Welcome to Sharing and Deploying Data Science with KNIME Server Going Live At

• Please use the Q&A section to post your questions. • Upvote for your favorite questions. Challenges Operationalizing Data Science

Creating Great Data Science

Large, Providing complex skills and variety of Continuous, Mainstreaming resources technologies high quality across the delivery organization

Data Science Driven Applications

R&D MFG IT Marketing Sales … more

Productionizing Data Science

Continuous, Mainstreaming Large, complex Providing high quality across the variety of skills and delivery organization technologies resources

Data Science Driven Applications

R&D MFG IT Marketing Sales … more

Create Productionize

Gather & Model & Deploy & Consume & Wrangle Visualize Manage Optimize

Open Source Commercial KNIME Analytics Platform KNIME Server

Data KNIME KNIME KNIME Community Partner Science as WebPortal Extensions Integrations Extensions Extensions a Service

. Collaboration . Share Expertise and Templates/Blueprints . Automation . Schedule, Monitor, Update . Deployment . To Humans: Analytical Applications (“Guided Analytics”) . To Machines: via REST and custom APIs . Management . Manage distributed setups . Integrate with existing enterprise setup (authentication)

Workflow Hub Workflows Metanodes, Data Nodes Collaboration

Shared Repository, Versioning

Provisioning Remote, Client Control Distributed Executors Automation

Web Front-ends Guided Analytic Apps RESTful Services Deployment

Management Configuration & Client & User Security Versioning Preferences

. Interaction & Automation . Data Scientist’s Choice: right mix for target audience

• Enables external integration Deploy KNIME • Build applications around KNIME Server workflows as web • e.g. for Microservices and real time scoring services

Output in server Input data response

. Create snapshots of workflow revisions . Allow roll-back to previous versions . Full workflow history available in client and on Workflow Hub

. Inspect differences between versions of the same workflow

Highlight differences: - Nodes included/excluded - Node configurations

. Manage permissions for workflows and data on KNIME Server . Control which groups can access, modify, or execute a workflow . Use LDAP / Active Directory groups for centralized administration

How do I How do I configure install Python? database drivers?

KNIME KNIME KNIME Analytics Analytics Analytics Platform Platform Platform

KNIME Website Internal knowledgebase

• Different departments/teams have different Marketing Finance R&D requirements

• Multiple OS deployments • Windows 7 • Windows 10 • Linux • macOS Windows 10 Windows 7 Linux and macOS Hive Oracle Python Spark MS Access R

• Client-profiles • Python-Linux • Python-macOS KNIME Server • R-Linux client-profiles • R-macOS • Databases-Win7 Big Data- Databases- Python- • Big Data-Win10 Win10 Win7 macOS (etc)

Profiles can include: Preferences, drivers, and more Marketing Finance R&D

Features: • Offload compute from KNIME Server • Scale Executors to compute needs • Support Executors with varying configurations • Flexible deployment options

Features: • Match workflow needs to Executor capabilities • Partition compute resources by capability, department, usage, … • Workflow needs determined by workflow publisher

Supporting Executors in the Enterprise*

Executor Group Properties Marketing More

… Features: • Logical groupings of Executors Executor Group Properties • Match users/groups to Executor Finance More Groups KNIME … Server • Partition compute resources by groups, department, … Executor Group Properties • Partitioning managed by Server Engineeri More administrators ng …

*production July 2020

KNIME Cloud Offerings – AWS and Azure Features: • KNIME Analytics Platform • KNIME Server Large BYOL • Supports Server Large with multiple Executors • Has an embedded Executor so can be stand-alone • KNIME Executors • Multiple Executors that can be used by KNIME Server Large • Pay as you go (PAYG) offering supports elastic scaling • Bring your own license (BYOL) offering uses cores from your Server license

KNIME Executor Auto-scaling

Features: • Using cloud platforms or Kubernetes* auto-scaling capabilities • Elastic scaling to meet demand • Scales out to meet needed capacity • Scales in to save costs • Supported on AWS and Azure in PAYG licensing model

Mixed Cloud Usage

Virtual Private Cloud

Executors - BYOL Features: • Supplement traditionally Executor Executor licensed Executors with Pay-as- Executor Executor you-Go (PAYG) model • Meet periodic demand peaks KNIME Server • Fulfill need for speciality Executors - PAYG hardware (e.g. GPU‘s) • Meet budgeting needs Executor Executor

Executor Executor

Executors - licensed

Executor Executor Features: Executor Executor • Mix of Enterprise data center and Cloud deployments KNIME • Meet periodic demand peaks Server • Fulfill need for speciality Executors - PAYG hardware (e.g. GPU‘s) V P Executor Executor • Meet budgeting needs N Executor Executor

AWS Virtual Private Cloud

Workflow Hub Workflows Metanodes, Data Nodes Collaboration

Shared Repository, Versioning Ready to get started with KNIME Server? Provisioning Remote, Client Control Distributed Executors Contact us for a free Automation trial:

[email protected] Web Front-ends Guided Analytic Apps RESTful Services Deployment

Management Configuration & Client & User Security Versioning Preferences