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Modernize the Data Stack to Transform the Data Experience

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Explainer

Reinventing geospatial analytics as only Google can do: Intelligent platform

Geospatial analytics is undergoing a fundamental change with the application of cloud computing products. Every day, data analysts need to understand the geospatial impact on their data and GIS professionals are finding themselves constrained by legacy technology that can’t keep pace with increasing data volume.

Google Cloud’s geospatial analytics platform brings the full suite of Google’s Geo offerings to both sets of users to unblock workloads and free them from legacy capacity constraints.

Listen to Joe Bettridge, Consulting Lead, TELUS Insights, TELUS and Chad Jennings, Product Manager and GIS Lead, Google Cloud, and learn about Google Cloud’s uniquely powerful, full–platform solution for geospatial analytics and how organizations are using it to reduce query times from hours, days, or months to minutes. These workloads can span both structured and imagery data.

In this session, they will cover:

  • An overview of BigQuery GIS
  • Some use cases
  • Examples of algorithms TELUS is using
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Speech Analytics and AI: Leverage Every Customer Interaction as a Data Point

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Contact centers can transform customer experience using AI-driven speech analytics to evaluate every customer interaction and use it as a ‘data point’ to identify key patterns, enquiries, pain points, reviews and feedback to enhance customer experience with real-time, personalized recommendations. Knowlarity’s AI-based cloud telephony solutions for businesses built with Google Cloud takes speech analytics to another level!

Download the article to empower your contact centers with AI-powered speech analytics to make predictive analysis, reduce call handling time and volume as well as train contact center agents to provide customers with quick and real-time feedback.

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Google Cloud named a leader in the Forrester Wave: Streaming Analytics

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There’s a lot of pressure on companies today to become data-driven, but they need high-performing technology to make that a reality.

As part of Google’s larger cloud data analytics platform, Cloud Pub/Sub and Cloud Dataflow are designed for ease of use, scalability, and performance.

Google Cloud unifies streaming analytics and batch processing the way it should be. No compromises.

Forrester

Forrester has named Google Cloud as a leader in The Forrester Wave™: Streaming Analytics, Q3 2019. This findings reflect Google Cloud’s market momentum, and what Google hears from enterprise customers who are using Cloud Pub/Sub and Cloud Dataflow in production for streaming analytics in conjunction with our broader platform.  

According to Forrester, many leading enterprises realize that real-time analytics—the analytics of what’s happening with data in the present—is an incredible competitive advantage. With it, they can act right away to serve customers, fix operational problems, power internet of things (IoT) apps, and respond decisively to competitors.

The report evaluates the top 11 vendors against 26 rigorous criteria for streaming analytics to help enterprise IT teams understand their options and make informed choices for their organizations. Google scored 5 out of 5 in Forrester’s report evaluation criteria of scalability, availability, aggregates, management, security, extensibility, ability to execute, solution roadmap, partners, community, and customer adoption. 

We are very excited about the productivity benefits offered by Cloud Dataflow and Cloud Pub/Sub. It took half a day to rewrite something that had previously taken over six months to build using Apache Spark.
Paul Clarke, Director of Technology, Ocado

While stream analytics is a leading business priority, real-life use cases frequently require batch data as an input as well. Google Cloud Platform (GCP) customers can simplify their pipeline development by reusing code across both batch and stream processing using Apache Beam, which also provides pipeline portability to OSS projects. Further, Google Cloud’s data analytics portfolio autoscales across ingestion, processing, and analysis, which eliminates the need for provisioning and makes handling varying volumes of streaming data automatic. We hear from users that they’re able to ingest and process data much more quickly than in the past, helping to get new business insights faster and allowing more users to do self-serve analytics.

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CCAI Insights: Answer Customers’ Queries & Understand Them Better with Conversation Data

With CCAI Insights, businesses can drive contact center efficiency, solve customer problems and leverage data from customer interactions to understand them better!

CCAI Insights, a core piece of the Google Cloud’s Contact Center AI product suite is built to help contact center management dive into data to adjust business needs, preempt problems with timely analysis of customer conversations and keep agents prepared. Additionally, businesses can automatically feed data into Insights from other areas of CCAI like Dialogflow CX or another product sources. Watch the video to find out more benefits and capabilities of CCAI Insights in elevating CX.

Case Study

This Diagnostic Company is Revolutionising Healthcare Delivery with AI

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How do you shrink the time it takes to deliver MRI results from a minimum of 2 days to a mere 15 minutes?

Dr. Elliot Smith cannot be accused of lacking ambition. A high achiever with a Ph.D. in Electrical Engineering and a specialist in magnetic resonance imaging (MRI) systems, Smith aims to deliver top quality healthcare to anyone in the world — regardless of their location or wealth.

