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Case Study

Kohl’s Leverages Google Cloud Platform for Omnichannel Retail

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When Kohl’s, an omnichannel retailer, wanted to focus on driving traffic, operational efficiency and delivering seamless omnichannel customer experiences, it turned to Google Cloud. It's a decision that worked well.

Kohl’s is an omnichannel retailer focused on driving traffic, operational efficiency and delivering seamless omnichannel customer experiences.

Ratnakar Lavu is Kohl’s Senior Executive Vice President and Chief Technology Officer. He, and Kohl’s, are at the forefront of retail technology innovation, focusing on a frictionless customer journey across digital, mobile and more than 1,150 stores.

As part of this journey to more closely unify its online and offline experiences for customers, the company was looking for supporting cloud services that would continue to drive  best-in-class data center infrastructure; the ability to manage data at a very large scale; and industry leading analytics and machine learning tools to continually understand real time data streams and help personalize experiences for their customers.

Kohl’s recognized the opportunity to take on a cloud partner to help drive the improvement of the speed and reliability of their operations, while they focused on a number of innovations to deepen customer experiences.

“At the time, I was looking for an open and scalable platform to partner with our Kohl’s technology team as we transform our business by shifting to the cloud,” says Ratnakar.

“Google has great engineering talent as well as demonstrated experience solving stability and scale in its own Ads and Search business. At Kohl’s, we need to be bold and innovative in today’s retail environment, and therefore need partners who deeply understand how to manage risk.” 

Kohl’s leveraged several capabilities of Google Cloud. For example:

  • They built applications to automate deployment, scaling and operations.
  • They used monitoring capabilities to monitor for things like response time.
  • Scalable technology provided an infrastructure to elastically scale to site traffic.
  • They ran their infrastructure across multiple regions for high availability.

In 2017 and 2018, record-setting numbers of customers visited Kohls.com during the Thanksgiving holiday weekend and the digital platform experienced high double-digit growth both years.

The capabilities provided by Google Cloud Platform (GCP) and Google’s data center infrastructure supported Kohl’s servers and systems during these key timeframes.

In addition, the Kohl’s team partnered together with Google’s core engineering team and services organization to optimize applications and make them more reliable.

Google Cloud’s Customer Reliability Engineers (CREs) worked with them in advance of their peak time frames to test the infrastructure for performance, scaling, and fault tolerance.

“Google CRE and services teams collaborated with us as we ran drills and exercises during each phase of preparation for peak time frames,” Ratnakar said. “As we continued to understand better how to scale, monitor, and support our applications in GCP and we are pleased that we worked with the CRE team as partners on monitoring services, alerting teams, and triaging work.”

Case Study

If You Run Your Country’s Largest Retail Franchise, How Do You Pull Together, in Sync?

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Tired of failing email systems, South Africa’s largest electrical retail franchise switched to G Suite. The move eliminated email downtime, enabled cross-company assessments on dashboards, faster sharing of ideas, and seamless administration.

In 1984, Mario Maio set up a small business manufacturing electrical transformers in his Johannesburg garage. Over the next two decades, the ACDC Dynamics company he created came to dominate manufacturing, import, and distribution in South Africa’s electrical goods sector. Then, in 2007, Mario’s son, Ricardo Maio, founded a retail arm to the business, ACDC Express. Today ACDC Express is South Africa’s largest electrical retail franchise, with 29 franchise stores across the country. Eight of those franchises joined in 2017 alone, and ACDC Express is experiencing quarter-on-quarter growth of 28% per year.

Rapid expansion increases the demands on the ACDC Express central administration, which provides each franchise with IT support and a full suite of marketing, operational, and bookkeeping functions. So when email server downtime became a frequent problem, Ricardo and his team chose G Suite to transform the way the franchise worked.

“We lost revenue when our email servers went down. When I researched Google’s SLA of 99.9% uptime and experimented with G Suite on my private Gmail account, I could see the difference this technology could create.”

Ricardo Maio, CEO, ACDC Express

“On consecutive occasions, our entire email server went down,” says Ricardo Maio, CEO at ACDC Express. “It would take more than one or two days to bring it back up. We had already highlighted software cost overhead as a potential thing to reduce, so when that happened several times within a short period, we knew it was time to make a change.”

