Seven-Eleven Japan Leverages Google Cloud’s Performance and Speed for Real-time Business Insights

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With the rise of technologies like smartphones, retailers have felt the pressure to meet evolving consumer needs and expectations. Seven-Eleven Japan(“SEJ”) has long been on the forefront of this thanks to the way they develop and invest in IT. However, in recent years, Japan’s leading convenience store chain has struggled to maintain its complex legacy systems at the rate needed to keep up with today’s rapid digitization, spurred on by the increasing proliferation of smartphones and an IT vendor-dependent structure.
Legacy systems limiting real-time responsiveness and innovation
Since its early days, SEJ has been proactive in adopting information technology, mainly relying on technology solutions from Japan’s leading vendors. But as the systems have grown, key business issues have been resolved using a vendor-dependent structure rather than being driven by SEJ’s own needs.
Datasets and business logic were combined and built into legacy environments, gradually leading to data silos. As a result, data was distributed across multiple systems, causing a variety of problems, including the inability to efficiently retrieve data when needed, delays in accessing data collected in individual stores, and difficulties taking measurements at the right time in business operations that require real-time responsiveness.
Connecting different systems also takes time and money, and the lead time for introducing new services—from planning to development and launch—has been longer than expected.
To solve these problems, SEJ’s IT department built “Seven Central”—a new platform for practical data use launched in 2020 to support the company’s future IT strategies and digital transformation initiatives.
At its core, Seven Central’s ultimate purpose is to allow real-time data views. Versatile, real-time datasets—such as point-of-sale (POS) data from 7-Eleven stores—are consolidated into a centralized location in the cloud. They created a simple data mart that provides data via an API to enable them to respond more quickly to requests from individual departments.
“In such uncertain times, it’s vital to use data to make quick decisions,” says Izuru Nishimura, Executive Officer and Head of ICT Department. “Each department across the entire company will be able to gain an immediate understanding of the situation based on the most up-to-date data and respond accordingly. This is why we built Seven Central.”
Google Cloud selected to help SEJ build and grow their data cloud
Today’s rapidly changing business environment has also highlighted the risk of IT support becoming a bottleneck. The long-term strategy is to gradually expand the datasets managed and collected in Seven Central according to business needs.
In the first phase, SEJ collected POS data from all 21,000+ stores to enable real-time analysis. Moving forward, they would like to collect other relevant data—for example, unstructured data, such as images and videos, or master datasets that are currently stored externally.
Google Cloud was already a top contender when SEJ started developing Seven Central in 2019. They compared various public cloud services besides Google Cloud, focusing on three main capabilities.
“We placed particular emphasis on service scalability to drive future digital transformation; security when handling data, which is the lifeline of our company; and finally, openness,” says Nishimura. He emphasizes that openness was perhaps the most important factor for choosing Google Cloud. Breaking away from the negative aspects of an entirely vendor-dependent system enabled them to build an agile development system with multiple vendors.
Google Cloud technologies including BigQuery and API management platform, Apigee, play a vital role in Seven Central. BigQuery’s high-speed processing at petabyte scale and fully managed infrastructure helped keep costs low during development and verification.
“Data is stored in a way that allows you to share it easily across organizations, which helps solve the issue of data silos from the perspective of scalability. I also like the fact there are some interesting features that could be used in the future—like BigQuery ML, which enables machine learning on BigQuery,” says Nishimura.
Apigee allows SEJ to separate datasets and business logic, which is one of the key points of Seven Central. While the trend these days is to standardize interfaces using an API, the reality tends to involve many different APIs rather than the introduction of one unified API. With Apigee, SEJ provides a single unified API for all of its data cloud, and they can now understand what data is used thanks to Apigee’s API usage visualizations.
“Right now, we collect data from all 21,000+ stores,” says Nishimura. “But in anticipation of a future expansion in business operations, we have designed a system that can scale up and run without issue, even if we were to have 30,000 stores, with 1,000 customers per store per day, purchasing five items per person.”
Real-time insights with BigQuery and Cloud Spanner