Dr. Smith has already made strides on this journey with his Brisbane, Queensland-headquartered business, Maxwell MRI. “I saw there was a big gap in the market around automating the diagnosis of health conditions,” he says. “Existing processes were typically manual and involved a lot of people.”

Artificial intelligence (AI) and machine learning can remove a key obstacle to scaling out medicine and improve the efficiency and accuracy of diagnosing conditions, the healthcare entrepreneur believes.

“Realistically a cloud product like GCP is the only way we can grow from an Australian-based company to a global company. If we had the burden of looking to set up our own infrastructure, it simply wouldn’t be feasible.”
-Dr. Elliot Smith, Founder and CTO, Maxwell MRI

“Our grand vision is to build an AI doctor that anyone can receive affordable support from and connect to in order to obtain results,” explains Dr. Smith.

Maxwell MRI presently enables clinicians to submit anonymised MRI scans to a machine learning enabled AI platform to help diagnose prostate cancer. The service is sold to clinicians who can then charge a per-session fee to clients. As well as obtaining results for individual cases, the MRI scans and associated information is used to ‘train’ the platform to deliver accurate diagnoses faster and in a more affordable way than existing systems do.

Dr. Smith and his team started by running a number of functions and processes on a single server with graphics processing units (GPUs) and sizable hard disk capacity. However, this infrastructure could not scale to support the planned growth of the business. Each case Maxwell MRI processes involves about 200MB of data in MRI scans alone. Once supplementary data, blood test result, pathology results and genetic information is included, this load can reach more than 1GB of data per patient.

The business aimed to process 150,000 cases by the end of 2018. This required a service that could deliver massive scale in data storage and compute, and could easily be accessed from any location. “We wanted to move from three GPUs to 30 GPUs without having to buy more servers or other associated equipment, so the cloud was the natural next step,” says Dr. Smith.

“We’re saying that with our platform running on GCP, we’ll deliver you results in 10 to 15 minutes, regardless of the number of patients coming in.”
-Dr Elliot Smith, Founder and CTO, Maxwell MRI

Maxwell MRI evaluated Google Cloud Platform (GCP) and determined that the managed services component of GCP would remove the burden of infrastructure deployment and administration. In addition, Google Cloud Machine Learning Engine would enable the business to scale to as many GPUs as needed to meet demand.

Maxwell MRI started with some small experiments to determine that GCP met all its requirements and completed its migration to the platform in February 2017. “We really started to scale up the data we had and consequently our computing requirements at that time,” Dr. Smith says.

The Maxwell MRI platform features an upload service that enables clinicians to upload imaging and associated data. This service triggers several different upload pipelines that clean and standardise data. They then write imaging data to Google Cloud Storage, and more structured data to a combination of Google Cloud Datastore and Google Cloud Spanner.

“We wanted to move from three GPUs to 30 GPUs without having to buy more servers or other associated equipment, so the cloud was the natural next step.”
-Dr. Elliot Smith, Founder and CTO, Maxwell MRI

The platform then converts the information into records that can be used to ‘train’ new machine learning configurations or run evaluations through existing machine learning pipelines.

“The tasks we perform including segmenting various anatomical regions for analysis and sending those results back into Google Cloud Storage,” says Dr. Smith. “This then commences that repeated process of running Google Cloud Dataflow pipelines and machine learning algorithms, and presenting those outcomes back to the clinicians.”

Existing Literature Validated

The data processed and analysed to date has, Dr Smith says, enabled Maxwell MRI to help validate existing literature that indicates clinicians lack confidence in existing early-stage testing procedures for prostate cancer. This prompts them to move quickly to the biopsy stage to assure themselves their diagnosis is valid. “New technologies have a lot of potential to rectify this situation and guide treatment to be more accurate, specific and cost-effective,” he says.

Results Delivered in 10-15 Minutes

More specifically, using GCP has enabled Maxwell MRI to guarantee to clinicians that results will be delivered within minutes. “Clinicians are used to getting results back in two days to a week,” says Dr. Smith. “We’re saying that with our platform running on GCP we’ll deliver you results in 10 to 15 minutes, regardless of the number of patients coming in.”

Running on GCP has enabled the business to accelerate its development cycles, test new ideas easily on a subset of data, test in parallel and deliver new services considerably faster than in another environment. In addition, the flexible GCP charging model aligned with the ability to scale compute capabilities quickly and easily has enabled the fledgling business to control its costs.

Google technologies are poised to play an integral role in the business’s future. “With Google available, it doesn’t make sense for us to use our own infrastructure,” Dr. Smith says. “Our expertise in AI, machine learning and clinical engagement complements cloud platform specialties of infrastructure, managed services and ease of use. We see a bright future ahead in helping to transform healthcare globally.”

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