Building a better franchise

Franchise businesses undergoing rapid expansion must respond quickly to the demands of new stores. At ACDC Express, 33 staff run the national franchise, delivering core services and support to 29 franchises across the country. Key tasks, such as updating the operations manual, were hampered by a reliance on paper forms and mail services, while email servers experienced repeat failures, which compromised communication. By implementing new, cloud-based productivity tools, ACDC Express looked to cut down on slow and expensive practises, and deliver an agile, reliable online communications platform.

To do that, ACDC Express migrated its franchise to G Suite with Opennetworks. “We lost revenue when our email servers went down,” says Ricardo. “When I researched Google’s SLA of 99.9% uptime and experimented with G Suite on my private Gmail account, I could see the difference this technology could create.”

Since moving to Gmail, ACDC Express reports that the problem of email server downtime “is no longer existent for us,” while with Google Drive, versioning problems have been resolved. Using surveys on Google Forms, ACDC Express quickly and easily collects data from stores and customers—whether they are in stores or on the road—and populates Google Sheets with the information.

“Our operations manual is a binding document, and it’s a living document that gets regularly updated. In the past, we would struggle to track which franchise had which version. With Google Drive, we can be sure that everyone is looking at the right one.”

Ricardo Maio, CEO, ACDC Express

With Google Data Studio, the managing team then consolidates that data on dashboards, creating snapshots of performance, complete with averages and simple comparisons, which make it easy to spot issues and outliers in need of attention. Individual businesses that do require help are then contacted over Google Hangouts Meet to assess what they need, part of a culture of sharing expertise, which Ricardo sees as key to the franchise mode.

“As a franchise, sharing knowledge is as important as maintaining control,” he says. “If there’s a new procedure or system that worked in one store, we can immediately update our manuals and documentation so that everyone has access to it. That’s been fantastic.”

“Our operations manual is a binding document, and it’s a living document, which gets regularly updated,” says Ricardo. “In the past, we would struggle to track which franchise had which version, and every time we had to make a change we would print out a version and send it to stores through an unreliable postal service. With Google Drive, we can be sure that everyone is looking at the right one.”

Remote training, rapid migration

Rolling out new IT tools across a franchise is often expensive, demanding extensive travel and numerous training sessions, which often repeat the same material. Instead, ACDC Express set up training on Google Hangouts that staff could drop into at their convenience, creating a cost-effective training schedule, which meant individual stores could plan their own learning process.

“When we moved to G Suite, we did it all at once, with every employee changing at the same time. We took a band-aid approach, switching to the new tools as rapidly as possible. After six months of training, there have been no reported problems with G Suite at all.”

Ricardo Maio, CEO, ACDC Express

“The whole benefit of franchising is that you can learn from your peers,” says Ricardo. “When we moved to G Suite, we did it all at once, with every employee changing at the same time. We took a band-aid approach, switching to the new tools as rapidly as possible. After six months of training, there have been no reported problems with G Suite at all.”

More mobile, more reliable

Today, ACDC Express operates 240 Google accounts, and information from the franchises’ marketing systems, research, operations, and accounting is fed back automatically to Google Sheets and Google Dashboard at the headquarters in Edenvale, Gauteng. By Ricardo’s estimation, the administrative team is now so effective with G Suite tools, it can achieve twice as much as it could without them.

Now, ACDC Express is looking to use Google Chromebooks in a new web-based point-of-sale system, and considering moving its ERP onto Google Cloud Platform for greater stability, in another project with Opennetworks.

“We’ve developed an in-house point of sale system that’s web-based and can use a functional touchscreen,” adds Ricardo. “We’re looking at rolling that out with Google Chromebooks. We really like how straightforward and simple the Google Chrome devices are, and because we’ve taken a lot of infrastructure into the cloud, we no longer actually need physical machines on our counters. We can work anywhere. That’s something that applies from our head office right down to our smallest franchise store.”

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Podcast

Rethinking Financial Services with Google Cloud

Kohl’s is an omnichannel retailer focused on driving traffic, operational efficiency and delivering seamless omnichannel customer experiences.

Ratnakar Lavu is Kohl’s Senior Executive Vice President and Chief Technology Officer. He, and Kohl’s, are at the forefront of retail technology innovation, focusing on a frictionless customer journey across digital, mobile and more than 1,150 stores.

As part of this journey to more closely unify its online and offline experiences for customers, the company was looking for supporting cloud services that would continue to drive  best-in-class data center infrastructure; the ability to manage data at a very large scale; and industry leading analytics and machine learning tools to continually understand real time data streams and help personalize experiences for their customers.

