As a leading French agricultural cooperative, Groupe Dauphinoise places collaboration at the heart of its philosophy. Working with farmers in the Rhone-Alpes region, Groupe Dauphinoise takes on a diverse range of activities from agricultural production to research and development to running retail outlets.

As its operations expanded and strained its existing infrastructure, Groupe Dauphinoise saw the opportunity to upgrade its technology solutions and adopted G Suite, Chrome devices and ultimately Google Cloud Platform (GCP).

“We transitioned to G Suite to improve our staff’s collaboration. We quickly realized that as the company grew, we needed a new infrastructure. Based on our satisfaction with G Suite, we chose GCP. With Google, ‘any device, anytime, anywhere’ is not just a dream,” says Sylvain Claudel, Head of IT at Groupe Dauphinoise.

“We transitioned to G Suite to improve our staff’s collaboration. We quickly realized that as the company grew, we needed a new infrastructure. Based on our satisfaction with G Suite, we chose GCP. With Google, ‘any device, anytime, anywhere’ is not just a dream.”

—Sylvain Claudel, Head of IT, Groupe Dauphinoise

Flexible workforce, stable infrastructure

Many of Groupe Dauphinoise’s 1,500 employees spend their days out of the office. Five years ago, with the help of Google partner GoWizYou, the company transitioned to G Suite to improve the flexibility and collaboration of its staff.

As Groupe Dauphinoise began to expand and collect more data, the company reached the limits of its on-premise infrastructure. Adding new storage was not a simple matter. Acquiring, configuring and synchronising new servers costs Groupe Dauphinoise time as well as money. In addition, with all its servers stored in a single room, security was a concern. Groupe Dauphinoise needed a new infrastructure.

Google Cloud Platform was the only solution in mind after Groupe Dauphinoise’s experience with G Suite and Chromebooks. Disruption was kept to a minimum thanks to Google’s licensing agreements with Microsoft products, allowing the company to migrate without affecting its operations.

After migrating its infrastructure to Compute Engine, Groupe Dauphinoise can let Google look after the security and maintenance. Cloud IAM makes it easy for Groupe Dauphinoise to hand out permissions to sensitive resources across a number of sites with maximum security and minimum fuss. The company placed its archives in Cloud Storage, while Cloud SQL allows it to continue to make use of its MySQL databases without disrupting the day to day business. Meanwhile, BigQuery provides Groupe Dauphinoise with the raw power to analyse large datasets quickly.

“Our company is growing and we have more and more data to collect and analyze like sales data, weather patterns or production numbers. With GCP, we have more than a single on-premise data store, so our disaster recovery plan is much more flexible. Compute Engine allows us to add more storage quickly and easily, without having to spend days synchronizing data and installing new servers. We have improved security and maintained the stability of our infrastructure while keeping costs down,” says Sylvain.

Safeguarding the present, looking to the future

With Google Cloud Platform, Groupe Dauphinoise has expanded and secured its infrastructure without sinking costs into on-premise servers or DevOps staff. Its investment in Chrome devices and adoption of G Suite mean that its mobile workforce can fully reap the benefits of a cloud-based infrastructure while dramatically cutting the cost of hardware. Meanwhile, working with a 200 million line table of sales data in Google BigQuery, the cooperative found that queries ran ten times faster than with its previous database provider. Groupe Dauphinoise is experimenting with Google BigQuery to expand its BI capabilities. Products like Google BigQuery help Groupe Dauphinoise grow its business, safe in the knowledge that its infrastructure is stable and secure.

“The amount of data we collect is growing very quickly. We need to break our rules and evolve from the mindset that we had with on-premise infrastructure and our old databases. We can now look at collecting more customer fidelity data, or big data for our farmers. With our data and infrastructure in Google’s care, we can concentrate on growing our customer base instead of our IT department!” says Sylvain.

When ATB Financial decided to migrate its vast SAP landscape to the cloud, the primary goal was to focus on things that matter to customers as opposed to IT infrastructure. Based in Alberta, Canada, ATB Financial serves over 800,000 customers through hundreds of branches as well as digital banking options. To keep pace with competition from large banks and FinTech startups and to meet the increasing 24/7 demands of customers, digital transformation was a must. To support this new mandate, in 2019, ATB migrated its extensive SAP backbone to Google Cloud. In addition to SAP S/4 HANA, ATB runs SAP financial services, core banking, payment engine, CRM and business warehouse on Google Cloud. 

In parallel, changes were needed to ATB’s legacy data platform. The platform had stability and reliability issues and also suffered from a lack of historical data governance. Analytics processes were ad hoc and manual. The legacy data environment was also not set up to tackle future business requirements that come with a high dependency on real-time data analysis and insights.