Google Cloud partner Cloud Ace came on board early in the planning phases. Based on their recommendations, SEJ decided to continue making full use of BigQuery to analyze data collected from all 21,000+ stores throughout Japan, while also using Cloud Spanner’s availability, near-unlimited scalability and transactional consistency to help achieve the real-time results needed for the project.
“Given that both the data and the regularity with which it is accessed are expected to steadily increase in the future, we chose Cloud Spanner as backend storage for data delivery via API. We consider it a good choice,” says Shota Kikuchi, General Manager, Consulting Department, Technology Division, Cloud Ace Co., Ltd.
Finally, they chose to use Google Cloud’s Stream Analytics Solutions messaging service for collecting POS data in real time, which can then be put to immediate use with Cloud Spanner and BigQuery.
High-speed responses exceed targets and create new value
Seven Central went live in September 2020 with surprising results.
They initially set a target time of one hour from when a customer makes a purchase to the point when Seven Central can use that data. But when the final system was first tried—it took barely a minute. Moving forward they estimate that the latest inventory data from the service side will become available within a few minutes of being added to the system.
“This is real innovation, and I must admit that I am quite surprised. As well as being able to solve existing issues, we also hope it will lead to new improvements and services that have been unimaginable up until now,” says Nishimura.
The team hopes to roll out the Seven Central platform in all companies affiliated with Seven & i Holdings—not just SEJ. They also plan to explore Google Cloud AI and machine learning technologies to take on challenges in new areas. For example, they are investigating the idea of clustering individual stores using BigQuery ML.
Seven Central has already attracted attention from many departments and received a lot of requests. Nishimura and his team say they hope to continue to grow Seven Central while still observing their fundamental principles—not including business logic, maintaining real-time results, and staying true to the uniqueness of SEJ.
Learn more about Google Cloud smart analytics solutions.
Google Cloud’s Professional Service Organization: How it Accelerates Operational Health Review Cloud Migration

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Introduction
The Google Cloud Professional Services Organization’s (PSO) mission is to help our customers get the most out of Google products. PSO is responsible for customer success by sharing our technical expertise in order to unlock business value from the cloud by providing cloud strategy and best practice advice, implementation guidance, and training using our proven methodology.
In this blog post, we want to focus specifically on Operational Health Reviews and how PSO engages in a myriad of activities to ensure the overall success and health of a customer engagement while ensuring we are meeting customer expectations and objectives, managing risk, and ultimately delivering value during or after the Google Cloud migration. We will discuss the assets, methodology, and tools that we leverage to ensure this success.
What is an Operational Health Review and what purpose does it serve?
Operational Health Reviews (OHR) are regular reviews to proactively address the below topics:
- A customer’s support experience
- Analysis of trends in key operational metrics
- Analysis of trends in Google Cloud usage
- Status reports for high-priority cloud projects
- Discussion of upcoming events
- Discussion of potential opportunities for training
- Review of feature requests
The core aim of an OHR is to measure progress and advise customers on the overall health of the account and migration progress while providing recommendations as a team on what adjustments should be considered to ensure continued success. During the OHR, we will address any pain points as well as identify and remediate any negative trends in support interfaces and usage metrics.
The intention of the activity is to also perform a blameless reflection for continuous improvement. This supports the effort to maintain common ground and obtain mutual optimism for the next phase of the customer’s journey on Google Cloud.
Let’s dive a little deeper into some of the activities that go into an OHR.
Support experience
One of the Google Cloud’s Support Organization’s goals is to simplify and streamline our customer’s support experience with a scalable and flexible set of offerings built with the customer needs at the center. This includes supporting an ongoing partnership model, with a proactive and collaborative approach. Premium Support is our top-tier support model which is a paid support offering designed for enterprises that run mission critical workloads and require fast response times, platform stability, and increased operational efficiencies. As part of this offering, customers are provided with a Technical Account Manager (TAM) who is in charge of delivering frequent touchpoints, including OHRs.
During the support experience section of an OHR, some of the following topics may be reviewed:
- Case volume by priority
- Case volume by product
- Cases linked to Google Cloud incidents
- Escalated cases or incidents
- Case initial response time (IRT)
- Case IRT SLO Met Rate
- Case total resolution time (TRT) hours

