Best Practices

Essential patterns and strategies for building effective Elementum workflows

Master the art of building effective workflows with these proven patterns and strategies. This guide covers the essential principles that separate good Elementum implementations from great ones.

New to Elementum? Start with our Quick Start Guide to understand the basics before diving into these advanced practices.

Core Objects Overview

Understanding Elementum’s core objects is fundamental to building effective workflows. Each object serves a specific purpose and excels in particular scenarios.

Elementum’s core objects fall into two categories:

• Process-oriented objects (Services, Apps, Tasks) - For structured workflows and processes
• Data-oriented objects (Elements, Tables, Surveys) - For data management and collection

Services

Best for: Customer support, help desk, and request portals

When to Use Services

• Creating user-facing portals for request submission
• Automatically generating App records from submissions
• Standardizing intake processes across teams
• Providing self-service capabilities to end users

Example Use Cases:

• IT helpdesk portal
• Employee onboarding requests
• Customer support ticket system
• Equipment request portal

Apps

Best for: Tracking individual business processes and work items

When to Use Apps

• Managing unique work items that progress through stages
• Tracking complex business processes with multiple stakeholders
• Coordinating work that spans multiple departments
• Maintaining audit trails for compliance

Example Use Cases:

• Contract approval workflows
• Employee onboarding processes
• Customer implementation projects
• Compliance audits

Tasks

Best for: Breaking down work into manageable, assignable activities

When to Use Tasks

• Decomposing complex Apps into smaller activities
• Assigning specific work to individual team members
• Creating parallel workstreams within larger processes
• Tracking progress on detailed work items

Key Principles:

• Tasks should be specific and actionable
• Assign clear ownership and deadlines
• Use Tasks to create accountability within larger workflows
• Complex Apps often require multiple related Tasks

Elements

Best for: Managing structured data with unique identifiers

When to Use Elements

• Storing configuration, master, or transactional data
• Managing data that needs unique identification
• Creating relationships between different data types
• Building searchable, updateable data repositories

Requirements:

• Each record must have a unique identifier
• Data structure should be relatively stable
• Updates need to be tracked and auditable

Tables

Best for: Data analysis, reporting, and automation triggers

When to Use Tables

• Joining and manipulating Elementum objects for insights
• Accessing Snowflake data without primary key requirements
• Powering Data Mines for automation workflows
• Creating complex analytical views

Advantages:

• Unique Identifiers not required (unlike Elements), allowing for duplicates if needed
• Effective for aggregations and analytics
• Essential for automation triggers

Surveys

Best for: Collecting structured feedback and responses

When to Use Surveys

• Gathering feedback from internal and external users
• Collecting parallel responses from multiple stakeholders
• Linking feedback directly to App records
• Creating standardized data collection processes

Best Practices:

• Design questions to minimize ambiguity
• Link Surveys to relevant Apps for context
• Use conditional logic to improve user experience
• Plan for data analysis during survey design

Implementation Strategies

Object Selection Framework

Follow this decision tree to choose the right object for your needs:

1. Define Your Primary Goal

   • Need to track work through stages? → Apps + Tasks
   • Need to gather information? → Surveys + Elements
   • Need to analyze or report? → Tables + Data Mines
   • Need user self-service? → Services
2. Consider Your Data Requirements

   • Unique identifiers needed? → Elements
   • No unique ID required? → Tables
   • User input required? → Surveys
   • Process tracking needed? → Apps
3. Plan for Relationships

   • Link Surveys to Apps for process feedback
   • Connect Tasks to Apps for work breakdown
   • Relate Elements to Apps for contextual data
   • Use Tables to join multiple object types for analysis

Building Effective Relationships

Strategic relationships between objects unlock Elementum’s full potential:

Process Relationships

Service → App → Tasks

Creates complete workflow from request to completion

Data Relationships

Survey → App → Elements

Connects feedback to processes and reference data

Relationship Best Practices

Avoid Over-Engineering: Don’t create relationships just because you can. Each relationship should serve a clear business purpose.

