As organizations continue to produce vast quantities of data, they increasingly need platforms that allow them to analyze, store, and extract meaningful insights from that data. And research from analyst firms like Gartner offer an important way for organizations to evaluate and compare cloud data warehouse providers.

Earlier this year, Gartner named Google a Leader in the 2019 Gartner Magic Quadrant for Data Management Solutions for Analytics (DMSA) (report available here). This evaluation covers Google Cloud’s core data analytics offerings, including BigQuery, a serverless, managed data warehouse, Cloud Dataproc, a managed Spark and Hadoop service, and Cloud Dataflow, which enables you to stream and batch-process your data. Here are a few takeaways:

Simplicity and speed

BigQuery’s performance permits complex queries on large-scale data sets to return in seconds, and a substantial number of BigQuery customers maintain data warehouses that store more than 50 terabytes (and a few customers now use more than 100 petabytes). More than half of these customers are loading data either continuously or many times per day. These customers value the ability to extract, transform, load, and analyze their data on a serverless platform, all without maintaining any underlying infrastructure.

A versatile serverless data warehouse

One of BigQuery’s major advantages is its ability to allow customers to address a wide variety of use cases—from a traditional data warehouse to data science. Over the past year, we’ve worked hard to introduce new features in BigQuery like data types for financial and monetary uses, BigQuery GIS for geospatial data, and machine learning capabilities through BigQuery ML. BigQuery’s continuous ingest capabilities make it suitable for an operational—or a real-time—serverless data warehouse.

An expanding ecosystem

With overall increased market adoption, our analytics offerings continue to benefit from a fast-growing partner ecosystem of service providers, and business intelligence (BI) and data integration vendors. In particular, in 2018 we expanded our partnerships with established industry providers, including Confluent, Dell Boomi, Informatica, Looker, Reltio, Tableau, and ThoughtSpot.

More and more organizations are finding value in Google Cloud’s serverless data warehouse and analytics offerings. If you’d like to learn more, you can download a complimentary copy of the Gartner Magic Quadrant for Data Management Solutions for Analytics on the Google site (requires an email address).

_{Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.}

Lung cancer is the leading cause of cancer death in the United States and like any cancer, early detection is crucial to survival. Screening at-risk populations is an important part of reducing mortality, and if concerning nodules are found on imaging, further testing may be required. Today, we’ll share how Northwell Health uses Google Cloud products such as Cloud Healthcare APIs and BigQuery to increase caregiver productivity and deliver better care for patients with findings that indicate potential development of lung cancer.

Northwell is New York’s largest healthcare provider

Northwell Health is New York’s largest healthcare provider with 23 hospitals and nearly 800 outpatient facilities. Northwell’s nearly 4,000 doctors care for millions of patients each year, and at this scale, there is an immense amount of healthcare data to manage. To better manage and leverage this data, Northwell Health partnered with Google Cloud starting in 2018.

Enabling caregivers to spend more time with patients

Nic Lorenzen, the lead developer of Northwell Emerging Technology and Innovation team, has a mission to put together data for caregivers in a way that makes sense. It is no secret that inefficient electronic health records systems have a negative impact on a physician’s ability to deliver quality care. Traditional EHRs have information distributed across many tabs, which forces caregivers to spend considerable time at the computer trying to find information. Moreover, speed of care matters. If care is delayed, patients may have to spend more time in the hospital and may suffer worse health outcomes.

To solve this problem, Nic’s team focused on giving caregivers the most relevant pieces of data at the right time by developing an intelligent clinician rounding app. The data needed to derive these insights can depend on the caregiver’s role–a nurse cares about different things than a cardiologist. This system aggregates multiple data sources, and provides patient-specific insights to caregivers.

This system would not have been possible before with traditional EHRs and data warehouses that have proprietary data models and rarely sync data in real time. Now with data easily accessible through Google Cloud’s Healthcare solutions, Nic’s team can deliver the right clinical information to the right people instantly. These days, Nic says, “instead of spending 75% of our time dealing with architecting the underlying platforms, we spend 75% of our time focused on  higher value use cases for clinicians and patients. Google Cloud’s Healthcare solutions have greatly improved our developer productivity and time to value.”

Caregivers have found this new system to be a game changer.Before the implementation of this system, caregivers would spend, on average, seven to nine minutes finding the data needed to make medical decisions for one patient. Now, that aggregated information is delivered to a caregiver’s mobile device in less than a second.

Ensuring patients get the right care with the power of AI

There are a number of reasons why patients might not get the care that they need. For example, patients today can go to multiple hospitals and clinics settings, and coordinating care across multiple facilities is complex. Regional hospitals and clinics have their own siloed view of their data, so pertinent information gathered by one clinic might not be seen by another. These gaps in clinical data lead to gaps in patient care.

When a patient gets radiologic imaging, they may have findings unrelated to the reason they initially got the imaging. For example, a chest CT for a car accident might reveal an incidental lung nodule that could be cancerous. Unfortunately, research shows that a large portion of patients do not get follow up for these incidental findings because it isn’t the primary reason why the patient is seeing a doctor. Moreover, social determinants of health are a factor that affects which patients receive follow-up care. Identifying these patients and providing the necessary follow up care prevents adverse events related to delayed detection of cancer.

