Graph Database Starter Kits
TigerGraph Cloud Starter Kits
Out-of-the-box starter kits for fast application development
TigerGraph Cloud Starter Kits are built with sample graph data schema, dataset, and queries focused on a specific use case such as Fraud Detection, Recommendation Engine, Supply Chain Analysis and/or a specific industry such as healthcare, pharmaceutical or financial services.
Starter Kit
- Blank
- Customer 360 – Attribution and Engagement Graph
- COVID-19 Analysis
- Cybersecurity Threat Detection-IT
- Enterprise Knowledge Graph (Corporate Data)
- Enterprise Knowledge Graph (Crunchbase)
- Entity Resolution (MDM)
- Financial Services (Payments) – Fraud Detection
- Fraud and Money Laundering Detection (Fin. Services)
- GSQL 101
- Graph Analytics - Centrality Algorithms
- Graph Analytics - Community Detection Algorithms
- Graph Analytics - Shortest Path Algorithms
- Healthcare Graph (Drug Interaction/FAERS)
- Healthcare – Referral Networks, Hub(PageRank) & Community Detection
- Machine Learning and Real-time Fraud Detection
- In-Database Machine Learning Recommendation
- In-Database Machine Learning for Big Data Entity Resolution
- Low-Rank Approximation Machine Learning
- Network and IT Resource Optimization
- Recommendation Engine (Movie Recommendation)
- Recommendation Engine 2.0 (Hyper-Personalized Marketing)
- Social Network Analysis
- Supply Chain Analysis
Overview
- No pre-populated schema, dataset or queries
- Create a real-time 360-degree view of the customer journey for attribution and engagement insights
- Detect hubs of infection and track the movements of potential spreaders
- Block cybersecurity threats by detecting interconnected events, devices and people
- Analysis of corporate data including investors and key stakeholders
- Knowledge Graph example featuring Crunchbase data with startups, founders and companies
- Identify, link and merge entities such as customers with analysis of attributes and relationships
- Detect and stop fraudulent payments in real-time
- Multiple types of fraud and money laundering patterns
- Introduction to TigerGraph’s powerful graph query language
- Determine the entity in your network that is most central to the others
- Find communities of a specific type in your network Tags: Graph Algorithms
- Identify the path through your network with the fewest number of hops
- Healthcare example focused on public (FAERS) and private data for pharmaceutical drugs
- Analyze member (patient) claims to establish referral networks, identify most influential prescribers (doctors) and discover the connected prescriber communities
- Mobile industry example for detecting fraud in real-time and generating graph-based features for training the machine learning solution
- Provide content and products suggestions using an in-database machine learning recommendation system
- Match, link and group entities for creating a single identity across large datasets with in-database machine learning.
- Implement the low-rank approximation algorithm natively in-database to deliver personalized recommendations
- Network and IT resource graph for modeling and analyzing the impact of the hardware outage on workloads
- Graph-based movie recommendation engine built with public data
- Hyper-personalized recommendation engine to create dynamic offers in real-time for higher click-through and revenue
- Social network example for understanding and analyzing relationships
- Example covering inventory planning and impact analysis
Video
- Graph Gurus 23
- Customer 360 Demo
- COVID-19 Demo
- Graph Gurus 22
- Enterprise Relationship Demo
- Crunchbase Data Demo
- Graph Gurus 18
- Graph Gurus 17
- Anti-Fraud Demo
- GSQL Webinar
- Graph Gurus 27
- Graph Gurus 29
- Graph Gurus 26
- Healthcare FAERS Demo
- Referral Networks Demo
- Graph Gurus 3
- Graph Gurus 28
- In-Database Machine Learning for Big Data Entity Resolution Demo
- Graph Gurus 28
- Graph Gurus 9
- Graph Gurus 2
- Graph Gurus 16
- Social Connections Demo
- Supply Chain Demo
Dataset
- Customer 360 Dataset
- COVID-19 Analysis Dataset
- Cybersecurity Dataset
- Enterprise Knowledge Graph (Corporate) Dataset
- Enterprise Knowledge Graph (Crunchbase) Dataset
- Entity Resolution Dataset
- Financial Services (Payments) Dataset
- Fraud and Money Laundering Detection Dataset
- GSQL Dataset
- Centrality Algorithms Dataset
- Community Detection Algorithms Dataset
- Shortest Path Algorithms Dataset
- Healthcare FAERS Dataset
- Healthcare Referral Networks Dataset
- Machine Learning / Fraud Detection Dataset
- In-Database Machine Learning Recommendation Dataset
