“Any device, anytime, anywhere.” A cohort of CIOs within Airbus believed that the cloud, combined with new ways of working, could provide the foundation for this vision. Google Workspace and Google Cloud have played a pivotal role in helping Airbus realize this new path, transforming security, data management, and collaboration along the way.

Adopting a secure-by-design approach

In adopting Google Workspace and Google Cloud Airbus needed to ensure a robust, zero-trust security model that works across the entire organization, even when employees are working outside the office. Google Workspace provides a single login that enables secure access to data, based on device and user information, as well as contextual inputs that inform the security risk of each login and user action. Airbus admins also use Google Workspace to define trust rules that govern what information and files can be shared within and outside the organization, making it easy for employees to comply with best practices from anywhere.

Encryption also plays a central role in keeping information secure and private. By default, Google Workspace uses the latest cryptographic standards to encrypt all data at rest and in transit. Google Workspace also offers client-side encryption, which Airbus uses for their most sensitive projects, giving them authoritative control over their data as the sole owner of their encryption keys.

And to ensure the organization is protected against hackers, Airbus has implemented sharding as a standard practice, thereby splitting data across multiple servers and data centers. Because the company works with incredibly sensitive information—including government and military information—the ability to locate data all within European data centers continues to be a necessity.

Powerful data management

Managing an enormous volume and variety of data, Airbus needs to ensure complete compliance with internal policies, as well as with external standards, like the General Data Protection Regulation (GDPR). Given this context, Airbus requires a solution that has strong built-in governance controls. Airbus also leverages the Drive labels feature, along with manual classification, to ensure that every file added to Google Drive is tagged and labeled correctly. In turn, these labels define the loss-prevention policies assigned to each file.

Staying connected during the pandemic

Before the pandemic, nearly every employee spent their workdays at an Airbus facility. When remote work became mandatory, the company made the pivot to Google Chat and Google Meet as an essential part of supporting real-time and asynchronous collaboration. Gmail also played a significant role in secure, anywhere-anytime communication, with its built-in anti-spam and anti-malware protections. Customizable filters let administrators protect against suspicious attachments, untrustworthy links, and countless other forms of malicious content. While Gmail blocks more than 99.9% of spam and phishing messages from ever reaching users’ inboxes, more advanced security measures like sandboxing can be put in place for specific use cases.

Protecting more than just data

Google Cloud’s sustainability efforts are as equally important to Airbus as data security. Google Cloud has been working to keep its climate footprint and those who use its services as low as possible, with all of Google currently carbon neutral and with a goal to run on carbon-free energy 24/7 at all of our data centers by 2030. And with our smarter, more efficient data centers, we’re already on that path with more than six times the computing power for the same amount of electrical power we used 5 years ago.

Building the future of work

By combining Google Workspace with Google Cloud, Airbus has been able to live up to its vision of “any device, anytime, anywhere.” The new model is a core foundation for its evolving future of work. Not only has Airbus adopted a zero-trust model across the organization, it’s also transformed how data is secured, managed, and accessed by employees working across a broad range of locations. The new flexible approach has also led to changes in how collaboration happens. Google is deeply gratified to have supported Airbus as they implement these changes and we continue to be proud that we’re running the cleanest cloud in the industry.

Want to learn more about how Google Workspace helps businesses like yours do more while keeping your data secure? Read this whitepaper to find out about our zero-trust model and other ways we protect organizations.

Over the past decade, cybersecurity has posed an increasing risk for organizations. In fact, cyber incidents topped the recent Allianz Risk Barometer for only the second time in the survey’s history. The challenges in combating these risks only continue to grow. Adversaries tend to be agile and are consistently looking for new ways to land within your digital environments. They also drive attack vectors that work, which means enterprise risk leaders are now forced to look for new ways of securing infrastructure and data.

Cloud comes of age in the modern day cybersecurity threat landscape

When cloud, in its various delivery models, was first introduced, it didn’t fit neatly into the security frameworks that had seemingly protected networks for many decades. Public cloud was the answer to ongoing IT challenges: scale, resources, security capabilities, and budget cycle limitations. Now, public cloud is meeting the increasing challenge of implementing cybersecurity controls and frameworks that are capable of protecting today’s global enterprise.

Cloud adoption – with all its scale and redistribution of longstanding security paradigms – is the optimal choice for infrastructure and security, particularly as organizations grapple with the need to engage in digital transformation. We assert that successful digital transformation is impossible without incorporating the use of the scale, security architecture, and resiliency of the cloud.