Kohl’s recognized the opportunity to take on a cloud partner to help drive the improvement of the speed and reliability of their operations, while they focused on a number of innovations to deepen customer experiences.

“At the time, I was looking for an open and scalable platform to partner with our Kohl’s technology team as we transform our business by shifting to the cloud,” says Ratnakar.

“Google has great engineering talent as well as demonstrated experience solving stability and scale in its own Ads and Search business. At Kohl’s, we need to be bold and innovative in today’s retail environment, and therefore need partners who deeply understand how to manage risk.” 

Kohl’s leveraged several capabilities of Google Cloud. For example:

  • They built applications to automate deployment, scaling and operations.
  • They used monitoring capabilities to monitor for things like response time.
  • Scalable technology provided an infrastructure to elastically scale to site traffic.
  • They ran their infrastructure across multiple regions for high availability.

In 2017 and 2018, record-setting numbers of customers visited Kohls.com during the Thanksgiving holiday weekend and the digital platform experienced high double-digit growth both years.

The capabilities provided by Google Cloud Platform (GCP) and Google’s data center infrastructure supported Kohl’s servers and systems during these key timeframes.

In addition, the Kohl’s team partnered together with Google’s core engineering team and services organization to optimize applications and make them more reliable.

Google Cloud’s Customer Reliability Engineers (CREs) worked with them in advance of their peak time frames to test the infrastructure for performance, scaling, and fault tolerance.

“Google CRE and services teams collaborated with us as we ran drills and exercises during each phase of preparation for peak time frames,” Ratnakar said. “As we continued to understand better how to scale, monitor, and support our applications in GCP and we are pleased that we worked with the CRE team as partners on monitoring services, alerting teams, and triaging work.”

Explainer

Thinking of a Multicloud Journey? Here’s What Our Experts Want You to Consider

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Are you thinking of kickstarting a multicloud journey? We have complied what Google Cloud's experts have to say on the do's and dont's while evaluating your organization's multicloud aspirations for value generation across processes and business.

Do you want to fire up a bunch of techies? Talk about multicloud! There is no shortage of opinions. I figured we should tackle this hot topic head-on, so I recently talked to four smart folks—Corey Quinn of Duckbill Group, Armon Dadgar of Hashicorp, Tammy Bryant Butow of Gremlin, and James Watters of VMware—about what multicloud is all about, key considerations, and why you should (or shouldn’t!) do it.

Five important insights came out of these discussions. If you’re on a multicloud journey or considering one, keep reading.

Do: Choose to do multicloud for the right reasons

Don’t do multicloud because Gartner says so, implores Corey Quinn. Before embarking on a multicloud, define a “why” focused on business value journey, says Armon Dadger. For example, you might want to use services from each public cloud because of their differentiated services, according to Tammy Bryant Butow. Armon also calls out regulatory reasons, existing business relationships, and accommodating mergers and acquisitions. On the topic of M&A, Corey points out that if you acquire a company that uses another cloud, it’s usually expensive and difficult to consolidate. It can be smarter to stay put.

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

Don’t: Over-engineer for workload or data portability

Thinking that you’ll build a system that moves seamlessly among the various cloud providers? Hold up, says our group of experts. Armon points out that aspects of your toolchain or architecture may be multicloud—think of some of your workflows or global network routing—but that shifting workloads or data is far from simple. Corey says that trying to engineer for “write once, run anywhere” can slow you down, and ignores the inherent uniqueness that’s part of each platform. Specifically, Corey calls out the per-cloud stickiness of identity management, security features, and even network functionality. And data gravity is still a thing, says James, that causes some to dismiss multicloud outright.