The purpose of this activity is to better understand the efficiency of both the customer’s and Google’s cloud operations from a support trend perspective. The goal is to celebrate any positive trends, but also to identify potential negative trends and proactively determine a remediation strategy.
Status reports for high-priority cloud projects
The purpose of this part of the OHR is to ensure the senior management stakeholders have continued visibility into the status of all their high-priority cloud initiatives with an easy-to-read, sometimes color-coded assessment on the status of each project. The assessment [Figure 1] may include, but is not limited to potential identified risks, key next steps, key stakeholders, and a mitigation plan for any high priority issues that may occur during their migration engagement. Additionally, the TAM may also cover any upcoming milestones or events, as well as any potential anticipated future blockers [Figure 2].


Review trends in Google Cloud usage
This part of the OHR is meant to provide the customer with a holistic view of their overall Google Cloud usage. The purpose is to provide understanding around what products are being used on Google Cloud and also where cost is generally being allocated for overall cost management and budget tracking purposes. This can help customers with their overall cost optimization efforts. Some of the metrics we may cover in this section are:
- Current Google Cloud usage by service
- Google Cloud growth trends
- Google Cloud growth trends by service
- Google Cloud growth trends by project
- Review of used and available service credits


Feature request review and advocacy
TAMs will work with customers to help identify product needs and advocate for feature requests with Google Product Management and Engineering teams. While feature request advocacy is an ongoing activity, during the OHR, the TAM will review any high priority feature requests that have previously been submitted, providing updates on status including potential release dates.
When a feature is coming up for the release, the TAM can help the customer prepare for implementation (providing early Preview access, coordinating a meeting with the Product Manager to review the feature, etc.) and then continue to provide support until the feature is successfully implemented in the customer environment. Similarly, if a high priority or technical blocking feature is not yet coming available, the TAM can help offer an alternative solution that can unblock the customer in the short term.
The OHR is also a great time for the TAM to work with the customer to ensure they have early access to new and exciting features that are in Alpha or Beta, and that would be beneficial to the customer and their environment.

Training strategy
Training is a primary component to ensuring the overall success in adopting Google Cloud. During the OHR, a review of training metrics will be provided. This may include tracking metrics to determine how the customer is tracking towards an initially agreed upon learning plan or coming up with additional upskilling strategies as necessary. Additionally, throughout an engagement, the customer’s TAM will provide opportunities for both free and paid Google Cloud training.

Conclusion
PSO is the voice of customer health, maintaining priority to proactively and strategically guide large enterprise customers to operate effectively and efficiently in the cloud, both during and after the migration process. The OHR is an efficient and effective way to maintain alignment, ensure expectations and objectives are being met, manage risk, and overall ensure the success of the customer.
Learn more about our methodology and get started with Google Cloud by completing a free discovery and assessment of your migration. Alternatively, if you’d like to engage directly with our PSO team on your migration, contact us!
Your DW Need Scaling Up? Try What This Company Did: It Can Run 25,000 Events a Second