After evaluating several potential solutions, ATB chose BigQuery as a serverless data warehouse and data lake for its next-generation, cloud-native architecture. “BigQuery is a core component of what we call our data exposure enablement platform, or DEEP,” explains Dan Semmens, Head of Data and AI at ATB Financial. According to Semmens, DEEP consists of four pillars, all of which depend on Google Cloud and BigQuery to be successful:

1. Real-time data acquisition: ATB uses BigQuery throughout its data pipeline, starting with sourcing, processing, and preparation, moving along to storage and organization, then discovery and access, and finally consumption and servicing. So far, ATB has ingested and classified 80% of its core SAP banking data as well as data from a number of its third-party partners, such as its treasury and cash management platform provider, its credit card provider, and its call center software. 
2. Data enrichment: Before migrating to Google Cloud, ATB managed a number of disconnected technologies that made data consolidation difficult. The legacy environment could handle only structured data, whereas Google Cloud and BigQuery lets the bank incorporate unstructured data sets, including sensor data, social network activity, voice, text, and images. ATB’s data enrichment program has enabled more than 160 of the bank’s top-priority insights running on BigQuery, including credit health decision models, financial reporting, and forecasting, as well as operational reporting for departments across the organization. Jobs such as marketing campaigns and month-end processes that used to take five to eight hours now run in seconds, saving over CA$2.24 million in productivity. 
3. Self-service analytics: Data for self-service reporting, dashboarding, and visualization is now available for ATB’s 400+ business users and data analysts. Previously, bringing data and analytics to the business users who needed it while ensuring security was burdensome for IT, fraught with recurrent data preparation and other highly manual elements. Now, ATB automates much of its data protection and governance controls through the entire data lifecycle management process. Data access is not only open to more team members but it is faster and easier to acquire without compromising security. And it’s not just raw data that users can access. ATB uses BigQuery to define its enterprise data models and create what it calls its data service layer to make it easier for team members to visualize their data.
4. AI-assisted analytics and automation: Through Google Cloud and BigQuery, ATB has been able to publish data and ML models that provide alerts and notifications via APIs to customer service agents. These real-time recommendations allow customer service agents to provide more tailored service with contextualized advice and suggested new services. So far, the company has deployed more than 40 ML models to generate over 20,000 AI-assisted conversations per month. Thanks to improved customer advocacy and less churn, the bank has realized more than CA$4 million in operating revenue. During the ongoing COVID crisis, the system was also able to predict when business and personal banking customers were experiencing financial distress so that a relationship manager could proactively reach out to offer support, such as payment deferral or loan restructuring. The AI tools provided by BigQuery are also helping ATB detect fraud that previously evaded rules-based fraud detection by using broader sets of timely and accurate data. 

Thanks to the speed and ease of moving data from SAP to BigQuery, ATB is using artificial intelligence (AI) and machine learning (ML) to do things it previously hadn’t thought possible, including sophisticated fraud prevention models, product recommendations, and enriched CRM data that improves the customer experience. 

Using the power of Google Cloud and BigQuery, ATB Financial has been able to draw more value from its SAP data while lowering cost and improving security and reliability. Speed to provide data sets and insights to internal team members has improved 30%. The bank also has seen a 15x reduction in performance incidents while improving data governance and security. Dan Semmens projects that the digital transformation strategy built on Google Cloud and BigQuery has both saved millions compared to its on-premises environment and has also realized millions in new business opportunities. 

Semmens is looking toward the future that includes initiatives like Open Banking and greater ability to provide real time personalized advice for customers to drive revenue growth. “We see our data platform as foundational to ATB’s 10-year strategy,” he says. “The work we’ve undertaken over the past 18 months has enabled critical functionality for that future.” 

Learn more about how ATB Financial is leveraging BigQuery to gain more from SAP data. Visit us here to explore how Google Cloud, BigQuery, and other tools can unlock the full value of your SAP enterprise data.

In 2013, long before the world was discussing clean energy and sustainable practices, two IIT Madras graduates — Swapnil Jain and Tarun Mehta — had an idea to develop India’s first-ever electrical scooter.

This was at a time when auto manufacturers were still focusing on fossil-fuel-driven vehicles and ‘eco-friendly’ mobility solutions were more a trendy alternative catering to a niche market.

The duo founded Ather Energy in 2013 and launched their first fully-electric scooter, the Ather S340, in Bengaluru in 2016. Since then, the company has released several new models into the market and is planning to expand to eight more cities by the end of the year.

To support the smooth running of their vehicles, lower costs, improve time to market, and create great customer experience, Ather turned to Google Cloud.

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We’ve made several updates to Google Cloud VMware Engine in recent weeks—today’s post provides a recap of our latest milestones. Google Cloud VMware Engine delivers an enterprise-grade VMware stack running natively in Google Cloud. This cloud service is one of the fastest paths to the cloud for VMware workloads without making changes to existing applications or operating models across a variety of use-cases. These include rapid data center exit, application lift and shift, disaster recovery, virtual desktop infrastructure, or modernization at your own pace.

In fact, Mitel, a global provider of unified communications-as-a-service to 70 million business users across 100 countries, migrated 1,000 VMware instances to Google Cloud VMware Engine in less than 90 days and improved its monthly operational output four times. 

