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5:00 Minutes
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What is Dataflow?
What is Dataflow, and how can you use it for your data processing needs?
In this episode of Google Cloud Drawing Board, Priyanka Vergadia walks you through Dataflow, a serverless system for processing and enriching data, supporting both streaming and batch models.
Here’s what’s inside:
0:00 – 0:14 Video snapshot
0:15 – 0:57 What is Dataflow
0:58 – 2:23 How does Dataflow work
2:24 – 3:34 How to use Dataflow
3:35 – 3:58 Dataflow security
3:58 – 4:24 What does it cost to use Dataflow
4:25 – 4:55 Dataflow use cases
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1:15 Minutes
The most insightful time you'll spend today!
An Indian Example of How to Really Up Your Customer Experience Game and Increase Conversion Rates With AI
How about selfie analysis of users to recommend them the right lipstick color?
That’s just one of the many ideas folks at Purplle.com came up with to improve the buying experience of Indian consumers.
And without the power of Google Cloud, it would probably have remained just that…an idea.
But today, thanks to Google Cloud, “Nothing seems impossible,” says Suyash Katyayani, CTO, Purplle.
Purplle.com is an online e-commerce company in India and one of the pioneers in creating a digitally-native beauty brands in India.
“The beauty industry is so data intensive that we needed to have a strong data strategy and we were looking out for solutions which would enable us to have a strong data pipeline and a strong data warehousing solution,” says Katyayani.
That’s when it turned to Google Cloud.
Additionally, Purplle.com, says Katyayani, does not have to worry about at what scale the company operates at because they have access to state-of-the-art infrastructure from Google Cloud available to them so that their developers can run experiments.
“The biggest plus point for us has been the agility that Google Cloud has added,” says Katyayani.
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2:30 Minutes
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Haaretz on Google Cloud Guarantees Faster, Reliable & Responsive Services to its Audience
Israeli centenarian newspaper, Haaretz relied on on-prem infrastructure to serve readers digitally. As the need for scalability, security and business intelligence grew alongside their readership, Haaretz was looking for more than just a cloud-based solution to replace their infrastructure. Inon Gershovitz, CTO, Haaretz takes us through the journey of recreating digital news experience, serving growing reader traffic and keeping up the editorial standards with Google Cloud.
Watch the video to hear from Haaretz’ leaders on delivering personalized content to readers with Google Cloud solutions!
11 Google Cloud Analytics Tools, Each Explained Simply in Under 2 Minutes

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22:00 Minutes
The most insightful time you'll spend today!
Need a quick overview of Google Cloud analytics technologies? Quickly learn these 11 Google Cloud products—each explained in under two minutes.
BigQuery in a minute
Storing and querying massive datasets can be time consuming and expensive without the right infrastructure. This video gives you an overview of BigQuery, Google’s fully-managed data warehouse. Watch to learn how to ingest, store, analyze, and visualize big data with ease.
Firestore in a minute
Cloud Firestore is a NoSQL document database that lets you easily store, sync, and query data for your mobile and web apps, at global scale. In this video, learn how use Firestore and discover features that simplify app development without compromising security.
Cloud Spanner in a minute
Cloud Spanner is a fully managed relational database with unlimited scale, strong consistency, and up to 99.999% availability. In this video, you’ll learn how Cloud Spanner can help you create time-sensitive, mission critical applications at scale.
Cloud SQL in a minute
Cloud SQL is a fully-managed database service that helps you set up, maintain, manage, and administer your relational databases on Google Cloud. In this video you’ll learn how Cloud SQL can help you with time-consuming tasks such as patches updates, replicas, and backups so you can focus on designing your application.
Memorystore in a minute
Memorystore is a fully managed and highly available in-memory service for Google Cloud applications. This tool can automate complex tasks, while providing top-notch security by integrating IAM protocols without increasing latency. Watch to learn what Memorystore is and what it can do to help in your developer projects.
Bigtable in a minute
Cloud Bigtable is a fully managed, scalable NoSQL database service for large analytical and operational workloads. In this video, you’ll learn what Bigtable is and how this key-value store supports high read and write throughput, while maintaining low latency.
BigQuery ML in a minute
BigQuery ML lets you create and execute machine learning models in BigQuery by using standard SQL queries. In this video, learn how you can use BigQuery ML for your machine learning projects.
Dataflow in a minute
Dataflow is a fully managed streaming analytics service that minimizes latency, processing time, and cost through autoscaling and batch processing. In this video, learn how it can be used to deploy batch and streaming data processing pipelines.
Cloud Pub/Sub in a minute
Cloud Pub/Sub is an asynchronous messaging service that decouples services that produce events from services that process events. In this video, you’ll learn how you can use it for message storage, real-time message delivery, and much more, while still providing consistent performance at scale and high availability.
Dataproc in a minute
Dataproc is a managed service that lets you take advantage of open source data tools like Apache Spark, Flink and Presto for batch processing, SQL, streaming, and machine learning. In this video, you’ll learn what Dataproc is and how you can use it to simplify data and analytics processing.
Data Fusion in a minute
Cloud Data Fusion is a fully managed, cloud-native, enterprise data integration service for quickly building and managing data pipelines. In this video, you’ll learn how Cloud Data Fusion can help you build smarter data marts, data lakes, and data warehouses.
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2:15 Minutes
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The True Story of How HotStar Broke a World-Record–Thanks to Firebase and Google BigQuery
Hotstar, India’s largest video streaming platform with 150 million monthly active users around the world, provides live-streaming of TV shows, movies, sports, and news on the go.
By using a combination of Firebase products together, Hotstar safely rolled out new features to its watch screen during a major live-streaming event without disrupting users, sacrificing stability, or releasing a new build. They also used Firebase with BigQuery to analyze their event data and reduce app startup time.
“We have an ambitious mission, but our engineering team is only a fraction of the size of most of our competitors. But we are still keeping up, and we are doing it with the help of Firebase,” says Ayushi Gupta, Android Engineer, Hotstar.
Google Cloud Helps Northwell Health to Boost Caregiver Productivity and Access to Right Care Using AI

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2:00 Minutes
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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.
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