If you’re using multiple public clouds, you take advantage of the distinct value each offers, Armon says. Use native cloud services where possible so that you see the benefits from useful innovations, built-in resilience, and baked-in best practices. The value from that cloud-infused workload may outweigh the benefits of seamless portability.

https://youtube.com/watch?v=B1VH56_L8f8%3Fenablejsapi%3D1%26

Do: Recognize different stakeholder interests and needs

James smartly points out that many multicloud debates happen because people are arguing from different perspectives. Context matters. If you’re an infrastructure engineer who invests heavily in a given cloud’s identity and access management model, multicloud looks tricky. Or if you’re a data engineer with petabytes of data homed in a particular cloud, multicloud may look unrealistic. James highlights that many developers default to multicloud because their local tools—where all the work happens—are multicloud. A developer’s IDE and preferred code framework(s) aren’t tied to any given cloud. Be aware that groups within your organization will come at multicloud from distinct directions. And this may impact your approach!

https://youtube.com/watch?v=I9sqXDqkKBM%3Fenablejsapi%3D1%26

Don’t: Go it alone

Corey talks about the importance of asking others what worked, and what didn’t. Tammy offers her best practices around sharing results from experiments. It’s about sharing knowledge and tapping into it for community benefit. Others have probably tried what you’re trying, and can help you avoid common pitfalls. If you’ve just made an architectural choice that didn’t work out, share it, and help others avoid the pain. 

Read research from analysts, go to conferences or watch videos to observe case studies, and join online communities that offer a safe place to share mistakes and learn from others.

https://youtube.com/watch?v=mrSb5vqOfuI%3Fenablejsapi%3D1%26

Do: Experiment first using techniques like multi-region deployments

If you think you can operate systems across clouds, how about you first try doing it across regions in a specific cloud, suggests Corey. Getting a system to properly work across cloud regions isn’t trivial, he says, and that experience can help you uncover where you have architectural or operational constraints that will be even worse across cloud providers.

This is great guidance if your multicloud aspirations involve using multiple clouds to power one application—versus the more standard definition of multicloud where you use different clouds for different applications—but can also surface issues in your support process or toolchain that fail when faced with distributed systems. Start with muti-region deployments and chaos engineering experiments before aggressively jumping into multicloud architectures.

The Google Cloud take

Do the things above. It’s great advice. I’ll add three more things that we’ve learned from our customers.

  1. Don’t fear multicloud. You’re already doing it. You don’t single-source everything. As Corey mentioned, you probably already have one cloud for productivity tools, another for source code, another for cloud infrastructure. You’ll use software and application services from a mix of providers for a single app. You have that experience in your team and have been doing that for decades. What people do rightly worry about is using more than one infrastructure service beneath an application, as that can introduce latency, security, and logistical hurdles. Make sure you know which model your team is considering.
  2. Embrace the right foundational components, including Kubernetes. Will everything run on Kubernetes? Of course not. Don’t try to do that. But it also represents the closest thing we have to a multicloud API. Companies are using Kubernetes to stripe a consistent experience across clouds. And this isn’t just to orchestrate containers, but also to manage infrastructure and cloud-native services. Also, consider where you need other fundamental consistency across clouds, including areas like provisioning and identity federation.
  3. Use Google Cloud as your anchor. Here’s a fundamental question you have to decide for yourself: Are you going to bring your on-premises technology and practices to the cloud, or bring cloud technology and practices on-prem? We sincerely believe in the latter. Anchor to where you’re trying to get to. We offer Anthos as a way to build and run distributed Kubernetes fleets in Google Cloud and across clouds. By using a cloud-based backplane instead of an on-prem one, you’re offloading toil, leveraging managed services for scale and security, and introducing modern practices to the rest of your team.

We learned a lot about multicloud through these discussions, and it seems like others did too. That’s why we’re going to do a second round of interviews with a new crop of experts so that we can keep digging deeper into this topic. Stay tuned!

Blog

End Security Risks with the Unattended Projects Recommender Feature

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Google Cloud's Unattended Project Recommender in the Active Assist helps organizations identify abandoned projects based on API and networking activity, billing, usage of cloud services, and other signals. Learn how!

In fast-moving organizations, it’s not uncommon for cloud resources, including entire projects, to occasionally be forgotten about. Not only such unattended resources can be difficult to identify, but they also tend to create a lot of headaches for product teams down the road, including unnecessary waste and security risks. 

To help you prune your idle cloud resources, we’re excited to introduce Unattended Project Recommender. It’s a new feature of Active Assist that provides you with a one-stop shop for discovering, reclaiming, and shutting down unattended projects. With actionable and automatic recommendations, you no longer have to worry about wasting money or mitigating security risks presented by your idle resources. Unattended Project Recommender uses machine learning to identify, with a high degree of confidence, projects that are likely abandoned based on API and networking activity, billing, usage of cloud services, and other signals. This feature is available via the Recommender API today, making it easy for you to integrate with your company’s existing workflow management and communication tools, or export results to a BigQuery table for custom analysis.

