principles of a cloud-first organization and recognized that we needed to shift our talent focus to crafting analytics solutions that bridge Google Cloud capabilities with our internal systems.
Google Cloud Platform with its open architecture approach is giving our teams greater freedom to:
The Accenture global IT organization has created the foundation that will completely transform our analytics platform—reducing overheads, decreasing costs in server storage, and providing our people with cutting-edge, advanced analytics.
Going forward, Accenture intends to continue to transform and strengthen the big data insight capabilities we offer, explore the full value of the cloud ecosystem, and open the door to more innovative solutions.