Consequently, cloud adoption becomes a necessary component of roadmap discussions and planning as your organization looks to reduce overall risk. Risk leaders and enterprise cybersecurity leaders must consider that moving data, digital processes, and priority workloads to the public cloud is a crucial step for meeting the current and future digital needs of the enterprise. Going forward, this digital transformation increasingly will include hybrid infrastructure environments composed of a combination of on-premises and cloud solutions.

Pinpointing where threats thrive

As digital environments become more complex within a given organization, proactively countering adversaries becomes all the more difficult. It’s harder to implement, scale, and adhere to existing security and control frameworks. It’s also increasingly challenging to apply framework guidance to new applications, build and support infrastructure within a secure foundation, and maintain good cyber hygiene through the digital lifecycle.

As reported by TechTarget, the 2020 hack of the SolarWinds Orion IT performance monitoring system is a prime example. It grabbed headlines “not because a single company was breached, but because it triggered a much larger software supply chain incident.” This vulnerability in popular, commercially available, and widely utilized software compromised the data, networks, and systems of thousands of companies when a routine software update turned out to be backdoor malware.

A close look at the root problems behind high-profile security breaches reveals that it’s a lack of agility and an inability to scale resources that prohibit the modern security organization’s ability to respond quickly enough to counter new challenges. Look even closer and you’ll often find an insufficient implementation of best practices and ineffective solutions, leaving an organization continually chasing the next tool or solution and scrambling to stay ahead of emerging threats.

While the cost to individual businesses is high, most organizations struggle with the needed skills and resources to rigorously maintain data security basics and ensure readiness for inevitable attacks. The previous sentence is especially true when you consider that maintaining an effective state of cybersecurity readiness is a costly practice that requires the continual development of expertise, the evaluation of new tools, and an ongoing element of vigilance.

Threat visibility is a big part of the problem. You can’t protect your company from what you can’t see. For individual enterprises – with critical data workloads housed in a combination of on-premises servers, a variety of endpoints, and both private and public cloud instances – staying ahead in the ongoing battle requires a new approach.

The identification of actionable alerts and other data contributes to a better overall state of readiness. Thought leadership and discussions related to Autonomic Security Operations provide a promising outlook for security organizations willing to lean into the changing technology landscape – a landscape that now benefits from leveraging automation and machine learning currently used in security stacks. Reducing the chance of introducing vulnerabilities or missing-critical alerts starts with ensuring full visibility into an increasingly expanding and complex environment.

The evolution of a shared responsibility to a shared fate

Industry megatrends are driving cloud adoption and with it a path to improved cybersecurity. Among these trends is the concept of shared fate as an evolution of the historical shared-responsibility model. Shared fate drives a flywheel of increasing trust which develops as more enterprises transition to the cloud. This compels an even higher security investment and a more vested interest from cloud service providers.

At Google Cloud, shared fate means we take an active stake in our customers’ security posture, offering capabilities and defaults that help ensure secure deployments and configurations in the public cloud. We also offer experience-based guidance on how to configure cloud workloads for security, and can assist with risk management, reduction, and transfer.

The Google Cloud Risk Protection Program represents the continuing evolution of the shared-fate model. The program offers a practical solution that provides the modern enterprise a snapshot comparison of its current security state against well-adopted cloud-security frameworks. It also give you an opportunity to explore cyber insurance designed to meet your needs from our partners Allianz and Munich Re.

When performed with diligence, cloud adoption can help increase your overall cybersecurity effectiveness. Using a hybrid approach – and steadily reducing which data assets remain on premises – can strengthen your overall security posture and reduce risks to the organization.

Cloud security and the ability to reduce risk

In comparison to the enterprise-by-enterprise security scramble to protect data and workloads in individual private clouds, global public cloud solutions like Google Cloud can be a force multiplier when adhering to established best practices. By that, we mean, quite literally, that you get more security at every touchpoint – from infrastructure and software to access and data security.

Strong security in the public cloud starts with the foundational pieces: the hardware and design elements. At Google, for example, we take a security-by-design approach within both the data center and purpose-built components themselves. Within Google Cloud, data is encrypted by default – both at rest and in transit. Google’s baseline security architecture adheres to the zero trust principles, meaning that every network, device, person, or service initially cannot be trusted.

