Knowledge Graphs: Make This Smart Shift to Your Data & Analytics Approach
Are you managing data and analytics at your organization? Learn how tech leaders are using knowledge graphs to transform their approach.
Semantic Layers: Four Characteristics that Define the Valuable New Approach
The secret to data analytics success today is a democratized, self-service data platform, and that’s only possible when you leverage a semantic layer to shift from columns to concepts.
Activate Metadata as Part of your Semantic Layer with Stardog's Integration of Databricks Unity Catalog
Modern enterprises need to develop a Data Governance Framework. For effective governance, this is generally underpinned by a catalog megastore. Unity Catalog provides that megastore across the lakehouse, enabling business users access to full metadata across the workspaces and allowing them to visualize the relationships across the data landscape. The creation of a knowledge layer is accelerated when this metadata is available for modeling in Stardog platform.
Graph Database Examples
How do companies use graph databases in real life? At Stardog, our platform combines graph technology with semantics to enable knowledge graphs. Consider the ability to deeply understand and work with connections between organizations, people, transactions, and events (to name a few examples). Add in inferencing, scalability, and near real-time traversal of big data. The number of graph use cases explodes. Relational databases like SQL simply can’t deliver like graph can.
Stardog Is Now Available in Databricks Partner Connect
The Databricks Partner Connect integration makes it faster and easier for Databricks users. Get started on a path toward building a semantic data layer on top of the Databricks Lakehouse Platform. As an existing Databricks user, you can launch a new instance of Stardog Cloud using your Databricks credentials.
Common Graph Databases Use Cases
There are many reasons for data and analytics leaders to embrace graph techniques. These techniques can provide unique insight into business problems, especially those problems requiring contextual awareness of the connections and disconnections between multiple entities, including organizations, people, transactions, and events. A well-designed and richly populated graph can capture essential data relationships and their variable nature.
Graph Databases vs. Relational Databases: Know the Differences
Graph refers to a data organization system that emphasizes the relationships between data points. This approach contrasts with the more traditional relational data systems — where data is stored in tables.
3 Ways Knowledge Graphs Can Fuel Big Data Analytics in Automotive, Now
What is the most disruptive force in the automotive industry? Electric engines? New business models? Consumer mobility? Nope. The real firebrand for the industry lies in a different kind of engine known as data. Automakers, suppliers, and dealers must adapt quickly to the changing landscape by harnessing the power of data and knowledge graphs to jump-start advanced analytics today.
Why X-Tech Startups are Seizing on Knowledge Graph
The phrase “every company is a tech company” is giving way to “every company is a data company,” which I believe means the value of technology is shifting from applications to data. And as the size and complexity of data multiply, organizations are increasingly turning to semantic knowledge graphs to harness data and unleash insights that fuel data-informed decisions.
Knowledge Graphs and Machine Learning
Knowledge graphs make it easier to feed better and richer data into ML algorithms. The inherent traits of knowledge graphs posit them as a top tool of modern AI and ML strategy. Let’s examine a few ways in which they help.
How to Build a Knowledge Graph
Practical steps for building knowledge graphs: powerful tools for linked data, data integration, and data management. Scale all those use cases that have been inspired by data science. Increase your number of users, as needed. And spread the use of data itself. Do you really need a knowledge graph? Data rules the world. But organizations struggle to leverage that data for a competitive advantage. Raw, uninterpreted data in a system somewhere isn’t very helpful.
Benchmarking Needs for Enterprise Knowledge Graph Excellence (and Awe)
The tricky task of benchmarking Enterprise Knowledge Graphs—what potential clients ask for, what factors affect benchmarking, and more. A Q&A with Stardog’s CTO, Evren Sirin.