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With access to more data than ever before, companies have never been better positioned to adopt precision marketing methods and target the right customers at the right time. Emarsys, a digital marketing platform, enables its clients to collect, analyze, and act on a wide variety of data. From websites to mobile apps to emails, Emarsys’ customers can handle data from all its digital channels on a single, easy-to-use platform. Emarsys also makes sure that customers receive the highest quality data possible, making for smarter decisions and better business practices.
“We were close to the limits of our internal data warehouse, scalability-wise. We didn’t want to get to the point where we’d have to delete data or cancel projects. In Google Cloud we saw a platform that could scale with our ambitions and be optimized for AI and real-time solutions.”
—Levente Otti, Head of Data, Emarsys
Since launching as an email solutions provider in 2000, Emarsys has grown into the world’s largest independent digital marketing platform, with more than 2,500 clients worldwide and reaching more than 1.4 billion people. By 2016, the company felt that its existing data warehouse platform was close to its limits, affecting not just day-to-day operations but also important strategic goals.
“We were close to the limits of our internal data warehouse, scalability-wise. We didn’t want to get to the point where we’d have to delete data or cancel projects,” says Levente Otti, Head of Data at Emarsys. “In Google Cloud, we saw a platform that could scale with our ambitions and be optimized for AI and real-time solutions.”
Minimal maintenance, unlimited scale with Google Cloud
Digital marketing is a highly competitive environment. Emarsys works alongside big players with a huge market share on the one hand and smaller, specialist companies on the other. It has thrived by successfully combining the all-inclusive offerings of the former with the agility of the latter, constantly looking for ways to innovate and improve. In recent years, the company had started to feel that the ability to handle large quantities of data was no longer enough. The next challenge was speed. “We truly believe that in the future, everything will be done in real time, including data processing, analytics, and AI predictive models,” Levente says.
At the start of 2016, Emarsys’ existing data warehouse was a software-as-a-service solution running on-premises, which required hardware and software maintenance in order to keep up with the company’s growing appetite for data-heavy use cases such as prediction and analytics. The existing platform had proven its worth processing large amounts of data in batches, but its real-time capabilities were limited. Moreover, Emarsys had begun to experiment with AI technology, but found that its data warehouse couldn’t scale to accommodate some of the more resource-intensive processes, such as training the predictive models. The company decided that it needed a new, cloud-based data platform.
After evaluating some of the leading cloud providers, Emarsys chose Google Cloud for its mature AI capabilities and its ease of use. “With the other solutions, we still had to rent virtual machines and hardware and be responsible for maintenance. At the time, Google Cloud was the only provider that could take that management overhead away from us, while keeping customers accounted for on every query level,” Levente says.
To implement its new data platform, Emarsys teamed up with Google Cloud Partner Aliz. Over a series of meetings, workshops, and architecture reviews, Aliz helped Emarsys navigate the Google Cloud ecosystem to find the right products for the solution it was looking for. “Aliz really helped us set off in the right direction,” explains Levente.
With Google BigQuery, we can run queries which process terabytes of data, in seconds. We can also develop our own user-defined functions, incorporating Bayesian statistics into our predictive algorithms. That means we can take into account historical data, resulting in much more accurate predictions in a scalable way within seconds.”
—Levente Otti, Head of Data, Emarsys