Embarking on a zero trust architecture journey gives modern security practitioners the ability to methodically shut down traditional attack vectors. Zero trust also provides more granular visibility and control of rapidly expanding environments. The recent emphasis of its benefits, as the U.S. White House set forth through an executive order on increasing cybersecurity resilience, is an example of the wide-scale recognition by both government and industry on the benefits of this approach.

Since adopting a zero trust approach more than a decade ago, Google has achieved a recognizable level of maturity, reflected by our internal infrastructure and multiple enterprise offerings, enabling different aspects of the zero trust security journey.

Compliance and privacy drive critical elements of the cloud adoption cycle

Privacy frameworks, regulatory compliance, and data sovereignty are driving critical elements of the cloud adoption cycle. Cloud providers must ensure they have the necessary controls, attestations, and abilities to audit in order to provide organizations with the tools to preemptively satisfy regulatory and compliance mandates across the globe.

Now consistently expected to be part of a design feature that’s built into the cloud journey, it cannot simply be an add-on capability. The direction of this evolution promises to play more of a role in the future of cloud adoption, not less. Because this is an ongoing component of enterprise risk evaluation, your business must consider cloud providers that can partner on this critical aspect of the journey – and not leave you without the resources to respond to this growing critical need.

Building trust into your digital transformation journey

Digital transformation is difficult because the modern enterprise must build and design for both today and tomorrow. From a security perspective, the challenge has often been that security industry practitioners cannot always predict what the future will look like. That said, there are clear steps you can take to mitigate all-around risk throughout the process.

How you approach the cloud is, of course, integral to your journey, but it doesn’t need to be an all-or-nothing proposition. And although technology debt continues to persist with legacy systems, that doesn’t mean you shouldn’t begin to move forward.

Google Cloud enables you to modernize at your own pace and understand what’s realistic. We recommend you move what data you can to a more secure public cloud today, followed by a phased approach to move more in the months and years that follow. The key tenets of our approach to security in the public cloud include:

• The security-by-design posture of Google Cloud can help modern-day enterprises scale security capabilities and reduce risk with an architecture built on zero trust principles.
• The Google Cloud approach to security and resiliency includes a framework to help you protect against adverse cyber events by using our comprehensive suite of solutions.
• Google Cloud can help ensure your organization adheres to the requirements of a growing and increasingly complex regulatory and compliance environment.
• The ideal model of a future organization is one where cloud plays a major role in infrastructure design and architecture. Your organization should begin to view public cloud as an enabler of the business and a core component of digital transformation.

As you transition more data to the public cloud, it’s paramount that trust is ingrained in every step you take with your cloud service provider. Many service providers readily take on a shared responsibility with your organization when it comes to security. At Google, we take it several steps further with our shared fate model to help ensure data security in the public cloud. Your future and our’s are part of the same data security journey.

Even before the COVID-19 pandemic struck, the consumer packaged goods (CPG) industry was facing disruption. Consumers have come to expect personalized and seamless experiences at every point in their relationship with a brand. Additionally, consumers are expecting CPG brands to meet rising standards for sustainability, social responsibility, and transparency. Business models are shifting as well. Direct-to-consumer and subscription models have been gaining ground on traditional business models. Add in the CPG industry’s ever-present pressure for wider profit margins and the effects of the global pandemic, and you get a perfect storm of disruption. 

Leading CPG companies are responding to these changes by capitalizing on the potential of emerging technologies and leveraging the power of the cloud to create digital enterprises. In doing so, they can unlock value through reduced operational costs, faster innovation, improved marketing ROI, and greater transparency and sustainability—among other benefits. For businesses that run on SAP, accessing these benefits requires creating a digital enterprise with SAP at its heart. 

What CPG can expect from SAP on Google Cloud

SAP drives core business processes across most enterprise functions in CPG companies, and modernizing these operations is step one in unlocking next-level data and analytics capabilities. Creating a digital enterprise with SAP at the core requires establishing a digital foundation on a cloud platform capable of supporting and optimizing SAP workloads well into the future. From there, CPG companies can leverage the combination of SAP data and additional data signals to support high-value use cases utilizing the advanced analytics capabilities of the cloud

For CPG companies, running a successful digital enterprise in this climate depends on the power of the cloud because of the unmatched agility, security, scale, and flexibility offered by cloud technologies. More and more, consumer brands are turning to Google Cloud to host their applications—including core enterprise applications such as SAP—to drive business agility and maximize the value of data through smart analytics and machine learning. Google Cloud establishes a digital foundation for SAP customers by simplifying SAP deployments and offering  a suite of applications that integrates with and enhances SAP functionality. A Forrester study on the total economic value of Google Cloud for SAP customers found an average payback of less than six months and a total ROI of over 160%. By turning to Google Cloud to run their SAP systems, companies are able to: 