With Cloud Healthcare solutions, Northwell built an AI model to identify these patients so that oncologists can appropriately follow up with patients who have findings suspicious for lung cancer. The AI model detects incidental pulmonary nodules in radiology reports so that doctors can then contact the patients that need follow-up care. Nic says his team was able to build this system in a week: “Google Cloud did a lot of heavy-lifting for us and allowed us to get to the AI applications much faster. It allowed us to build a platform that just works.” 

Healthcare systems can now rapidly generate healthcare insights with one end-to-end solution, Google Cloud Healthcare Data Engine. It builds on and extends the core capabilities of the Google Cloud Healthcare API to make healthcare data more immediately useful by enabling an interoperable, longitudinal record of patient data. Northwell Health uses Google Cloud as the core of their platform, enabling their developers to create solutions to the most pressing healthcare problems.

Special thanks to Kalyan Pamarthy, Product Management Lead on Cloud Healthcare and Natural Language APIs for contributing to this blog post.

When Google announced our plan to go beyond purchasing renewable power for 100% of our energy usage and operate on 24/7 carbon-free energy by 2030, we noted that achieving this goal will require new transaction structures, advancements in clean energy policy, and innovative new technologies. Today, we’re pleased to announce that one of these new technologies—a first-of-its-kind, next-generation geothermal project—will soon begin adding carbon-free energy to the electric grid that serves our data centers and infrastructure throughout Nevada, including our Cloud region in Las Vegas.  

Google and clean-energy startup Fervo have just signed the world’s first corporate agreement to develop a next-generation geothermal power project, which will provide an “always-on” carbon-free resource that can reduce our hourly reliance on fossil fuels. In 2022, Fervo will begin adding “firm” geothermal energy to the state’s electric grid system, where Google’s commitments already include one of the world’s largest corporate solar-plus-storage power purchase agreements. 

Importantly, this collaboration also sets the stage for next-generation geothermal to play a role as a firm and flexible carbon-free energy source that can increasingly replace carbon-emitting fossil fuels—especially when aided by policies that expand and improve electricity markets; incentivize deployment of innovative technologies; and increase investments in clean energy research, development, and demonstration (RD&D). 

Next-generation geothermal technology

Traditional geothermal already provides carbon-free baseload energy to a number of power grids. But because of cost and location constraints, it accounts for a very small percentage of global clean energy production. 

That’s one reason this new approach is so exciting; by using advanced drilling, fiber-optic sensing, and analytics techniques, next-generation geothermal can unlock an entirely new class of resource. And the US Department of Energy has found that with advancements in policy, technology, and procurement, geothermal energy could provide up to 120 GW of firm, flexible generation capacity in the US by 2050. 

As part of our agreement, Google is partnering with Fervo to develop AI and machine learning that could boost the productivity of next-generation geothermal and make it more effective at responding to demand, while also filling in the gaps left by variable renewable energy sources. Although this project is still in the early stages, it shows promise.

Using fiber-optic cables inside wells, Fervo can gather real-time data on flow, temperature, and performance of the geothermal resource. This data allows Fervo to identify precisely where the best resources exist, making it possible to control flow at various depths. Coupled with the AI and machine learning development outlined above, these capabilities can increase productivity and unlock flexible geothermal power in a range of new places. 

This won’t be the first time that Google is applying software solutions to clean energy applications: we’ve just announced an update to our carbon-intelligent computing program that helps us reduce emissions associated with running applications at Google data centers. And other forms of AI and machine learning are currently being used to increase the value of wind energy. 

Already this year, Google has taken significant strides toward sourcing 24/7 carbon-free energy for all our data centers, office campuses, and Cloud regions. On Earth Day, our CEO Sundar Pichai announced that for the first time, five of our global data center sites operated near or at 90% carbon-free energy in 2020. 

Not only does this Fervo project bring our data centers in Nevada closer to round-the-clock clean energy, but it also acts as a proof-of-concept to show how firm clean energy sources such as next-generation geothermal could eventually help replace carbon-emitting power sources around the world.

Global life science supply chains are lengthy and complex with many moving parts. One small disruption can create serious delays and affect your ability to deliver therapeutics for patients.

Supply chain disruptors

Over the last few years, healthcare organizations have encountered a range of obstacles, from both internal and external factors, that have resulted in supply networks failing to get drugs and medical devices to where they need to be on time. These obstacles include:

• Labor and supply shortages
• Rising material costs
• Raw material constraints
• Geo-political events
• Unpredictable weather

How do you overcome supply chain disruptors that are out of your control?

The intelligent healthcare supply chain

While many organizations have already implemented data-driven supply chains, organizations are still faced with the challenges of static, siloed, and different functional supply chain applications; limited data exchange with key trading partners across upstream and downstream operations; and the inability to effectively leverage relevant external data.

At Google Cloud, we believe the key to meaningful and effective change is a data-driven supply chain that allows you to achieve visibility, flexibility, and innovation.

Our solutions help you prepare for the unpredictable and enhance the value of your data. By unlocking AI-driven insights, you can strengthen distribution networks and optimize your workflows and supply chains to become more reliable, intelligent, and sustainable. Some of the business challenges we address include:

• Predicting demand with Vertex AI Forecast
• Visual inspection for quality and predictive maintenance with pre-built ML models
• Automating and optimizing pickup and delivery operations with Cloud Fleet Routing API
• Real time and holistic inventory visibility with Supply Chain Twin

Make sure you’re prepared for the unpredictable with real-time visibility over your distribution networks. Learn how you can harness the power of AI and analytics and gain actionable insights that enhance your supply chain.