Emarsys’ new data platform would actually be two: one platform for batch processing data and one for real-time analysis and interactions. Firstly, a proprietary publishing component gathered all the data points from Emarsys’ various channels including the website, mobile, emails, and custom events. With Cloud Pub/Sub and Cloud Dataflow, Emarsys transported and processed the data into BigQuery, which allows for further work and reviews that take into account errors or delayed events. After this, the data was exported to the main batch processing platform, which ran on BigQuery. For the real-time analytics, Emarsys used Cloud Bigtable to access data and Cloud Dataflow to pipeline it into the real-time platform, which could communicate with AI components or interaction components via an API to deliver real-time interactions with customers.
On top of the overall data infrastructure, Emarsys built a new AI platform with Google Cloud components. Training the predictive models had been an issue in the past due to the large number of resources required, so Emarsys chose to use Google Kubernetes Engine clusters, which can scale up and down on demand, without the need for hardware configuration or management. The trained models were held securely in Cloud Storage. From here, they were integrated with BigQuery for power and flexibility, allowing Emarsys to improve not just the speed of its AI predictions but also the quality.
“With Google BigQuery, we can run queries which process terabytes of data, in seconds,” shares Levente. “We can also develop our own user-defined functions incorporating Bayesian statistics into our predictive algorithms. That means we can take into account historical data, resulting in much more accurate predictions in a scalable way within seconds.”
Real-time insight, long-term satisfaction
Google Cloud enabled Emarsys to build a scalable data and AI platform that delivers powerful, actionable insights in real time. According to Levente, the company wanted to spend less time managing overload and more time considering how it should handle data. An immediate result of the new platform has been that data is now available in a scalable way, without hardware additions and management.
“With Google Cloud, we’ve been able to build a truly real-time data platform. The norm used to be daily batch processing of data. Now, if an event happens, marketing actions can be executed within seconds, and customers can react immediately. That makes us very competitive in our market.”
—Levente Otti, Head of Data, Emarsys
The clear and innovative pricing schemes of Google Cloud have also brought a new level of accountability to Emarsys’ costs in a way that wasn’t possible with its on-premises infrastructure. “Now that we only pay for what we use, we can assign costs to specific customers or queries, which has a huge impact on our pricing and product development strategies,” says Levente.
Thanks to the power of BigQuery and the scale at which it can handle data, Emarsys can now apply its analytics and AI tools to their full potential. “It’s very important to enable our clients to create the best possible experience for customers,” says Levente. At the same time, the company has cut its AI platform costs by 70% with Kubernetes while increasing scalability compared to the previous solution. The whole data platform was built to be scalable, and its first big test came during the retail peak of Black Friday, when it comfortably handled 250,000 events per second. “Perhaps the biggest impact on the business came with the real-time nature of the new platform,” says Levente.
“With Google Cloud, we’ve been able to build a truly real-time data platform,” he explains. “The norm used to be daily batch processing of data. Now, if an event happens, marketing actions can be executed within seconds, and customers can react immediately. That makes us very competitive in our market.”
Since implementing the new platform, Emarsys has continued to innovate with it and is about to release a new Real-Time Decision Framework, which will provide customers with even more real-time products and tools. The company continues to work with Aliz and Google Cloud, exploring other products such as Google BigQuery ML and TensorFlow to improve its AI processes. “We had a problem that we wanted to tackle now, and for us, Google Cloud was the best way of doing that,” says Levente. “But it was also about looking ahead. We felt that Google Cloud offered us the best way of future-proofing our platform.”

