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Your DW Need Scaling Up? Try What This Company Did: It Can Run 25,000 Events a Second

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“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, Emarsys, a digital marketing platform.

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.”

Emarsys data and AI platform
Case Study

Manipal Group: Delivering High-Quality Patient Care with Google Cloud

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Manipal Group of Hospitals deployed a mobile application that automates nurse rostering, reducing personnel requirements, costs, and stress on nurses and freeing up senior nurses for more valuable tasks.

One of India’s best-known healthcare brands, Manipal Group prides itself on clinical excellence and a patient-centric approach. From humble beginnings in 1953 as a single teaching hospital—the Kasturba Medical College—in a university town in Karnataka, India, Manipal Group has grown to a presence in seven cities in India and operations in Malaysia and Nigeria. “Our founder, Dr T. M. A. Pai, established Kasturba Medical College just six years after India gained independence,” says C. G. Muthana, Chief Operating Officer, Teaching Hospitals, Manipal Health Enterprises Pvt. Ltd, part of Manipal Group.

Manipal Health Enterprises Pvt. Ltd operates 11 corporate, or for-profit, hospitals and five teaching hospitals. “We have about 7,000 beds India-wide, and on that measure, we are the third-largest private-sector healthcare provider in India today,” says Muthana. The organization now employs about 6,000 people in its corporate hospitals and 5,000 people in its teaching hospitals.

Manipal Health Enterprises Pvt. Ltd acquires and operates world-class medical technologies in its teaching and corporate hospitals. However, with 75% of corporate hospital wards allocated to fee-paying private patients—compared to just 25% of the wards in teaching hospitals—the differences in information technology budgets are significant. “In the general wards that comprise most of the wards in teaching hospitals, patients are typically treated for free or at heavily subsidized rates,” explains Muthana. “So revenues and costs of delivery vary between hospitals, while employee costs remain similar.”

Rostering nurses a critical task

Rostering nurses to work shifts is one of the most important tasks at Manipal Group corporate and teaching hospitals. As at all hospitals, nurses administer medications, monitor patients, maintain records, manage intravenous lines, and work with doctors to heal patients. They can also provide advice and support to patients and loved ones, including teaching them how to administer medication outside a hospital setting. If too few nurses are rostered for a particular shift, the quality of patient care may suffer.

Google Cloud results

  • Enabled the hospital to correctly size its nursing workforce
  • Lowers stress on nurses by delivering more equitable rostering
  • Presents opportunity to better manage nurses’ leave and other administration tasks

However, rostering at the group’s hospitals was a time-consuming exercise. Senior nurses on each ward would have to spend up to 45 minutes per day manually amending paper-based rosters to accommodate requested changes to duty shifts for personal or other circumstances. The organization began receiving complaints from patients, doctors, and other hospital staff that, on occasion, too few nurses were rostered on for certain shifts—particularly at its flagship hospital in Bangalore. “We had based our rostering calculations on the number of beds occupied by patients and, when we investigated, we found at a macro level, we were rostering on the correct number of nurses,” says Muthana. “However, on some days, on wards optimally staffed by, say, 10 nurses per shift, we might have 14 nurses rostered on for one shift and seven rostered on for another shift. Those times we had seven, we had a clear shortage.”

In 2012, Muthana asked a consultant to develop algorithms to help automate the rostering. “Unfortunately, there were so many variables, the consultant failed to solve the problem,” he says. The Chief Operating Officer’s next step was to ask the founder and Chief Executive Officer of predictive analytics business Retigence Technologies—already working with the business on a materials management project—to develop an application to manage rostering.

Removing the daily drudgery

“Our plan with the automation project was to relieve our senior nurses of the daily drudgery of amending the rosters and to deliver rosters that were as fair as possible to all our staff,” says Muthana. “We also saw an opportunity to reduce our costs by reducing the overall number of nurses needed to look after our patients.”

Retigence Technologies’ team members then worked with the group’s nurses to capture the variables and requirements for the project. For example, a minimum number of nurses with one year experience or more needs to be rostered on for each shift. Retigence Technologies then started building an application using compute resources available through Compute Engine, a Google Cloud product. “We selected Google primarily because of its pioneering work in artificial intelligence (AI) and machine learning,” says Srinibas Behera, founder and Chief Executive Officer of Retigence Technologies.

