SnapLogic Live: Workday Integration

Jun 16, 2016Download as PPTX, PDF1 like547 views

SnapLogic provides a unified integration platform that allows users to integrate Workday with other enterprise systems rapidly without coding. The platform uses a modern hybrid and elastic architecture that scales out elastically to handle data and application integration use cases. It can integrate Workday with salesforce.com and other applications through pre-built integration patterns. A live demonstration of Workday integration capabilities is available at SnapLogic.com/live.

Anything
apps | data | APIs | Things
SnapLogic: Unified Platform for Data and Application Integration
Anytime
batch | streaming | real-time
Anywhere
on premises | in the cloud

Common SnapLogic Elastic Integration Use Cases
Hybrid
Application
Integration
Cloud Data
Warehouse/Anal
ytics
Big Data Ingest-
Transform-
Deliver
RESTful
Retire Legacy
Integration
Platforms

Sync Workday with the Enterprise
• Rapidly integrate Workday with other enterprise systems
without coding
• Integrate without the complexity of an ESB
• Quickly add or retire applications to workflows

SnapLogic and Workday Financial Management
• SnapLogic’s Quote-to-Cash (Q2C) integration is Approved by Workday and
connects the Workday Financials application with Salesforce CRM
• Configurable Pre-built quote-to-cash orchestration pattern
- Synchronizes Opportunity, Customer, Product and related data quickly, w/o manual
coding
- Documentation providing guidance, consistency for all Workday Customers,
Partners

SnapLogic’s Modern Architecture: Hybrid and Elastic
Streams: No data is
stored/cached
Secure: 100%
standards-based
Elastic: Scales out &
handles data and
app integration use
cases
Metadata
Data
Databases
On Prem
Apps
Big Data
Cloud Apps
and DataCloud-Based Designer, Manager,
Dashboard
Cloudplex
Groundplex
Hadooplex
Sparkplex
Firewall

Discussion
snaplogic.com
Unified Platform Self-Service UX
Modern Architecture Connected: 350+ Snaps

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Software testing plays a crucial role in the contribution process of open-source projects. For example, contributions introducing new features are expected to include tests, and contributions with tests are more likely to be accepted. Although most real-world projects require contributors to write tests, the specific testing practices communicated to contributors remain unclear. In this paper, we present an empirical study to understand better how software testing is approached in contribution guidelines. We analyze the guidelines of 200 Python and JavaScript open-source software projects. We find that 78% of the projects include some form of test documentation for contributors. Test documentation is located in multiple sources, including CONTRIBUTING files (58%), external documentation (24%), and README files (8%). Furthermore, test documentation commonly explains how to run tests (83.5%), but less often provides guidance on how to write tests (37%). It frequently covers unit tests (71%), but rarely addresses integration (20.5%) and end-to-end tests (15.5%). Other key testing aspects are also less frequently discussed: test coverage (25.5%) and mocking (9.5%). We conclude by discussing implications and future research.

Not So Common Memory Leaks in Java WebinarTier1 app

This SlideShare presentation is from our May webinar, “Not So Common Memory Leaks & How to Fix Them?”, where we explored lesser-known memory leak patterns in Java applications. Unlike typical leaks, subtle issues such as thread local misuse, inner class references, uncached collections, and misbehaving frameworks often go undetected and gradually degrade performance. This deck provides in-depth insights into identifying these hidden leaks using advanced heap analysis and profiling techniques, along with real-world case studies and practical solutions. Ideal for developers and performance engineers aiming to deepen their understanding of Java memory management and improve application stability.

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Exceptional Behaviors: How Frequently Are They Tested? (AST 2025)Andre Hora

Exceptions allow developers to handle error cases expected to occur infrequently. Ideally, good test suites should test both normal and exceptional behaviors to catch more bugs and avoid regressions. While current research analyzes exceptions that propagate to tests, it does not explore other exceptions that do not reach the tests. In this paper, we provide an empirical study to explore how frequently exceptional behaviors are tested in real-world systems. We consider both exceptions that propagate to tests and the ones that do not reach the tests. For this purpose, we run an instrumented version of test suites, monitor their execution, and collect information about the exceptions raised at runtime. We analyze the test suites of 25 Python systems, covering 5,372 executed methods, 17.9M calls, and 1.4M raised exceptions. We find that 21.4% of the executed methods do raise exceptions at runtime. In methods that raise exceptions, on the median, 1 in 10 calls exercise exceptional behaviors. Close to 80% of the methods that raise exceptions do so infrequently, but about 20% raise exceptions more frequently. Finally, we provide implications for researchers and practitioners. We suggest developing novel tools to support exercising exceptional behaviors and refactoring expensive try/except blocks. We also call attention to the fact that exception-raising behaviors are not necessarily “abnormal” or rare.

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SnapLogic Live: Workday Integration

1. SnapLogic Live: Workday Integration

3. Common SnapLogic Elastic Integration Use Cases Hybrid Application Integration Cloud Data Warehouse/Anal ytics Big Data Ingest- Transform- Deliver RESTful Retire Legacy Integration Platforms

4. Sync Workday with the Enterprise • Rapidly integrate Workday with other enterprise systems without coding • Integrate without the complexity of an ESB • Quickly add or retire applications to workflows

5. SnapLogic and Workday Financial Management • SnapLogic’s Quote-to-Cash (Q2C) integration is Approved by Workday and connects the Workday Financials application with Salesforce CRM • Configurable Pre-built quote-to-cash orchestration pattern - Synchronizes Opportunity, Customer, Product and related data quickly, w/o manual coding - Documentation providing guidance, consistency for all Workday Customers, Partners

6. SnapLogic’s Modern Architecture: Hybrid and Elastic Streams: No data is stored/cached Secure: 100% standards-based Elastic: Scales out & handles data and app integration use cases Metadata Data Databases On Prem Apps Big Data Cloud Apps and DataCloud-Based Designer, Manager, Dashboard Cloudplex Groundplex Hadooplex Sparkplex Firewall

7. Demonstration: Snaplogic.com/live

8. Discussion snaplogic.com Unified Platform Self-Service UX Modern Architecture Connected: 350+ Snaps

Editor's Notes

#3: Leading enterprises choose SnapLogic because we help them connect data and applications faster. We connect anything: sources including applications, APIs, things, or data We connect anytime: in batches, streaming, or in real time And we connect anywhere: on premises, in the cloud or a combination of both
#6: Automatically create/update Prospect in Workday when an Opportunity is created in Salesforce Create a Customer record in Workday when an Opportunity in Salesforce reaches a predefined stage Update Opportunity cost information in Salesforce based on data from Workday Create or update Products in Salesforce from Sales Item data in Workday And more…
#7: Here is an example of a SnapLogic deployment. The SnapLogic control plane – including he Designer, Manager and Dashboard - does not store your data. It’s metadata only. Once a pipeline is executed, it looks for the associated Snaplex or Hadooplex. The plex dynamically scales out, adding more nodes as needed. We like to say that SnapLogic “respects data gravity” and runs as close to the data as need be. If you are integrating only cloud applications, it would make no sense to run your integrations behind the firewall. Similarly, if you’re doing ground to ground or cloud to ground, you may want to run your Snaplex on Window or Linux servers. Note that the dotted line is sending instructions via metadata to the plex, which is waiting to run. The solid line indicates how data movies bi-directionally between systems.
#8: http://video.snaplogic.com/demos/

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Editor's Notes