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Today, during its Google Cloud Next 2021 conference, Google unveiled a number of data-focused products, including Intelligent Product Essentials and enhancements to Vertex AI, BigQuery, Contact Center AI (CCAI) and DocAI. The new analytics and industry solutions are designed to simplify how organizations extract value from data, Google says – whether they’re developing a new product or improving an existing one.
AI adoption and analysis is on the rise during the pandemic, with 20% of companies claiming to have increased their use of business analytics compared to the global average. But while 97% of executives say computer science is “crucial” to maintaining profitability, several major challenges stand in the way. A Dremio report showed that only 22% of data managers have realized a return on investment in data management in the last two years.
Focus on intelligent products such as Google Cloud [launching] provides a digital opportunity for [customers], ”Said IDC Group Vice President Kevin Prouty in a statement. “IDC sees faster and more efficient decision-making as the fundamental reason for the drive to digitize products and processes. This is how you can make faster and more efficient decisions to meet increased customer expectations, generate faster cash flows and better revenue realization. ”
Intelligent Product Essentials
Intelligent Product Essentials aims to help manufacturers develop hardware products. With it, they can deliver AI-enabled devices that can update over-the-air and provide insight using analytics in the cloud, according to Google.
Intelligent Product Essentials can be used to create personalized customer experiences – e.g. A chatbot that contextualizes responses based on product status and customer profiles. The service can also implement updates to products in the field and gather performance insights as well as develop capabilities over time with revenue generation opportunities.
Intelligent Product Essentials predicts parts and service issues and detects operating thresholds, anomalies, and errors so that it can proactively recommend service using AI. Customers can take advantage of the offer to connect and consume raw or time series product telemetry from various device platforms to support air updates. In addition, Intelligent Product Essentials lets developers build companion apps that work on smartphones, tablets, and computers using a pre-built API that includes product and security, device registration, and app behavior analysis.
“Intelligent Product Essentials [can] manage, update, and analyze fleets of connected products through APIs, “Google wrote in a blog post.”[Companies can] create new features or options [their] products that use AI and machine learning … [and] integrate data sources such as enterprise asset management, enterprise resource planning, customer relationship management, systems and others. ”
Vertex AI, BigQuery and Spark
Google introduced Vertex AI, a managed AI platform, in May at Google I / O 2021. Today, the Vertex AI Workbench service expands a user experience to build and implement AI models faster, accelerating time-to-value for data researchers and their organizations.
Data researchers spend most of their time cleaning and organizing data, according to a 2016 study by CrowdFlower. In a recent report from Alation, a majority of respondents (87%) pointed to data quality issues as the reason why their organizations could not implement AI. This may be why companies like Markets and Markets predict that the data preparation industry, which includes companies offering data cataloging and curation tools, will be worth up to $ 3.9 billion by the end of 2021.
While Vertex AI is designed to help companies accelerate the implementation and maintenance of AI models, Workbench specifically focuses on integrating IT capabilities into the computing environment. Workbench incorporates Dataproc, BigQuery, Dataplex, Looker and other Google Cloud services, facilitating the capture and analysis of data from a single interface.
“These features are delivered through managed notebooks and help computer scientists quickly build workflows and perform coordination, transformations, security, and machine learning operations, all within Vertex AI,” Google wrote.
On the BigQuery page, Google makes the BigQuery Omni widely available, enabling companies to analyze data across Google Cloud, Amazon Web Services, and Microsoft Azure. The managed, cross-cloud analytics solution helps answer questions and share results from a single pane across datasets, complementing Google’s Dataplex service (which will generally be available this quarter) to make data available to multiple analytics tools .
Google also today announced a preview of Spark on Google Cloud, which the company claims is the world’s first autoscaling and serverless Spark service for Google Cloud. It allows data engineers, data researchers and data analysts to use Spark from their favorite interfaces, write apps and pipelines that are automatically scaled without manual infrastructure provisioning or tuning.