With the nurses rostering application developed, Manipal Health Enterprises Pvt. Ltd undertook several pilots to build user acceptance. “Some of our senior nurses took time to accept the fact automation removed their control over rostering assignments, but were finally convinced by the better transparency the product offered,” says Muthana. The organization deployed the application to a smaller hospital and secured user support before rolling out the application to its Bangalore flagship.

Eliminating stress

Deploying the application has enabled Manipal Health Enterprises Pvt. Ltd to remove a buffer of about 100 nurses retained to accommodate the variations in number of nurses rostered for individual shifts. “The savings on those salaries more than paid for the cost of developing the application,” says Muthana.

The application also enabled the organization to reduce the stress on nurses—both the nurses in charge of the rosters and the nurses subject to the rosters. “Night shifts were more equitably distributed among the nurses, while we have been able to reduce the 45 minutes per day required to amend rosters to just 10 minutes,” says Muthana. “In Bangalore alone, we have 51 nurses in charge of rostering—so the combined saving there equates to nearly 30 hours per day.” This is freeing up these senior nurses to complete more important tasks.

The application was subsequently implemented at Kasturba Hospital, Manipal, again reducing the time needed to generate complete nursing rosters to less than 10 minutes.

Managing leave and training

The organization now plans to extend the application to manage leave and training for its nurses and other employees. “I would like to see every employee given an annual leave plan that is added to the roster at the start of the year,” says Muthana. “The flexibility and control afforded by the application would enable us to address challenges such as managing leave across a workforce with high attrition rates.” The organization would also be able to create a calendar to ensure nurses receive all their required training.

“We also plan to keep fine-tuning the application to deploy nurses more efficiently and continue to reduce their stress levels,” adds Muthana. “We also want to create a nursing load indicator tailored to patients’ specific circumstances. For example, a sedated patient may not require much nursing care, whereas a patient who comes in with a broken leg and may be on a ventilator may require assistance from three nurses at once.” The business plans to use Google’s AI and machine learning APIs in the future to improve the value and user experience of the product.

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A Year of Going Carbon-free! Google’s Road to Sustainability Looks Promising

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Google Cloud announced its sustainability goal to turn fully carbon-free by 2030. To mark the progress of the data centres on the road to sustainability, Google Cloud releases 2020 carbon-free energy percentages (CFE%). Read to know more.

Last year, we announced our most ambitious sustainability goal yet: to operate everywhere on 24/7 carbon-free energy by 2030. We’ve set this goal to ensure that Google Cloud continues to be the cleanest cloud in the industry, and to show that full-scale decarbonization of electricity use is possible. 

Since setting our target, we’ve made tremendous progress in how we trackbuy, and use electricity; advocate for clean energy policies; and support the development of new technologies to help us reach this goal. And we’ve done it all while maintaining a commitment to transparency that we hope will make it easier for other organizations wishing to fully decarbonize their operations as well.

In the spirit of transparency, today we’re releasing the 2020 carbon-free energy percentages (CFE%) for all Google data centers, as well as overall progress on the road to our 2030 goal: In 2020, Google achieved 67% round-the-clock carbon free energy across all its data centers, up from 61% in 2019. In other words, of all the electricity consumed by Google data centers in 2020, two-thirds of it was matched with local, carbon-free sources on an hourly basis.

Though we saw a significant jump in global CFE% in 2020, we expect the numbers to vary from year to year. Ultimately, CFE% is dependent on the amount of new clean energy that comes online in a given year; we may even occasionally see short-term drops in the numbers. What’s most important is that we continue to maintain a long-term trajectory toward our 2030 goal. With meaningful progress in clean energy policy, technologies, and transactional models, we believe 24/7 carbon-free energy is achievable.

Tracking these numbers also allows us to give Google Cloud customers greater control in their own sustainability efforts. Earlier this year we announced Google Cloud Region Picker, a system that helps our customers assess factors like cost, speed, and CFE% as they choose where to run their applications. 