In our last update, we focused on several innovative capabilities around networking, reach, and scale. Let us take a look at the highlights we released since our last installment.

Fast provisioning of a dedicated, intrinsically secure VMware private cloud

With Google Cloud VMware Engine, you can spin up a VMware private cloud in about 30 minutes. You can also scale your VMware-based infrastructure on-demand with dedicated hosts located in secure Google data centers. Let us look at what’s new:

Autoscale: The ability to elastically and programmatically manage infrastructure resources to align with business needs or what is called “right-sizing” is a core capability of an IaaS platform. With autoscale, Google Cloud VMware Engine users can leverage policy-driven automation to scale the nodes needed to meet the compute demands of the VMware infrastructure. 

Autoscale:

• Addresses seasonal spikes in demand, gradual increases of utilization, or new projects being onboarded or expanded due to disaster recovery events. 
• Analyzes the CPU, memory, and storage utilization to give you the controls to scale Google Cloud VMware Engine nodes up or down. 
• Ensures that storage consumption does not exceed the recommended limits for maintaining the Google Cloud VMware Engine service-level agreement. 
• Reduces overhead on IT teams by automating capacity monitoring and enabling sufficient availability of resources based on thresholds. Note that safeguards for maintaining minimum capacity and maximum capacity can be configured to ensure there are boundaries to the automation.

Learn how to set up Autoscale.

Mumbai region availability 

Google Cloud VMware Engine is now available in the Mumbai region. This brings the availability of the service to 12 regions globally, enabling our multi-national and regional customers to leverage a VMware-compatible infrastructure-as-a-service platform on Google Cloud. For more details, please read the press release.

Enterprise-grade infrastructure

With 99.99% availability for a cluster in a single zone, fully dedicated 100 Gbps east-west networking with no oversubscription, and all nonvolatile memory express storage, Google Cloud VMware Engine provides the highest performance required for the most demanding workloads. Let us look at what’s new:

Preview – Google Cloud KMS integration: You already have the ability to bring your own keys to encrypt your vSAN datastores. With this new capability, organizations that want to eliminate the overhead of managing external key providers can leverage a Google managed key provider, using Cloud KMS. This brings increased flexibility in securing workloads and data by enabling vSAN encryption by default for newly instantiated VMware Private Clouds. This feature is currently in Preview. 

HIPAA compliance: Since April, Google Cloud VMware Engine is Health Insurance Portability and Accountability Act (HIPAA) compliant. This opens the service up to healthcare organizations, that can now migrate and run their HIPAA-compliant VMware workloads in a fully compatible VMware Cloud Verified stack running natively in Google Cloud with Google Cloud VMware Engine, without changes or re-architecture to tools, processes, or applications. Read more in this blog.

NSX-T support for Active Directory: With NSX-T support for Active Directory, you can now leverage your on-premises Active Directory as one of the lightweight directory access protocol identity sources for user authentication into NSX-T manager. This extends the theme of being able to leverage your on-premises tools with Google Cloud VMware Engine. For more information, read the documentation on how to set up identity sources.

vSAN TRIM/UNMAP support: For space-efficiency, vSAN allows creating thin-provisioned disks that grow gradually as they are filled with data. However, files that are deleted within the guest operating system (OS) do not result in vSAN freeing up space allocated. To increase space efficiency, guest OS file systems have the ability to reclaim capacity that is no longer used, using TRIM/UNMAP commands. vSAN is fully aware of these commands that are sent from the guest OS and enables reclamation of previously allocated storage as free space. We have enabled TRIM/UNMAP for vSan by default in Google Cloud VMware Engine.

Simplicity in experience and operations

With Google Cloud VMware Engine, you only need to worry about your workloads—not patching, upgrading, and updating the solution layer, for fewer interoperability issues and infrastructure maintenance. IIn addition, we have pre-built service accounts to enable your third-party VMware-supported tools and solutions to work seamlessly in VMware Engine. Access to Google services privately over local connections is also natively supported, enabling enrichment of existing applications and modernization over time. Finally, this service brings the power of Google Cloud Virtual Private Cloud (VPC) design by natively providing multi-VPC, multi-region networking that’s unique. Let’s look at what’s new:

Dashboards for Day 2 operations: To speed up cloud transformation and enable efficiency, Google Cloud VMware Engine administrators can take advantage of Cloud Operations dashboards for the solution. In addition, administrators can create custom policies through cloud alerting and enable notifications via channels of their choice (SMS, email, Slack, and more). For more details on how to set up cloud monitoring, please refer to Setting up Cloud Monitoring. 

For the latest updates, bookmark Google Cloud VMware Engine release notes.

^{Thanks to Manish Lohani, Product Management, Google Cloud; Nargis Sakhibova, Product Management, Google Cloud; and Wade Holmes, Solutions Management, Google Cloud; for their contributions to this blog post.}