Thousands of projects can be unattended in large organizations, presenting major security risks

Your cloud projects can go abandoned or unattended for a number of reasons — ranging from a test environment that’s no longer needed, to project cancellation, to project owner switching jobs, and more. Not only can such projects contribute to your cloud bill (waste) but they may contain security issues such as open firewalls or privileged service account keys that attackers can exploit to get a hold of your cloud resources for cryptocurrency mining or, worse, compromise your company’s sensitive data. These security risks tend to grow over time because the latest best practices and patches are usually not applied to unattended projects. 

We experience this issue here at Google, too… In fact, it has been on Google’s internal security team’s radar for some time now, so we joined forces and looked into this problem together, starting with our very own “google.com” organization cloud projects. We quickly found some projects that were unattended, but remediating this issue was easier said than done due to challenges in several areas:

  • Detection: With lots of signals available to you via sources like Cloud Monitoring, what are the right ones you should look at (e.g. API, networking, user activity)? How can you tell the difference between an unattended project and a project that has a low level of activity by design (e.g. a “shell” project that holds an auth token)?
  • Remediation: Once you have identified a project that seems abandoned, how do you go about ensuring that it’s indeed an unattended project? How do you reduce the risk of deleting something that might be essential to a production workload, causing irreversible data loss? How do you solve this at the scale of your entire organization, beyond a one-time cleanup? 

Over the course of 2021 we built and tested a Google-internal prototype first, cleaning up many of our internal unattended projects, and then worked with a number of Google Cloud customers to build and tune this feature based on real-life data (thank you to all of our early adopters for working with us and your generous feedback that helped us shape this feature!) It was not uncommon for us to come across organizations with thousands of unattended projects, and we’re very excited to bring Unattended Project Recommender to all customers, in public preview.

Discovering and acting on unattended project recommendations

Unattended Project Recommender analyzes usage activity across all projects under your organization, including the following data:

  • API activity (e.g. service accounts with authentication activity, API calls consumed)
  • Networking activity (ingress and egress)
  • Billing activity (e.g. services with billable usage)
  • User activity (e.g. active project owners)
  • Cloud services usage (e.g. number of active VMs, BigQuery jobs, storage requests)

Based on these signals, it can generate recommendations to clean up projects that have low usage activity (where “low usage” is defined using a machine learning model that ranks projects in your organization by level of usage), or recommendations to reclaim projects that have high usage activity but no active project owners. Here’s what an example post-processed summary list of recommendations can look like for the “foobar” organization that has 3 projects:

  Project ID: demo-project-307815
Recommendation: CLEANUP_PROJECT

Project ID: new-project
Recommendation: N/A

Project ID: bobs-playground-project
Recommendation: RECLAIM_PROJECT

In addition to the recommendations, you can also examine the underlying project activity insights that the recommendations are based upon. The insights provide additional information that can be useful for integration with your organization’s existing workflows and automation (e.g. send an auto-generated email or chat message to project owners based on the list provided by the owners field). Here’s an example insight payload:

  content:
  activeAppengineInstanceDailyCount: 0
  activeCloudsqlInstanceDailyCount: 0
  activeGceInstanceDailyCount: 3
  activeServiceAccountDailyCount: 1
  apiClientDailyCount: 18922           // Daily average API calls produced
  bigqueryInflightJobDailyCount: 0
  bigqueryInflightQueryDailyCount: 0
  bigqueryStorageDailyBytes: 0
  bigqueryTableDailyCount: 0
  consumedApiDailyCount: 0             // Daily average API calls consumed
  datastoreApiDailyCount: 0
  gcsObjectDailyCount: 11
  gcsRequestDailyCount: 0
  gcsStorageDailyBytes: 2663548
  hasActiveOauthTokens: false          // OAuth tokens used in the last 180 days
  hasBillingAccount: true
  numActiveUserOwners: 1
  owners:                              // List of project owners
  - activeOnProject: false
    member: user:user1@example.com
  - activeOnProject: true
    member: user:user2@example.com
  serviceWithBillableUsage:
  – Cloud Storage
  - Compute Engine
  vpcEgressDailyBytes: 264456938       // Daily average VPC egress bytes
  vpcIngressDailyBytes: 392435047      // Daily average VPC ingress bytes
  usagePercentile: 20                  // Level of usage relative to other projects

GCP projects are used in many different ways and for many different purposes. In case you get a recommendation to delete a project that’s being used in a way that’s out of the scope for this feature, you can dismiss the recommendation and it will stop showing up for the given project. 

Restoring deleted projects

When you choose to shut down a project using the projects.delete() method, it gets marked for deletion. After a project is marked for deletion, it becomes unusable, all resources within that project are shut down, and a 30-day wait period for the project and all of its data to get fully deleted begins.

In case a useful project is accidentally shut down, you have the option to restore the project within that 30-day wait period. Since restoring allows you to recover most but not necessarily all of your project data and resources, we recommend carefully examining the utilization insights associated with a project and considering any additional utilization signals that may not be captured by the Unattended Project Recommender before taking the cleanup action.

Early customer success stories

A number of enterprise customers are already using Unattended Project Recommender to keep their organizations clean of unattended projects and resources.

Decathlon, a French sporting goods retailer, is excited for the insight Unattended Project Recommender will bring to their environment, and are already deploying it as a part of their latest cloud security initiatives.

“After a thorough test of this feature and the validation of our CISO, we ended up deleting our first 775 projects, and no one complained! A great help to improve our security. The next step for us will be to operationalize it at scale, and implement a company wide policy for unattended resource management.” —Adeline Villette, Cloud Security Officer

For Veolia, one of the world’s largest water, waste and energy management companies, not only does this feature reduce security risks and waste, but also helps drive cultural shift and alignment with its ecological transformation strategy.

“This feature allows us to reduce our costs and security debt on assets that are no longer in use, and is also fully in line with Veolia’s philosophy of limiting its carbon footprint. After having tested Unattended Project Recommender on more than 3,000 projects throughout our organization, we are looking to bring it as proactive alerts to our project owners at scale.”Thomas Meriadec, Product Manager

Box, a secure cloud content management provider, views it as a foundation for building a repeatable process to remediate unused resources.

“Unattended Project Recommender is a great fit for us. It gives us a unified view of project usage across our entire organization and enables us to address security risks of legacy projects in a systematic and organized manner, ensuring an even safer environment.” —Matt Bowes, Staff Security Engineer

Getting started with the Unattended Project Recommender

To help you get started, we’ve prepared a Cloud Shell tutorial (source code) that you can use to find unattended project recommendations within your own Projects/Folders/Organization. Click this button to clone the tutorial from GitHub and run in your Cloud Shell environment:

google cloud shell.jpg

As you can see, listing recommendations for your projects only takes a few clicks with the tutorial (special thanks to Lanre Ogunmola, Security & Compliance Specialist, for making this look so easy)! For additional detail on using the gcloud CLI or API to discover unattended project recommendations, please refer to the documentation page.

You can also automatically export all recommendations from your Organization to BigQuery and then investigate the recommendations with DataStudio or Looker, or use Connected Sheets that let you use Google Workspace Sheets to interact with the data stored in BigQuery without having to write SQL queries.

As with any other Recommender, you can choose to opt out of data processing at any time by disabling the appropriate data groups in the Transparency & control tab under Privacy & Security settings.

We hope that you can leverage Unattended Project Recommender to improve your cloud security posture and reduce cost, and can’t wait to hear your feedback and thoughts about this feature! Please feel free to reach us at active-assist-feedback@google.com and we also invite you to sign up for our Active Assist Trusted Tester Group if you would like to get early access to the newest features as they are developed.

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Google Cloud Leads the Landscape for Unstructured Data Security Platform: Forrester

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Google Cloud has led the frontline for helping move sensitive data to the cloud and build customers' trust. Read more from The Forrester Wave™: Unstructured Data Security Platforms, Q2 2021 report to learn why Google Cloud leads this landscape.

As organizations expand their use of cloud computing services, more of their sensitive data inevitably moves to and lives in the cloud. Much of this sensitive data is unstructured and can be challenging to secure. Despite this potential challenge, the usefulness of cloud for data storage and processing is too big for most organizations to ignore and has in turn led to data sprawl, where their sensitive data is spread over many resources, both in the cloud and on-premise. Addressing data sprawl requires solutions that can discover, manage, and secure sensitive data, especially unstructured data, as it spreads.

To help organizations confidently move their sensitive data to the cloud, Google Cloud works diligently to earn and maintain customer trust. Control and transparency are pillars of our approach to offering a trusted cloud. Therefore, we’ve been expanding our capabilities to act on unstructured data as sprawl increases.