To outline some of the events that have helped us get to 67% CFE%, we’ve developed an animation that shows every hour of electricity use in 2020, at all our Google data centers around the world. 

Visualizing clean energy: every hour, every day, everywhere

Imagining what every hour in a year looks like is hard enough (there are 8,760 of them, in case you’re wondering). With 23 data centers and 25 cloud regions around the world, we’re aiming to source clean energy for over 200,000 operational hours each year.

https://youtube.com/watch?v=f9ecEokcFlk%3Fenablejsapi%3D1%26

The “A year in carbon-free energy” animation points out significant projects that came online in 2020 to bring our data centers closer to operating entirely on round-the-clock carbon-free energy. It also reflects an unparalleled level of transparency about our carbon-free energy data, showing hour-by-hour where we need to develop new clean energy projects, advocate for policy changes, and in some cases, look to new technologies that can help fill in the gaps left by variable renewable resources. 

In the animation, you’ll notice sites with a lot of green at midday (e.g. in Chile or the U.S. Southeast) – a sign that solar is making a big contribution. Other data centers, such as our facilities in the U.S. Midwest, rely more heavily on wind power and are subject to seasonal fluctuations in wind speed. 

Preventing the worst impacts of climate change will require decarbonizing the world’s electric grids, as fast as possible. Google is committed to doing as much as possible to clear a path for others and drive collective action to achieve this goal. We’re thrilled to be in good company as we move, together, toward a carbon-free future.

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Highmark & Google’s Secure-by-design Technique to Bring the Living Health Solution to Life

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U.S. prominent health and wellness firm, Highmark uses Google Cloud and Google Cloud Professional Services Organization to build an innovative platform that delivers a unique experience for customers across billing and insurance. Read more!

In an industry as highly regulated as healthcare, building a single secure and compliant application that tracks patient care and appointments at a clinic requires a great deal of planning from development and security teams. So, imagine what it would be like to build a solution that includes almost everything related to a patient’s healthcare, including insurance and billing. That’s what Highmark Health (Highmark)—a U.S. health and wellness organization that provides millions of customers with health insurance plans, a physician and hospital network, and a diverse portfolio of businesses–decided to do. 

Highmark is developing a solution called Living Health to re-imagine healthcare delivery, and it is using Google Cloud and the Google Cloud Professional Services Organization (PSO) to build and maintain the innovation platform supporting this forward thinking experience. Considering all the personal information that different parties like insurers, specialists, billers and coders, clinics, and hospitals share, Highmark must build security and compliance into every part of the solution. 

In this blog, we look at how Highmark Health and Google are using a technique called “secure-by-design” to address the security, privacy, and compliance aspects of bringing Living Health to life.

Secure-by-design: Preventive care for development

In healthcare, preventing an illness or condition is the ideal outcome. Preventive care often involves early intervention—a course of ideas and actions to ward off illness, permanent injury, and so on. Interestingly, when developing a groundbreaking delivery model like Living Health, it’s a good idea to take the same approach to security, privacy, and compliance. 

That’s why Highmark’s security and technology teams worked with their Google Cloud PSO team to implement secure-by-design for every step of design, development, and operations. Security is built into the entire development process rather than waiting until after implementation to reactively secure the platform or remediate security gaps. 

It’s analogous to choosing the right brakes for a car before it rolls off the assembly line instead of having an inspector shut down production because the car failed its safety tests. The key aspect of secure-by-design is an underlying application architecture created from foundational building blocks that sit on top of a secure cloud infrastructure. Secure-by-design works to ensure that these building blocks are secure and compliant before moving on to development.

The entire approach requires security, development, and cloud teams to work together with other stakeholders. Most importantly, it requires a cloud partner, cloud services, and a cloud infrastructure that can support it. 

Finding the right cloud and services for secure-by-design 

Highmark chose Google Cloud because of its leadership in analytics, infrastructure services, and platform as a service. In addition, Google Cloud has made strategic investments in healthcare interoperability and innovation, which was another key reason Highmark decided to work with Google. As a result, Highmark felt that Google Cloud and the Google Cloud PSO were best suited for delivering on the vision of Living Health—its security and its outcomes. 