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A well-executed digital transformation should do much more than keep you competitive… it should also position you to excel by untethering IT staff from low value, labor-intensive tasks, allowing them to focus on innovation and high-impact projects.
Also, replacing (or supplementing) legacy systems with modern technologies can reduce complexity and cost, while also positioning you to leverage cloud-native tools to achieve enhanced business intelligence and key strategic insights.
Finally, with nearly unlimited scalability at your fingertips, applications can scale up and scale down on demand, while you pay only for what you consume. This allows you to maintain a continuously right-sized cost profile, while also accelerating development and reducing procurement cycles.
Download this whitepaper to get a simple, prescriptive guidance to assist with the most important part of your digital transformation: the beginning.
Why Now Moving to Cloud is Great for Media and Broadcasting Companies

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The broadcasting industry has gone through many evolutions since its inception. From linear over-the-air (OTA) to digital & personalized, to standard to ultra high definition, these evolutions were driven by increased demand from viewers who want more choices. The next evolution is happening now, driven by the emergence in cloud computing in a globally connected world. Broadcasters are understanding that the key for long-term success is embracing technical agility while they innovate their business models. Google Cloud technologies can provide a path for continual transformation, empowering broadcasters a multitude of ways to chart their own growth.
As broadcasters evolve their business models and operations for a digital future, evaluating both financial alongside operational benefits will lead to the best outcome. Legacy and siloed media supply chains restrict the ability to deliver content quickly across multiple consumption platforms. By understanding how cloud capabilities can provide cost savings, allow for more efficiency and scale, and open new revenue streams, broadcasters can harness flexible cloud technologies while achieving cost savings and increasing revenue.
Media workflows in the cloud
Over the last few years we have seen tremendous growth from media companies migrating their supply chains to the cloud. Today, there exists a whole ecosystem of media technologies that are built to take advantage of the cloud. “Does it work on the cloud?” is no longer driving the conversation. Rather, media companies now want to understand how Cloud can integrate with their business and drive better business outcomes.
Over the last years we have partnered with leading media companies including Grupo Globo, TelevisaUnivision and others to not only migrate their content supply chain to the cloud, but also leverage cloud capabilities to innovate their services to:
- Increase and streamline content production
- Distribute personalized content at planet scale
- Forge deep relationships with their audiences
- Identify new monetization opportunities
Impact of Cloud on Performance & Financials
M&E companies need to be able to provide more content at a quicker pace, with experiences that are seamless and exciting to viewers to retain their attention and dollars. Moving legacy systems and processes to the cloud is an organization-wide commitment, and the journey can pay off financially, while providing M&E companies valuable industry capabilities. With Google Cloud business value engagement framework, we partner to identify where there are opportunities in cost, output, and impact that IT can have.
Below are some examples of how we have worked with our customers to map organization optimizations to business drivers

Working Together – How can Google help
Our focus with customers is to help identify and understand the challenges that Media & Entertainment companies have in moving to the cloud, and coming up with the plan and solutions that Google can do to overcome them. Together we commit to understanding your business, both where you are right now in your IT capabilities as well as the progress you want to make to continue providing the best digital capabilities to clients and employees.

As broadcasters move more processes and solutions to the cloud, the exponential effect of harnessing data and AI power will provide incremental business value across all lines of business. Combined, these impacts to a broadcaster allow both operational excellence while optimizing costs as they continue to expand offerings to customers and regions around the world.
We recognize that every media company’s journey is different and so are expected business outcomes. Google Cloud works closely with customers – partnering every step of the way – to align technology, the media industry, and business outcomes.
Building a Stronger South Bend through Cloud Computing Education

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The city of South Bend, Indiana has announced they are working with Google Cloud to connect 500 local job seekers with no-cost access to Google Cloud Skills Boost through Upskill SB. This initiative will train, upskill, and certify residents in cloud computing skills to create pathways to technical jobs.
As companies, nonprofits, and governments increasingly leverage cloud computing technology to strengthen their organizations, skilled cloud talent is in high demand both nationally, in Indiana, and in South Bend. According to Lightcast, there were 27,180 unique cloud roles open in the U.S. as of October 2022. Cloud skills are the most in-demand skill set by IT departments: more than one-third of tech learners said professionals with cloud skills are the most challenging to find.
“This partnership with Google Cloud will help residents get on a no-cost path to a cloud computing career at a time when the field is rapidly growing,” said Caleb Bauer, Executive Director of Community Investment for the City of South Bend. “This will help residents prepare to take the next step in their career with Google Cloud Skills Boost and will pave the way to build in-demand skills.”
Google Cloud Skills Boost is the destination for all Google Cloud learning and training opportunities. Local colleges and universities are also able to offer free access to Google Cloud Skills Boost for students through the Google Cloud Higher Education program. Students can request access to free online labs, quests, and courses. Faculty can take advantage of free Google Cloud Computing Foundations curriculum and coach their students to prepare for Google Cloud certifications.
“Google is proud to offer no-cost access to Google Cloud Skills Boost for jobseekers in South Bend,” said Alice Kamens, Workforce Development lead at Google Cloud. “Through this partnership, we’re advancing our work to ensure everyone has access to the technical training needed to pursue cloud computing careers.”
Those interested in learning more about the program or applying for Upskill SB should visit the Google Cloud page on Upskill SB. Scholarship recipients need access to a computer, hand-held device or smartphone and the internet.
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