Everything you need to know about AI, ML & Analytics Announcements At Google Next

Bimal Tandel runs through the announcements and service enhancements relating to Data & Analytics, ML and AI from Google Next San Francisco 2019.

Google made significant advancements in Data & Analytics, ML and AI by announcing new services and enhancements to its existing services at Google Next. It is clear that Google is now after traditional enterprise workloads and has added significant support for enterprise customers that are seeking to move analytics workloads to cloud with ease. 

What was announced:

  • Open Source technologies are now first-class citizen – GCP has announced a strategic relationship with multiple Open Source technology providers to offer a fully managed service based on these Open Source technologies. This is a significant shift from solely focusing on technologies Google has developed and also a challenge to other Cloud Providers who have taken a different approach when dealing with Open Source technologies. 

  • Accelerate adoption by simplifying Migration and Integration – GCP announced new capabilities that offer features to enterprise customers to accelerate their adoption of the GCP platform.
    • Cloud Data Fusion – Fully managed, code-free and cloud-native data integration service.
    • Data warehouse migration service for BigQuery – Automate data and schema migration from traditional and cloud Data Warehouses to BigQuery.
    • BigQuery Data Transfer Services integration to SaaS applications – Close to 100 connectors to many public SaaS application providers.
    • DataFlow FlexRS resource scheduler – Ability to execute batch operations at a significantly lower cost.
    • DataFlow SQL – Support for SQL in DataFlow Pipelines.

  • Advance analytics capability with the acceleration of insights – BigQuery will offer two new capability to accelerate time to insights.
    • BigQuery BI Engine – BigQuery adds in-memory analysis for sub-second response time for BI workloads.
    • BigQuery and Google Sheets integration – Google Sheets can natively connect to BigQuery for analysis on extremely large datasets.
    • BigQuery ML – New machine learning models that can be directly used in BigQuery.
  • Enhancement in data management – GCP announced services to advance their data management capabilities.
    • Cloud Data Catalog – Simplified Data Catalog and Governance to discover and manage data assets on GCP.

  • New and Enhanced AI capability – GCP made significant development to its AI capability with a brand new collaboration service and enhancement on existing services.
    • AI Platform – A collaborative development platform that helps teams prepare, build, run, and manage ML projects and accelerate the adoption of AI.
    • AutoML enhancements – New features include AutoML Tables, AutoML Video Intelligence,  AutoML Vision at Edge and enhancements to AutoML Natural Language with entity extraction and sentiment analysis.

  • Focused on Industry solutions – GCP has added industry focus with Digital Transformation as one of the key outcomes with the adoption of their platform. In this effort, they released new industry-focused services. 
    • Document Understanding – AI Service to classify and extract information from scanned documents.
    • Contact Center AI – Service that builds on DiaglogFlow to allow customers to build customer-centric call center solutions and intelligent virtual agents.
    • Vision Product Search – Service that allows retail customers to build search applications using images to find similar products.
    • Recommendations AI – Retail focused solutions to help customers provide recommendations of new products based on previous customer interactions.

Google has focused its announcements to highlight its focus on adoption of GCP platform for enterprise customers through simplification and providing services that accelerate cloud adoption for existing workloads.