• Hierarchical Relationships: Use parent-child relationships for natural hierarchies
• Reference Relationships: Link to Elements for master data lookups
• Process Relationships: Connect workflow stages through Apps and Tasks
• Contextual Relationships: Link Surveys to Apps for process-specific feedback

Performance Optimization

Query Performance

Element Optimization

• Use meaningful unique identifiers
• Index frequently searched fields
• Minimize complex calculated fields
• Regular cleanup of outdated records

Table Optimization

• Leverage Snowflake table types
• Use efficient Data Mine queries
• Implement proper data partitioning
• Monitor query performance regularly

Data Architecture

1. Design for Scale

   • Plan for data growth from day one
   • Use appropriate object types for your data volume
   • Consider Snowflake warehouse configuration early
2. Optimize Relationships

   • Avoid deep relationship chains (>3 levels)
   • Use reference relationships instead of duplicating data
   • Regular relationship cleanup and validation
3. Monitor and Maintain

   • Regular performance reviews
   • Optimize slow-running Data Mines
   • Clean up unused objects and relationships

Security and Governance

Access Control

Security First: Plan your access control strategy before building complex workflows.

• Role-Based Access: Align Elementum roles with organizational structure
• Data Sensitivity: Classify data and apply appropriate restrictions
• Workflow Permissions: Control who can view, edit, and approve at each stage
• Audit Trails: Maintain complete records of all changes and approvals

Governance Framework

Naming Conventions

Establish consistent naming patterns:

• Apps: [Department]_[Process]_[Year]
• Elements: [Type]_[Category]_[Identifier]
• Tasks: [Action]_[Object]_[Stage]
• Surveys: [Purpose]_[Audience]_[Version]

Documentation Standards

Maintain clear documentation:

• Purpose and scope for each workflow
• Role definitions and responsibilities
• Process diagrams and flowcharts
• Regular updates and reviews

Change Management

Control modifications carefully:

• Test changes in development environments
• Document all modifications
• Communicate changes to affected users
• Maintain rollback procedures

Common Pitfalls to Avoid

Critical Mistakes That Can Break Your Implementation

Object Misuse

Using the Wrong Object Type

Problem: Choosing Tables when Elements are needed, or vice versa

Solution:

• Use Elements when you need unique identifiers and data integrity
• Use Tables for analysis and reporting without unique constraints
• Use Apps for process tracking, not just data storage

Red Flags:

• Multiple “Tables” that should be related Elements
• Apps with no associated Tasks or workflow
• Elements being used purely for analytics

Over-Engineering

Creating Unnecessarily Complex Relationships

Problem: Building elaborate relationship networks that slow performance

Solution:

• Keep relationship chains under 3 levels deep
• Document the business justification for each relationship
• Regular reviews to eliminate unused connections

Red Flags:

• Relationships that require multiple hops to access data
• Circular references between objects
• Relationships created “just in case”

Poor Data Design

Inadequate Planning for Data Growth

Problem: Not considering how data volume will impact performance

Solution:

• Plan for 10x current data volume
• Implement archiving strategies early
• Use appropriate Snowflake table types (see Table Types Guide)

Red Flags:

• No data retention policies
• Single large tables without partitioning
• No performance monitoring in place

Success Metrics

Track these key indicators to measure your Elementum implementation success:

Process Efficiency

• Average time from request to completion
• Percentage of on-time deliveries
• User satisfaction scores
• Error rates and rework frequency

System Performance

• Query response times
• Data Mine execution duration
• User adoption rates
• System uptime and reliability

Next Steps

Ready to implement these best practices? Here’s your roadmap:

1. Assess Current State

   • Review existing workflows against these best practices
   • Identify quick wins and improvement opportunities
   • Plan your optimization roadmap
2. Implement Foundational Changes

   • Start with data best practices
   • Optimize your CloudLink setup
   • Configure proper table types and warehouses
3. Optimize and Scale

   • Implement advanced automation with Data Mines
   • Build comprehensive governance frameworks
   • Monitor and continuously improve performance

Data Best Practices

Deep dive into data management and optimization

CloudLink Setup

Optimize your data connectivity and performance

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This guide is regularly updated based on customer feedback and new Elementum features. Last updated: