Scope for Tech Adoption and Advancements in Healthcare are Still High: Google Cloud Research
5706
Of your peers have already read this article.
3:00 Minutes
The most insightful time you'll spend today!
Since the start of the COVID-19 pandemic, there’s been a rapid acceleration of digital transformation across the entire healthcare industry. Telehealth has become a more mainstream and safe way for patients and caregivers to connect. Machine learning modeling has helped speed up innovation and drug discovery. And new levels of integration and data portability have helped enable greater vaccine availability and equitable access to those who need it.
Data has been at the crux of this digital transformation — helping people stay healthy, accelerating life sciences research and delivering more personalized and equitable care. We recently unveiled partial results from our research with The Harris Poll, which revealed that nearly all physicians (95%) believe increased data interoperability will ultimately help improve patient outcomes. Today, we’re unveiling the second part of that research.
In February 2020, we commissioned The Harris Poll to survey 300 physicians in the U.S. about their biggest pain points — this was just before the COVID-19 pandemic strained the entire healthcare system and made us all hyper-aware of the risks we take in going to the hospital. In June 2021, we followed-up with those same questions and more. What it unveiled was just how much COVID-19 reshaped technology’s role in the healthcare field and how it’s changing day-to-day operations for physicians.
Here are some of the highlights:
Healthcare organizations accelerated technological upgrades over the course of the pandemic. After a year shaped primarily by the COVID-19 pandemic, use of telehealth saw substantial YOY growth, jumping nearly threefold from 32% in February 2020 to 90% this year. Forty-five percent of physicians say the COVID-19 pandemic accelerated the pace of their organization’s adoption of technology. In fact, more than 3 in 5 physicians (62%) say the pandemic has forced their healthcare organization to make technology upgrades that normally would have taken years. For example, 48% of physicians would like to have access to telehealth capabilities in the next five years. Before the COVID-19 pandemic, about half of physicians (53%) say their healthcare organization’s approach to the adoption of technology would best be described as “neutral” (i.e., willing to try new technologies only if they have been in the market for awhile or others have tried and recommended them).
Despite the technological leaps this year, most physicians still believe the industry lags behind in technology adoption but recognize the opportunity for technological support and advancement. The majority of physicians don’t view the healthcare industry as a leader when it comes to digital adoption. More than half of physicians describe the healthcare industry as lagging behind the gaming (64%), telecommunications (56%), and financial services industries (53%). However, the healthcare industry is not seen to be trailing as much as it was last year behind retail (54% in 2020; 44% in 2021); hospitality and travel (53% in 2020; 43% in 2021); and the public sector (39% in 2020; 26% in 2021).
Better interoperability alleviates physician burnout, improves health outcomes and speeds up diagnoses. The majority of physicians say increased data interoperability will cut the time to diagnosis for patients significantly (86%) and will ultimately help improve patient outcomes (95%.) In addition to better patient experiences and outcomes, more than half of physicians (54%) believe increased access to data via technology has had a positive impact on their healthcare organization overall. A majority believe that technology can alleviate the likelihood of physician “burn-out” (57%) and that efficient tools help decrease friction and stress (84%). And, as a result, 6 in 10 physicians say access to better technology and clinical data systems would allow them to have better work/life balance (60%) and that better access to/more complete patient data would reduce administrative burdens (61%). It is therefore not surprising that nearly 9 in 10 physicians (89%) say they are increasingly looking for ways to bring together all patient data into a single place for a more complete view of health.
Familiarity with new Department of Health and Human Services (DHHS) interoperability rules grows, and many physicians are in favor. Most physicians (74%) say they have at least heard of the new DHHS rules (launched in 2019) to improve the interoperability of electronic health information. This is a clear rise from 2020 (64%), but deeper knowledge is fairly low. Only 30% of physicians say they are somewhat or very familiar with the new rules (though, again, this is a rise from 2020, when only 18% said they were very/somewhat familiar). Similar to in 2020, among those who have heard of the new rules, nearly half are in favor (48% in 2021; 45% in 2020) but a similar proportion remain unsure (46% in 2021; 50% in 2020). And like in 2020, by far the top potential benefit of the rules is thought to be forcing EHRs to be more interoperable with other systems (70%).
Google was founded on the idea that bringing more information to more people improves lives on a vast scale. In healthcare, that means creating tools and solutions that make data available in real time to help streamline operations and improve quality of care and patient outcomes. For example, our recently announced Healthcare Data Engine makes it easier for healthcare and life sciences leaders to make smart real-time decisions through clinical, operational, & groundbreaking scientific insights. To find out more about the Healthcare Data Engine, click here.
Survey methodology: The 2021 survey was conducted online within the United States by The Harris Poll on behalf of Google Cloud from June 9 – 29, 2021 among 303 physicians who specialize in Family Practice, General Practice, or Internal Medicine, who treat patients, and are duly licensed in the state they practice. The 2020 survey was conducted from February 18 – 25, 2020 among 300 physicians who specialize in Family Practice, General Practice, or Internal Medicine, who treat patients, and are duly licensed in the state they practice. Physicians practicing in Vermont were excluded from the research. This online survey is not based on a probability sample and therefore no estimate of theoretical sampling error can be calculated. For complete survey methodology, including weighting variables and subgroup sample sizes, please contact press@google.com.
6 Tips for Stress-Free Google Cloud Billing
1327
Of your peers have already read this article.
1:30 Minutes
The most insightful time you'll spend today!
If you took one look at the title of this blog and thought, “just show me how, because I already know a million reasons why I’m stressed about billing things” then check out the interactive tutorial right here.
For everyone else, read on, because we’ll walk through some common sense tips, and a few step-by-step tutorials for all things billing related. If you’ve ever wished you could sit down with someone from Google Cloud, and walk through your bill, the console, and your options — you’re in the right place! Consider this Cloud Billing 101 – an intro level course that’ll get you started on the right foot.
6 simple tips to manage your Google Cloud billing accounts:
- Get to know your billing statement and console: Knowledge is power, after all. Take a tour of the billing console so you can better understand your options, along with what’s included in your monthly bill and the different components.
- Set up authorized users, alerts and budgets: Make sure anyone who needs to have access to payment settings is authorized. Allocate budgets for projects, and get notifications when your usage or spending exceeds a certain amount so you can take action as needed.
- Use cost-saving tools: We’ve got a range of tools and services to help you save money, like Committed Use Discounts, and even Recommenders for actionable, AI-powered intelligent recommendations around your cost trends and product usage.
- Optimize your resources: Use the Google Cloud Resource Manager to see how your resources are being used and identify areas for optimization, temporarily suspend, or even shut down unused projects.
- Review your billing history with reporting and data visualization: Regularly check your billing history with reports to help track your spending, identify any trends or patterns, and even anticipate future costs. You can even export your data to BigQuery for detailed analysis, or use a tool like Google Data Studio to visualize your data.
- Use the pricing calculator: Estimate your monthly costs and make informed decisions with the Google Cloud pricing calculator. It can help you get a ballpark figure for your usage, and determine if your use case fits within cost-free parameters.
I hope these common sense pointers and tutorials empower you to effectively manage your Google Cloud billing and stay on top of your spending. Get started right now by managing your billing methods and payment settings in this 5-minute tutorial, and then take a tour of the billing console to get familiar with your setup.
Dassana: Choosing Google Workspace and Google Cloud to accelerate growth and reach goals
3038
Of your peers have already read this article.
2:30 Minutes
The most insightful time you'll spend today!
When Dassana co-founders Gaurav Kumar and Parth Shah, formerly founder and founding engineer at RedLock (now Prisma Cloud by Palo Alto Networks), set out on a new startup journey in 2020, they knew exactly where to start: sign up for Google Workspace.
“Every startup I’ve been at, we used Google Workspace,” said Kumar. “We’ve been using it for so long, and we’re all used to it. It’s like drinking water—you don’t think about it.”
“We’re big on user experience,” explained Shah. “Google is one of the few companies out there that is all about building the right kind of user experience that’s easy to follow. The sharing capabilities are amazing and, of course, easy to use. Docs, Sheets, Slides—we use all of it.”
Dassana, which emerged from stealth with $5 million in seed funding earlier this year, is a next-generation security data lake. It provides a holistic picture of security risk across an organization and its business units by ingesting large volumes of structured data in a schema-less fashion. Their success is a great testament to why startups are choosing not only Google Workspace, but a range of Google Cloud products.
Though the Dassana team was comfortable with Workspace from the start, not all their early technology choices were the best fit for the company, and Google Cloud services became more crucial as the startup evolved. For example, the team opted to use Amazon Web Services (AWS) to start their cloud journey, but ultimately started to explore other cloud options when they decided to run their technology platform on Kubernetes.
“We started looking into which cloud platforms provide the best Kubernetes experience,” said Kumar. “Hands-down, Google Kubernetes Engine (GKE) had the best experience. If you look at product velocity and how GKE has evolved over time, from its early days to GKE Autopilot and all the features and other native integrations—nothing even comes close.”
In particular, Kumar noted that the native integration between Google Workspace and GKE was particularly unique and useful. “When I go to Google Workspace and then go to GKE, my identity is already there,” he said. “I don’t have to integrate or manage anything. If I disable an account in Workspace, it’s also disabled on GKE.”
Another advantage is that GKE allows you to set up Google Groups to work with Kubernetes role-based access control (RBAC) for GKE clusters. This lets administrators maintain users and groups outside of GKE and assign RBAC permissions directly to Groups in Workspace without any extra engineering work or overhead management.
“I can actually use my Workspace identity to give granular controls to my GKE workloads. The integration of Google Groups in GKE and Kubernetes is a lifesaver. It’s saved us a lot of hassles,” said Kumar. Kumar also noted that the platform delivers better performance compared to other solutions thanks to the low latency of Google Cloud’s global network.
Like many startups, Dassana has found a powerful combination in Google Workspace and GKE on Google Cloud that lets them connect technologies, easily collaborate with their teams, and rapidly build their product. The team also recognizes the necessity of continued innovation, and is exploring additional Google Cloud products to help them accelerate their momentum. For example, Dassana plans to use the performance and scale of Cloud Storage buckets to store the company’s data. The team is also investigating how to save time by using Pub/Sub to integrate data directly from Google Workspace and other sources for security analytics.
To learn more about why startups like Dassana are choosing Google Workspace and Google Cloud to accelerate their growth and reach their goals, visit our startup solutions pages for Google Workspace and Google Cloud.
AWS to Google Cloud Translator: Which AWS Database Service Is Equal to Google Cloud Database?
6315
Of your peers have already read this article.
2:30 Minutes
The most insightful time you'll spend today!
There are multiple reasons a growing number of database administrators, enterprise architects, application developers and other technology practitioners are moving to Google Cloud’s various database services.
Some are being driven by missing features in offering from other providers such as AWS. In Gartner’s Magic Quadrant for Operational Database Management Systems, the research and advisory firm points out that, “AWS’s surveyed reference customers scored its overall product capabilities one standard deviation (STD) below the mean. Their responses identified missing features such as multiregion writes and autosharding.”
Others are moving to database services on Google Cloud Platform driven by a few benefits. According to Gartner, “Reference customers repeatedly commented on Google’s ease of use and implementation, reliability and integration (with other services and other systems). Reference customers scored Google a full STD above the mean for satisfaction with GCP’s pricing; it received the second-highest satisfaction score of any vendor in this Magic Quadrant.
If you are looking to leverage the power of Google Cloud database offerings—but were unsure of which database services comes closest to the service you are currently using, here’s a handy map to find your way.
Google Cloud Announces General Availability of BigQuery Row-level Security
6609
Of your peers have already read this article.
3:00 Minutes
The most insightful time you'll spend today!
Data security is an ongoing concern for anyone managing a data warehouse. Organizations need to control access to data, down to the granular level, for secure access to data both internally and externally. With the complexity of data platforms increasing day by day, it’s become even more critical to identify and monitor access to sensitive data. In many cases, sensitive data is co-mingled with non-sensitive data, and access restrictions to sensitive data need to be enabled based on factors like data location or presence of financial information. There may also be nuances where data is sensitive for some groups of users, while for others, it is not.
Today, we’re pleased to announce the general availability of BigQuery row-level security, which gives customers a way to control access to subsets of data in the same table for different groups of users. Row-level security (RLS) extends the principle of least privilege access and enables fine-grained access control policies in BigQuery tables. BigQuery currently supports access controls at the project-, dataset-, table- and column-level. Adding RLS to the portfolio of access controls now enables customers to filter and define access to specific rows in a table based on qualifying user conditions—providing much needed peace of mind for data professionals.
“Our digital transformation and migration of data to the cloud magnifies the business value we can extract from our information assets. However, granular data access control is essential to comply with international regulatory and contractual requirements. BigQuery row-level security helps us comply with data residency and export restrictions,” says Jarrett Garcia, Iron Mountain’s Enterprise Data Platform Senior Director. “It enables us to manage fine-grained access controls without replicating data. What used to take months for approval and access provisioning can now be done more efficiently and effectively. We are looking forward to implementing additional data security capabilities on the BigQuery roadmap to address other critical business use cases.”
How BigQuery row-level security works
Row-level security in BigQuery enables different user personas access to subsets of data in the same table. Customers who are currently using authorized views to enable these use cases can leverage RLS for ease of management. To express the concept of RLS, we have introduced a new entity in BigQuery called row access policy. Row access policies map a group of user principals to the rows that they can see, defined by a SQL filter predicate.
Secure logic rules created by data owners and administrators determines which user can see which rows through the creation of a row-level access policy. The row-level access policies created on a target table by administrators or data owners are applied when a query is run on the table. One table can have multiple policies applied to it.
Below is an example, where row-level access policies have been created to filter data based on users’ “region”.
In the illustrated scenario above, row-level access policies have been created to verify a querying user’s region and to give them access only to the subset of data relevant to that region. Access policies are granted to a grantee list which support all types of IAM principles such as individual users, groups, domains or service accounts. In this example, when a user queries the table, row-level access policies are evaluated to assess which, if any, policies are applicable to that user. The group ‘sales-apac’ is granted access to view a subset of rows where region = ‘APAC’ whereas the group ‘sales-us’ is granted access to view a subset of rows where the region = ’US’. Likewise, users in both groups will see rows in both regions, and users in neither group will not see any rows.
Row-level access policies can also be created using the SESSION_USER() function to restrict access only to rows that belong to the user running the query. If none of the row access policies are applicable to the querying user, the user will have no access to the data in the table.
When a user queries a table with a row-level access policy, BigQuery displays a banner notice indicating that their results may be filtered by a row-level access policy. This notice displays even if the user is a member of the `grantee_list`.
When to put BigQuery row-level security to work
Row-level access policies are useful when you have a need to limit access to data based on filter conditions. The row-access policies’ filter predicate supports arbitrary SQL, and is conceptually similar to the WHERE clause of a SQL query. Filter predicates support the SESSION_USER() function to restrict access only to rows that belong to the user running the query. If none of the row access policies are applicable to the querying user, the user will have no access to the data in the table. Currently, the column used for filtering must be in the table, but we anticipate adding support for subqueries in the filter expression, opening up access to use cases where data is filtered based on lookup tables and calculated values. Row-level access policies can be created, updated and dropped using DDL statements. You will be able to see the list of row-level access policies applied to a table using the BigQuery schema pane in the Cloud Console, which simplifies the management of policies per table, or by using the bq command-line tool.
Row-level security is compatible with other BigQuery security features, and can be used along with column-level security for further granularity. Since row-level access policies are applied on the source tables, any actions performed on the table will inherit the table’s associated access policies, to ensure access to secure data is protected. Row-level access policies are applicable to every method used to access BigQuery data (API, Views, etc).
Try it out
We’re always working to enhance BigQuery’s (and Google Cloud’s) data governance capabilities, to provide more controls around managing your data. With row-level security, we are adding deeper protections for your data. You can learn more about BigQuery row-level security in our documentation and best practices.
Recapping Google Cloud VMware Engine’s Latest Milestones
3467
Of your peers have already read this article.
3:00 Minutes
The most insightful time you'll spend today!
We’ve made several updates to Google Cloud VMware Engine in recent weeks—today’s post provides a recap of our latest milestones. Google Cloud VMware Engine delivers an enterprise-grade VMware stack running natively in Google Cloud. This cloud service is one of the fastest paths to the cloud for VMware workloads without making changes to existing applications or operating models across a variety of use-cases. These include rapid data center exit, application lift and shift, disaster recovery, virtual desktop infrastructure, or modernization at your own pace.
In fact, Mitel, a global provider of unified communications-as-a-service to 70 million business users across 100 countries, migrated 1,000 VMware instances to Google Cloud VMware Engine in less than 90 days and improved its monthly operational output four times.
In our last update, we focused on several innovative capabilities around networking, reach, and scale. Let us take a look at the highlights we released since our last installment.
Fast provisioning of a dedicated, intrinsically secure VMware private cloud
With Google Cloud VMware Engine, you can spin up a VMware private cloud in about 30 minutes. You can also scale your VMware-based infrastructure on-demand with dedicated hosts located in secure Google data centers. Let us look at what’s new:
Autoscale: The ability to elastically and programmatically manage infrastructure resources to align with business needs or what is called “right-sizing” is a core capability of an IaaS platform. With autoscale, Google Cloud VMware Engine users can leverage policy-driven automation to scale the nodes needed to meet the compute demands of the VMware infrastructure.
Autoscale:
- Addresses seasonal spikes in demand, gradual increases of utilization, or new projects being onboarded or expanded due to disaster recovery events.
- Analyzes the CPU, memory, and storage utilization to give you the controls to scale Google Cloud VMware Engine nodes up or down.
- Ensures that storage consumption does not exceed the recommended limits for maintaining the Google Cloud VMware Engine service-level agreement.
- Reduces overhead on IT teams by automating capacity monitoring and enabling sufficient availability of resources based on thresholds. Note that safeguards for maintaining minimum capacity and maximum capacity can be configured to ensure there are boundaries to the automation.