- In-Database Machine Learning for Big Data Entity Resolution Demo Dataset
- Low-Rank Approximation Machine Learning Dataset
- Network and IT Dataset
- Recommendation Engine Dataset
- Recommendation Engine 2.0 Dataset
- Social Network Dataset
- Supply Chain Dataset
Starter Kit | Blank |
Overview | No pre-populated schema, dataset or queries |
Video | Graph Gurus 23 |
Dataset |
Dataset | |
|---|---|
Starter Kit | Customer 360 – Attribution and Engagement Graph |
Overview | Create a real-time 360-degree view of the customer journey for attribution and engagement insights |
Video | Customer 360 Demo |
Dataset | Customer 360 Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | COVID-19 Analysis | ||
Overview | Detect hubs of infection and track the movements of potential spreaders | ||
Video | COVID-19 Demo | ||
Dataset | COVID-19 Analysis Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | Cybersecurity Threat Detection-IT | ||
Overview | Block cybersecurity threats by detecting interconnected events, devices and people | ||
Video | Graph Gurus 22 | ||
Dataset | Cybersecurity Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | Enterprise Knowledge Graph (Corporate Data) | ||
Overview | Analysis of corporate data including investors and key stakeholders | ||
Video | Enterprise Relationship Demo | ||
Dataset | Enterprise Knowledge Graph (Corporate) Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | Enterprise Knowledge Graph (Crunchbase) | ||
Overview | Knowledge Graph example featuring Crunchbase data with startups, founders and companies | ||
Video | Crunchbase Data Demo | ||
Dataset | Enterprise Knowledge Graph (Crunchbase) Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | Entity Resolution (MDM) | ||
Overview | Identify, link and merge entities such as customers with analysis of attributes and relationships | ||
Video | Graph Gurus 18 | ||
Dataset | Entity Resolution Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | Fraud and Money Laundering Detection (Fin. Services) | ||
Overview | Multiple types of fraud and money laundering patterns | ||
Video | Anti-Fraud Demo | ||
Dataset | Fraud and Money Laundering Detection Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | Financial Services (Payments) – Fraud Detection | ||
Overview | Detect and stop fraudulent payments in real-time | ||
Video | Graph Gurus 17 | ||
Dataset | Financial Services (Payments) Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | GSQL 101 | ||
Overview | Introduction to TigerGraph’s powerful graph query language | ||
Video | GSQL Webinar | ||
Dataset | GSQL Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | Graph Analytics – Centrality Algorithms | ||
Overview | Determine the entity in your network that is most central to the others | ||
Video | Graph Gurus 27 | ||
Dataset | Centrality Algorithms Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | Graph Analytics – Community Detection Algorithms | ||
Overview | Find communities of a specific type in your network Tags: Graph Algorithms | ||
Video | Graph Gurus 29 | ||
Dataset | Community Detection Algorithms Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | Graph Analytics – Shortest Path Algorithms | ||
Overview | Identify the path through your network with the fewest number of hops | ||
Video | Graph Gurus 26 | ||
Dataset | Shortest Path Algorithms Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | Healthcare Graph (Drug Interaction/FAERS) | ||
Overview | Healthcare example focused on public (FAERS) and private data for pharmaceutical drugs | ||
Video | Healthcare FAERS Demo | ||
Dataset | Healthcare FAERS Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | Healthcare – Referral Networks, Hub(PageRank) & Community Detection | ||
Overview | Analyze member (patient) claims to establish referral networks, identify most influential prescribers (doctors) and discover the connected prescriber communities | ||
Video | Referral Networks Demo | ||
Dataset | Healthcare Referral Networks Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | Machine Learning and Real-time Fraud Detection | ||
Overview | Mobile industry example for detecting fraud in real-time and generating graph-based features for training the machine learning solution | ||
Video | Graph Gurus 3 | ||
Dataset | Machine Learning / Fraud Detection Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | In-Database Machine Learning Recommendation | ||
Overview | Provide content and products suggestions using an in-database machine learning recommendation system | ||
Video | Graph Gurus 28 | ||
