Semantic Data Fabric is a new solution to data silos that combines the best-of-breed technologies, data catalogs and knowledge graphs based on Semantic AI.
Poor data quality is the unintended consequence of data silos and poor data & analytics governance
Gartner (2019): ‘Think Big, Start Small, Be Prepared — Master Data Management’
The Challenge: Data Silos Everywhere
Business success depends heavily on the ability to make effective use of data. The first step towards this data-driven culture is data access, but many organizations have data silos that hinder this effort. Siloing data has its advantages and disadvantages. While you can maintain full control over the data and establish your own governance processes, data silos reduce speed, accuracy in reporting and data quality. A data silo owner cannot efficiently handle the full range of contexts that are potentially available to enrich his or her data.
The Need To Overcome Data Silos
Data silos present two primary challenges for enterprises:
- How to deal with existing data silos
- How to avoid creating new data silos
This is especially true when exploring Artificial Intelligence, Machine Learning and other advanced techniques rooted in data management and analysis. Siloed data often leads to re-creating knowledge that already exists but is not accessible; and worse, it can create conflicting data due to inconsistent data standards or methodologies. This leads to unnecessary costs and potential inaccuracy. Migrating and standardizing data represents primarily cost in the mechanical effort required, but also requires standard definitions and methodologies to be accurate.
A Solution To Silos
The ultimate goal is to unify unstructured, semi-structured and structured data to make all that available as if it were one database. Our approach combines the respective advantages of data lakes, data warehouses, and cloud-native data catalogs and complements them with the advanced linking methods and text mining facilities that Semantic Graph Technologies bring with them.
Gartner (2019): ‘Augmented Data Catalogs: Now an Enterprise Must-Have for Data and Analytics Leaders’
Data.world Cloud-Native Data Catalog + PoolParty Semantic Suite
Driven by a joint passion for knowledge graph technology, data.world and PoolParty, two leading metadata management platforms, have teamed up to provide a powerful solution. Businesses that leverage both products will benefit from a highly scalable, standards-based, and user-friendly business solution that meets the requirements of enterprise data management and metadata management. Both technologies are recognized in the 2019 Gartner Magic Quadrant for Metadata Management Solutions.
data.world makes it easy for everyone—not just the “data people”—to get clear, accurate, fast answers to any business question. The cloud-native enterprise data catalog collects, connects, and aligns data and metadata, creating a unified body of knowledge anyone can find, understand, and use. PoolParty uses text mining (entity extraction) and inference mechanisms to easily create and manage knowledge graphs, which can then be used for sophisticated metadata enrichment and classification tasks within data.world. Both platforms are built on graph standards such as RDF, enabling seamless integration.
The Benefit: Analytics Over Connected Metadata in a Knowledge Graph
More Value From Data
With a semantic data fabric, companies can combine text and documents (unstructured) with data residing in relational databases and data warehouses (structured) to create a much more comprehensive and accurate view of their customers, employees, products, and other vital areas of business.
Here are 3 examples of how companies can use a data fabric to extract more value from data:
Enrich your knowledge
You can find valuable unstructured information about the customer on the web, social media, and in other channels, to augment your understanding of the customer and the problem they are experiencing.
Replacing equipment can cost millions of dollars. Anticipating failure to provide life-extending maintenance and plan for replacement is essential. To accurately predict equipment failure, you need data from different observation, reporting, and maintenance systems. A data solution that understands and links text and other data across different sources can improve predictions and save businesses millions.
Not seeing the full picture of your employees’ skills and expertise costs you precious time and money. Typically, such information is siloed in HR databases, resume documents, and other disconnected systems. By combining this unstructured and structured data, you can optimize costs and boost productivity by better matching your people to problems and tasks.
Do you want more?
Learn more about Semantic Data Fabric and how to implement it in your organization in our Webinar Series.
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Awards and Recognitions
KMWorld 100 COMPANIES That Matter in Knowledge Management
KMWorld Trend-Setting Product of 2016, 2017 and 2018