Learn how to set up Autoscale.
Mumbai region availability
Google Cloud VMware Engine is now available in the Mumbai region. This brings the availability of the service to 12 regions globally, enabling our multi-national and regional customers to leverage a VMware-compatible infrastructure-as-a-service platform on Google Cloud. For more details, please read the press release.
Enterprise-grade infrastructure
With 99.99% availability for a cluster in a single zone, fully dedicated 100 Gbps east-west networking with no oversubscription, and all nonvolatile memory express storage, Google Cloud VMware Engine provides the highest performance required for the most demanding workloads. Let us look at what’s new:
Preview – Google Cloud KMS integration: You already have the ability to bring your own keys to encrypt your vSAN datastores. With this new capability, organizations that want to eliminate the overhead of managing external key providers can leverage a Google managed key provider, using Cloud KMS. This brings increased flexibility in securing workloads and data by enabling vSAN encryption by default for newly instantiated VMware Private Clouds. This feature is currently in Preview.
HIPAA compliance: Since April, Google Cloud VMware Engine is Health Insurance Portability and Accountability Act (HIPAA) compliant. This opens the service up to healthcare organizations, that can now migrate and run their HIPAA-compliant VMware workloads in a fully compatible VMware Cloud Verified stack running natively in Google Cloud with Google Cloud VMware Engine, without changes or re-architecture to tools, processes, or applications. Read more in this blog.
NSX-T support for Active Directory: With NSX-T support for Active Directory, you can now leverage your on-premises Active Directory as one of the lightweight directory access protocol identity sources for user authentication into NSX-T manager. This extends the theme of being able to leverage your on-premises tools with Google Cloud VMware Engine. For more information, read the documentation on how to set up identity sources.
vSAN TRIM/UNMAP support: For space-efficiency, vSAN allows creating thin-provisioned disks that grow gradually as they are filled with data. However, files that are deleted within the guest operating system (OS) do not result in vSAN freeing up space allocated. To increase space efficiency, guest OS file systems have the ability to reclaim capacity that is no longer used, using TRIM/UNMAP commands. vSAN is fully aware of these commands that are sent from the guest OS and enables reclamation of previously allocated storage as free space. We have enabled TRIM/UNMAP for vSan by default in Google Cloud VMware Engine.
Simplicity in experience and operations
With Google Cloud VMware Engine, you only need to worry about your workloads—not patching, upgrading, and updating the solution layer, for fewer interoperability issues and infrastructure maintenance. IIn addition, we have pre-built service accounts to enable your third-party VMware-supported tools and solutions to work seamlessly in VMware Engine. Access to Google services privately over local connections is also natively supported, enabling enrichment of existing applications and modernization over time. Finally, this service brings the power of Google Cloud Virtual Private Cloud (VPC) design by natively providing multi-VPC, multi-region networking that’s unique. Let’s look at what’s new:
Dashboards for Day 2 operations: To speed up cloud transformation and enable efficiency, Google Cloud VMware Engine administrators can take advantage of Cloud Operations dashboards for the solution. In addition, administrators can create custom policies through cloud alerting and enable notifications via channels of their choice (SMS, email, Slack, and more). For more details on how to set up cloud monitoring, please refer to Setting up Cloud Monitoring.
For the latest updates, bookmark Google Cloud VMware Engine release notes.
Thanks to Manish Lohani, Product Management, Google Cloud; Nargis Sakhibova, Product Management, Google Cloud; and Wade Holmes, Solutions Management, Google Cloud; for their contributions to this blog post.
More Relevant Stories for Your Company
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
Explore Google Cloud’s Bi-monthly Technical Learning Series for Innovators in Public Sector
Cloud engineers face a constant barrage of new cloud services, products, and innovations. By late 2021, Google Cloud alone had released thousands of new features across hundreds of services. Couple this with other technologies and service releases, and it quickly becomes a herculean task for engineers to navigate, consume, and
Google Cloud Leads the Pack in Cloud Security: Forrester Research
As organizations continue to move workloads to public clouds, security professionals must protect the sensitive data and digital identities found in those workloads. Once wary of cloud adoption, many security professionals now believe that the native security capabilities of large public cloud platforms actually offer more affordable and superior security
Impact of Cloud FinOps on Your Business Can be Measured with Five Key Metrics!
Value of Establishing a Baseline for Metrics As organizations continue to leverage cloud investments to drive their business growth and top line revenue, business, finance, and technology executives need to become increasingly connected in their efforts to deliver strong business outcomes. More than ever before, executives need to quantify the