Dataset | In-Database Machine Learning Recommendation Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | In-Database Machine Learning for Big Data Entity Resolution | ||
Overview | Match, link and group entities for creating a single identity across large datasets with in-database machine learning. | ||
Video | In-Database Machine Learning for Big Data Entity Resolution Demo | ||
Dataset | In-Database Machine Learning for Big Data Entity Resolution Demo Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | Low-Rank Approximation Machine Learning | ||
Overview | Implement the low-rank approximation algorithm natively in-database to deliver personalized recommendations | ||
Video | Graph Gurus 28 | ||
Dataset | Low-Rank Approximation Machine Learning Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | Network and IT Resource Optimization | ||
Overview | Network and IT resource graph for modeling and analyzing the impact of the hardware outage on workloads | ||
Video | Graph Gurus 9 | ||
Dataset | Network and IT Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | Recommendation Engine (Movie Recommendation) | ||
Overview | Graph-based movie recommendation engine built with public data | ||
Video | Graph Gurus 2 | ||
Dataset | Recommendation Engine Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | Recommendation Engine 2.0 (Hyper-Personalized Marketing) | ||
Overview | Hyper-personalized recommendation engine to create dynamic offers in real-time for higher click-through and revenue | ||
Video | Graph Gurus 16 | ||
Dataset | Recommendation Engine 2.0 Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | Social Network Analysis | ||
Overview | Social network example for understanding and analyzing relationships | ||
Video | Social Connections Demo | ||
Dataset | Social Network Dataset |
Starter Kit | Overview | Video | Dataset |
|---|---|---|---|
Starter Kit | Supply Chain Analysis | ||
Overview | Example covering inventory planning and impact analysis | ||
Video | Supply Chain Demo | ||
Dataset | Supply Chain Dataset |
Blank
No pre-populated schema, dataset or queries
Customer 360 – Attribution and Engagement Graph
Create a real-time 360-degree view of the customer journey for attribution and engagement insights
COVID-19 Analysis
Detect hubs of infection and track the movements of potential spreaders
Cybersecurity Threat Detection-IT
Block cybersecurity threats by detecting interconnected events, devices and people
Data Lineage v3
Improve data governance with the ability to track data back to its source
Enterprise Knowledge Graph (Corporate Data)
Analysis of corporate data including investors and key stakeholders
Enterprise Knowledge Graph (Crunchbase)
Knowledge Graph example featuring Crunchbase data with startups, founders and companies
Entity Resolution (MDM)
Identify, link and merge entities such as customers with analysis of attributes and relationships
Financial Services (Payments) – Fraud Detection
Detect and stop fraudulent payments in real-time
Fraud and Money Laundering Detection (Fin. Services)
Multiple types of fraud and money laundering patterns
GSQL 101
Introduction to TigerGraph’s powerful graph query language
Graph Analytics - Centrality Algorithms
Determine the entity in your network that is most central to the others
Graph Analytics - Community Detection Algorithms
Find communities of a specific type in your network Tags: Graph Algorithms
Graph Analytics - Shortest Path Algorithms
Identify the path through your network with the fewest number of hops
Graph Convolutional Networks
Graph convolutional networks for paper classification on a citation graph
Healthcare Graph (Drug Interaction/FAERS)
Healthcare example focused on public (FAERS) and private data for pharmaceutical drugs
Healthcare – Referral Networks, Hub(PageRank) & Community Detection
Analyze member (patient) claims to establish referral networks, identify most influential prescribers (doctors) and discover the connected prescriber communities
In-Database Machine Learning Recommendation
Provide content and products suggestions using an in-database machine learning recommendation system
In-Database Machine Learning for Big Data Entity Resolution
Match, link and group entities for creating a single identity across large datasets with in-database machine learning.
Low-Rank Approximation Machine Learning
Implement the low-rank approximation algorithm natively in-database to deliver personalized recommendations
Network and IT Resource Optimization
Network and IT resource graph for modeling and analyzing the impact of the hardware outage on workloads