Looker and Spanner
To complement the rest of its data-focused offering, Google continues to make Cloud Spanner, its fully managed, relational database, accessible to customers via a PostgreSQL interface (in preview). The interface supports several popular PostgreSQL data types and SQL functions, so that schemas and queries built against the PostgreSQL interface can be ported to another Postgres environment.
In addition to this, Google debuted new integrations with Looker, which it says will allow customers to “operationalize analytics” and more efficiently scale implementations. Tableau customers and Connected Sheets users will soon be able to take advantage of Looker’s semantic model, with the Connect Sheets integration launched in preview at the end of the year. Looker’s new solution for CCAI helps contextualize support calls coming to the company’s call centers. And the upcoming Looker Block for Healthcare NLP API, compatible with Fast Healthcare Interoperability Resources (FHIR), will give healthcare providers, payers and pharmaceutical companies access to insights from unstructured medical text from clinical sources.
Google Earth Engine
By touching the geospatial, Google revealed the Google Earth Engine on Google Cloud, making the Google Earth Engine catalog of over 50 petabytes of satellite imagery and geospatial datasets available for analysis. Google says Google Cloud customers will be able to integrate Earth Engine with BigQuery, Google Maps Platform and Google Cloud AI technologies, giving data teams “a way to better understand how the world is changing and what actions they can take “- from saving energy costs to understanding business risks and serving customer needs.
Investments in “green” practices are not only beneficial to the environment – they make business sense. According to a 2017 survey on corporate social responsibility, 87% of consumers have a more positive image of businesses that support social or environmental issues. In addition, 87% say they would buy a product with a social and environmental benefit, and 88% would be more loyal to a company that supports this effort.
“For over a decade, Earth Engine has supported the work of scientists and NGOs from around the world, and this new integration brings together the best of Google and Google Cloud to enable companies to create a sustainable future for our planet and for your business. “, Wrote Google.
CCAI and DocAI
Google Clouds CCAI, which offers AI-powered virtual agents and other features, entered general availability in 2019, while the company’s AI-powered document processing service DocAI rolled out in April. Now the two services each get new features in CCAI Insights and Contract DocAI. CCAI Insights delivers out-of-the-box and custom data modeling techniques, and Contract DocAI — now in preview — provides features specifically built for contract lifecycles and processing.
Over the past many years, companies have increasingly turned to cloud-based contact centers to address emerging customer service challenges. The pandemic accelerated this move – service amenities were introduced out of necessity, giving customers more opportunities to interact with businesses. For example, 78% of US contact centers now intend to implement AI over the next 3 years, according to Canam Research. And research from The Harris Poll indicates that 46% of customer interactions are already automated, with the number expected to reach 59% by 2023.
CCAI Insights uses AI to extract raw contact center interaction data for useful information, whether that data comes from a virtual or human agent. It provides out-of-the-box analysis of customer conversations, including Smart Highlighters, which automatically highlights important conversation moments, e.g. When an agent approves or a customer confirms that their problem has been resolved. Meanwhile, integration with Google’s Cloud Natural Language Processing (NLP) identifies positive or negative moods and tags different entities within conversations by types, including date, person, contact information, organization, location, events, products, and media.
CCAI Insights – which can forward calls and chats handled by Dialogflow and Agent Assist – also categorizes conversations with custom highlighters that let customers define rules, keywords, and natural language training phrases. Topic modeling – another capability – leverages NLP technologies so teams can create an AI model of their data to define caller taxonomy.
As for Contract DocAI, it uses NLP, knowledge graph technology, and optical character recognition to analyze contracts for important terms such as those involving start and end dates, renewal terms, parties involved, contract type, location, or service level agreements. It automatically distinguishes important terms and conditions between them, which could potentially lead to faster and cheaper contract processing, Google claims.
“All of these new additions will help transform businesses by making the power of AI more accessible and more focused on achieving business results,” Google wrote. “[The] Announcements build on the momentum we have seen with our AI solutions in delivering business value to our customers. ”
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