“Google takes security more seriously than the other providers we considered, which is very important to an organization like us. Cloud applications and infrastructure for healthcare must be secure and compliant,” explains Highmark Vice President and Chief Information Security Officer, Omar Khawaja. 

Forming a foundation for security and compliance

How does security-by-design with services work? It starts with the creation and securing of the foundational platform, allowing teams to harden and enforce specified security controls. It’s a collaborative process that starts with input from cross-functional teams—not just technology teams—using terms they understand, so that everyone has a stake in the design. 

A strong data governance and protection program classifies and segments workloads based on risk and sensitivity. Teams build multiple layers of defense into the foundational layers to mitigate against key industry risks. Google managed services such as VPC Service Controls help prevent unauthorized access. Automated controls such as those in Data Loss Prevention help teams quickly classify data and identify and respond to potential sources of data risk. Automation capabilities help ensure that security policies are enforced.

After the foundational work is done, it’s time to assess and apply security controls to the different building blocks, which are Google Cloud services such as Google Kubernetes EngineGoogle Compute Engine, and Google Cloud Storage. The goal is to make sure that these and similar building blocks, or any combination of them, do not introduce additional risks and to ensure any identified risks are remediated or mitigated. 

Enabling use cases, step by step

After the foundational security is established, the security-by-design program enables the Google Cloud services that developers then use to build use cases that form Living Health. The service enablement approach allows Highmark to address complexity by providing the controls most relevant for each individual service. 

For each service, the teams begin by determining the risks and the controls that can reduce them. The next step is enforcing preventive and detective controls across various tools. After validation, technical teams can be granted an authorization to operate, also called an ATO. An ATO authorizes the service for development in a use case.

For use cases with greater data sensitivity, the Highmark teams validate the recommended security controls with an external trust assessor, who uses the HITRUST Common Security Framework, which maps to certifications and compliance such as HIPAANISTGDPR, and more. A certification process follows that can take anywhere from a few weeks to a few months. In addition to certification, there is ongoing monitoring of the environment for events, behavior, control effectiveness, and control lapses or any deviation from the controls.

The approach simplifies compliance for developers by abstracting compliance requirements away. The process provides developers a set of security requirements written in the language of the cloud, rather than in the language of compliance, providing more prescriptive guidance as they build solutions. Through the secure-by-design program, the Highmark technology and security teams, Google, the business, and the third-party trust assessor all contribute to a secure foundation for any architectural design with enabled Google Cloud services as building blocks. 

Beating the learning curve 

Thanks to the Living Health project, the Highmark technology and security teams are trying new methods. They are exploring new tools for building secure applications in the cloud. They are paying close attention to processes and the use case steps and, when necessary, aligning different teams to execute. Because everyone is working together collaboratively toward a shared goal, teams are delivering more things on time and with predictability, which has reduced volatility and surprises. 

The secrets to success: Bringing everyone to the table early and with humility

Together, Highmark and Google Cloud PSO have created over 24 secure-by-design building blocks by bringing everyone to the table early and relying on thoughtful, honest communication. Input for the architecture design produced for Highmark came from privacy teams, legal teams, security teams, and the teams that are building the applications. And that degree of collaboration ultimately leads to a much better product because everyone has a shared sense of responsibility and ownership of what was built. 

Delivering a highly complex solution like Living Health takes significant, more purposeful communication and execution. It is also important to be honest and humble. The security, technology, and Google teams have learned to admit when something isn’t working and to ask for help or ideas for a solution. The teams are also able to accept that they don’t have all the answers, and that they need to figure out solutions by experimenting. Khawaja puts it simply, “That level of humility has been really important and enabled us to have the successes that we’ve had. And hopefully that’ll be something that we continue to retain in our DNA.”

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Maximizing the Value of Your Cloud Migration

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Technology leaders have shifted many apps and workloads to public cloud, and they are not finished; 63% plan further expansion in the next 12 months.

According to this newly resealed Forrester report, enterprises are migrating all types of apps and workloads to cloud and the migration provides firms with a wide range of IT benefits.

Download this Forrester Report to learn how to maximize the value of your cloud migration.

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