Data management expert Artyom Keydunov discusses building a semantic layer for data sources to solve challenges of data silos and access control. The podcast explores the benefits of Cube as an interface for unified data governance and integration, hosted by Lee Atchison, a software architect and cloud computing thought leader.
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Quick takeaways
Building a semantic layer over heterogeneous data sources enables governance and access control for unified data access.
Cube's approach addresses data silos by focusing on metric definitions to improve data quality and consistency.
Deep dives
Challenge of Data Management
Managing data and access to data is a significant challenge for companies. Data often exists in siloed sources, making unified access difficult. Building a semantic layer on top of heterogeneous data sources can address this by providing a governance and access control interface. Cube, a semantic layer between data sources and applications, aims to streamline data access. This approach facilitates data governance and control.
Data Silo Definition
Data silos are standalone data sources holding interrelated data. The problem extends beyond just raw data to include data definition and metric silos. The Cube platform addresses nuances like metric definitions to ensure data integrity and consistency. This enhanced definition of data silos includes understanding how data is defined and used, improving overall data quality.
Data Silos Impact on Decision Making
Data silos hinder organizations from becoming truly data-driven by creating disconnected data views and definitions. The challenge lies in maintaining data accuracy and consistency across various data touchpoints. This repetition problem parallels the 'do not repeat yourself' principle in software engineering, underlining the complexity of managing disparate data sources and definitions.
Implementation of Semantic Layer
A semantic layer acts as a bridge between business metrics and underlying data structures, facilitating a common understanding of data across business intelligence tools. Cube offers a universal semantic layer to centralize data definitions, enabling consistent data access and governance. By abstracting data definitions, Cube simplifies data access and enhances data model management, ensuring data consistency and accuracy across tools.
Managing data and access to data is one of the biggest challenges that a company can face. It’s common for data to be siloed into independent sources that are difficult to access in a unified and integrated way.
One approach to solving this problem is to build a layer on top of the heterogenous data sources. This layer can serve as an interface for the data and provide governance and access control.
Cube is a semantic layer between the data source and data applications. Artyom Keydunov is the founder of Cube and he joins the show to talk about the approach Cube is taking.
This episode is hosted by Lee Atchison. Lee Atchison is a software architect, author, and thought leader on cloud computing and application modernization. His best-selling book, Architecting for Scale (O’Reilly Media), is an essential resource for technical teams looking to maintain high availability and manage risk in their cloud environments.
Lee is the host of his podcast, Modern Digital Business, an engaging and informative podcast produced for people looking to build and grow their digital business with the help of modern applications and processes developed for today’s fast-moving business environment. Listen at mdb.fm. Follow Lee at softwarearchitectureinsights.com, and see all his content at leeatchison.com.