Given the importance of these capabilities to our strategy, we are happy to announce today that Forrester Research has named Google Cloud a Leader in The Forrester Wave™: Unstructured Data Security Platforms, Q2 2021 report, and rated Google Cloud highest in the current offering category among the providers evaluated.

gcp forrester security.jpg

The report evaluates the 11 most significant providers with platform solutions to secure and protect unstructured data, spanning from cloud providers to data security-focused vendors. The report notes that “Google offers breadth and depth with built-in data security in the cloud. Google Cloud Platform, Google Workspace, and BeyondCorp Enterprise have underlying data security products and features for protecting customer data.”

Google Cloud tools focused on protecting unstructured data were developed and battle-tested internally at Google to alleviate some of our own data security challenges. This brings the best of Google security to the organizations utilizing Google Cloud and our security tools. The report highlights that “Google productizes capabilities originally developed to secure its own business, and brings a disciplined approach to product enhancements for enterprise requirements. It serves a wide range of enterprise and mid-market, with a focus on emphasizing data protection needs by industry. ”

Google Cloud’s data security strategy focuses on meeting customers wherever they are in their cloud migration journey. The report highlights that “Google further enables a Zero Trust approach with third-party integrations through its BeyondCorp Alliance of partners in device management, endpoint security and gateways.”

Google Cloud received the highest possible score in sixteen criteria, in total receiving the most 5 out of 5 ratings among all vendors assessed. These criteria include: Data Intelligence, Access Control, Deletion, Obfuscation-Scope, Obfuscation-Key Management, Deployment, Security and Risk, APIs and Integration, Data Security Platform Vision, Data Security Execution Roadmap, Performance, Planned Enhancements, Zero Trust Enabling Partner Ecosystem, Diversity, Equity and Inclusion, Installed Base, and Revenue. 

Notably, Google Cloud received the highest possible score in the Obfuscation criteria. Obfuscation can help protect sensitive data, like personally identifiable information (PII), which is critical to many enterprise workflows. Cloud DLP helps customers inspect and mask this sensitive data with techniques like redaction, bucketing, and tokenization, which help strike the balance between risk and utility. This is especially crucial when dealing with unstructured or free-text workloads, in which it can be challenging to know what data to redact. More than 150 detectors combine to power Cloud DLP’s masking, which can be deployed in data migrations and business workloads like real-time data collection and processing. For Obfuscation specifically, the report mentioned that Google “takes a broad view of DLP, which includes in-line redaction of sensitive elements in unstructured data and DLP APIs that extend support to additional data types like images or other media.”

We are honored to be a Leader in The Forrester Wave™ Unstructured Data Security Platforms Q2 2021 report, and look forward to continuing to innovate and partner with you on ways to make your digital transformation journey safer as we work to become your most trusted Cloud.

A copy of the full report can be viewed here.

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Case Study

How McKesson Gains Insights by Running SAP on Google Cloud

McKesson, a 185-yeal old, $200 billion, Fortune 6 pharmaceuticals and health information technology company, with over 80,000 employees migrated their SAP solution to Google Cloud for advanced healthcare analytics. With changing consumer expectations, the company needed to change its architecture to be able to better serve its customers. And the

Explainer

Driving Business Transformation in Manufacturing, Industrial, and Transportation Using Google Cloud and AI/ML

Google Cloud partners closely with manufacturing, industrial, and transportation organizations to drive business transformation. In this video, Mandeep Waraich, Head of Product - Industrial AI, Google Cloud, shares customer stories as well as Google Cloud’s differentiated AI products and solutions. Waraich covers the current state of automation and industrial efficiency

Case Study

Vodafone Leverages Google Cloud to Aid COVID-19 Frontline with Anonymized Insights on Population Mobility

Editor’s note: When Europe’s largest mobile communications company, Vodafone, was asked by the European Commission to help understand population movement across the European Union and the UK to help fight COVID-19, it was able to provide anonymized mobile network-based insights to answer the call. Here’s how Vodafone, with the support

Blog

Melbourne Joins Google’s 26 Cloud Regions

We opened our Sydney cloud region in 2017 and, since then, we have continued to invest and expand across Australia and New Zealand to support the digital future of organizations of all sizes. In Australia, Google Cloud supports almost A$3.2 billion in annual gross benefits to businesses and consumers. This includes A$686

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