• Maximize insights 
  CPG enterprise data is often fragmented across disparate systems. Google’s analytics tools including BigQuery and Looker allow businesses to connect customer, operational and business data at scale by unifying data from SAP systems with other Google data signals such as Ads, Maps, Shopping or Google Marketing Platform. This precious data is fully democratized, allowing for complex queries to be completed rapidly so companies can uncover and analyze insights and create an end-to-end view of the consumer and the business.
• Create an intelligent organization
  Google’s AI and machine learning capabilities allow businesses to create built-in intelligence. Instead of reacting to trends, they can accurately predict them. For marketing teams, this could be the ability to evaluate promotions and effectiveness of marketing spend. For forecasting, product quantities and restock timing can be better planned. Supply chain optimization can include external data sources to closely monitor inventory and eliminate stock outs. 
• Future-proof your business
  Running SAP systems on Google Cloud creates an agile, secure and highly available environment that scales quickly as a business grows and as the CPG market evolves. A recent study conducted by IDC showed that SAP on Google Cloud deployments resulted in a 46% lower three-year cost of operations with 83% less frequent unplanned downtime and 56% more efficient IT teams. This frees IT resources to drive innovation and customer centricity. 
• Deliver on sustainability 
  Around the globe, consumers are becoming more and more demanding regarding sustainability. The impact of climate change and the abundance of plastic waste is only fueling this trend. Consumers are leaning into social signalling, and CPG companies are taking note. Sustainable IT is step #1, significantly advanced by  moving applications to Google Cloud, the cleanest cloud in the industry. We’ve neutralized all of our carbon emissions since our founding in 1998 and matched 100% of our electricity consumption with renewable energy purchases since 2017. Google Cloud allows SAP enterprises to further drive sustainability compliance and business objectives with AI and ML tools that can drive down waste and provide real-time decision making power to support proactive green initiatives. 

Rémy Cointreau is in high spirits after deploying SAP in the Google Cloud

Rémy Cointreau, a family-owned international maker of fine spirits, has products that can take up to one-hundred years to produce. But this long production cycle presents some unique challenges in today’s hyper-competitive premium beverage brands market. Since 1724, the company has been consumed with putting its customers first. In 2020, the company realized it was failing to capitalize on the benefits that the cloud can provide and began searching for a business partner that could help with this transformation.  

Rémy Cointreau made the move to Google Cloud for many reasons. First, the company could connect its SAP backbone to key SaaS applications like Salesforce. This enabled the creation of a 360-view of data among its ecommerce platform, SAP, and Salesforce to deliver sophisticated customer experiences that reflect the heart of the brand. The Rémy Cointreau team quickly realized they now had the ability to be more agile in their finance, manufacturing, and supply chain functions with easy access to valuable SAP system data that drives decision-making. Sebastien Huet, the company’s CTO, explains: “Now that we’re fully deployed on Google Cloud Platform, anything is possible. We can pull data in from multiple sources via integration and analyze it in a matter of days. We don’t need a three-month project to see value.”  

In today’s on-demand, omnichannel world, it’s not enough for CPG brands to understand their consumers. For companies like Rémy Cointreau, it is mission-critical that they anticipate consumer preferences and deliver personalized experiences. The winners will be the companies that can reduce time to insights by treating all their data as strategic assets, breaking down data silos to enable real-time business intelligence. With SAP on Google Cloud, CPGs are transforming consumer relationships and business outcomes.

Are you ready to change how your CPG brand operates? Check out this video and read the Google Cloud for SAP CPG customer white paper and ebook.  Learn more about how your peers are leveraging SAP on Google Cloud to evolve their businesses.

Like virtually every business across the globe, The New York Times had to quickly adapt to the challenges of the coronavirus pandemic last year. Fortunately, our data system with Google Cloud positioned us to perform quickly and efficiently in the new normal. 

How we use data

We have an end-to-end type of data platform; on one side we work very closely with our product teams to collect the right level of data that they’re interested in, such as which articles people are reading, and how long they’re staying onsite. We frequently measure our audience to understand our user segments, and how they come onsite or use our apps. We then provide that data to analysts for end-to-end analytics. 

On the other side, the newsroom is also focused on audience, and we build tools to help them understand how Google Search or different social promotions play a role in a person’s decision to read The New York Times, and also to get a better sense of their behavior on our pages. With this data, the newsroom can make decisions about information that should be displayed on our homepage or in push notifications. 

Ultimately, we’re interested in behavioral analytics—how people engage with our site and our apps. We want to understand different behavioral patterns, and which factors or features will encourage users to register and subscribe with us. 

We also use data to create or curate preferences around personalization, to ensure we’re delivering to our users fresh content, or content that they may not have normally read. Likewise, our data also gets used in our targeting system, so that we can send out the right messaging about our various subscription packages to the right users.

Choosing to migrate to Google Cloud

When I came to The New York Times over five years ago, our data architecture was not working for us. Our infrastructure was gathering data that proved harder for analysts to crunch on a daily basis. We were also hitting hang ups with how that data was streaming into our system and environment. Back then we’d run a query and then go grab some coffee, hoping that the query would finish or give us the right data by the time we came back to our desks. Sometimes it would, sometimes it wouldn’t.

We realized that Hadoop was definitely not going to be the on-premises solution for us, and that’s when we started talking with the Google Cloud team. We began our digital transformation with a migration to BigQuery, their fully managed, serverless database warehouse. We were under a pretty aggressive migration timeline, focusing first on moving over analytics. We made sure our analysts got a top-of-the-line system that treated them the way that they themselves would want to treat the data. 

One significant prominent requirement in our data architecture choice was to enable analysts to be able to work as quickly as they needed to provide high-quality deliverables for their business partners. For our analysts, the transition to BigQuery was night and day. I still remember when my manager ran his very first query on BigQuery and was ready to go grab his coffee, but the query finished by the time he got up from his chair. Our analysts talk about that to this day.

While we were doing the BigQuery transition, we did have concerns about our other systems not scaling correctly. Two years ago, we weren’t sure we’d be able to scale up to the audience we expected on that election day. We were able to band-aid a solution back then, but we knew we only had two more years to figure out a real, dependable solution. 

During that time, we moved our streaming pipeline over to Google Cloud, primarily using App Engine, which has been a flexible environment that enabled quick scaling changes and requirements as needed. Dataflow and Pub/Sub also played significant roles in managing the data. In Q4 of 2020 we had our most significant traffic ever recorded, at 273 million global readers, and four straight days of the highest traffic we’ve had compared to other election weeks. We were proud to see that there was no data loss.

A couple of years ago, on our legacy system, I was up until three in the morning one night trying to keep data running for their needs. This year, for election night, I relaxed and ate a pint of ice cream because I was able to more easily manage our data environment, allowing us to set and meet higher expectations for data ingestion, analysis and insight among our partners in the newsroom.

How COVID-19 changed our 2020 roadmap 

The coronavirus pandemic definitely wasn’t on my team’s roadmap for 2020, and it’s important to mention here that The New York Times is not fundamentally a data company. Our job is to get the news out to our users every single day in paper, on apps, and onsite. Our newsroom didn’t expect the need to build out a giant coronavirus database that would enrich the news they share every day. 

Our newsroom moves quickly, and our engineers have built one of the most comprehensive datasets on COVID-19 in the U.S. With Google, The New York Times decided to make our data publicly available on BigQuery Google’s COVID-19 public dataset. Check out this webinar for more details on our evolution architecture:https://www.youtube.com/embed/mtNlrFpschU?enablejsapi=1&

Flexible approach

We have many different teams that work within Google Cloud, and they’ve been able to pick from the range of available services and tailor project requirements keeping those tools available in mind.

One challenge we think about with the data platform at The New York Times is determining the priorities of what we build. Our ability to engage with product teams at Google though the Data Analytics Customer Council allows us to see into the BigQuery roadmap, or the data analytics roadmap, and plays a significant role in determining where we focus our own development. For example, we’ve built tools like our Data Reporting API, which reads data directly from BigQuery, in order to take advantage of tools like BigQuery BI Engine. This approach encourages our analysts to be better managers of their domains around dimensions and metrics, but not have to focus on building caching mechanisms of their data. Getting that kind of clarity helps us plan how to build The New York Times in the new normal and beyond.

If you are interested to learn more about the data teams at the New York Times, take a look at our open tech roles here and you’ll find many interesting articles at NYT data blog.