By Mr. Pratik Jain, Senior Technical Architect, Kyvos Insights
Semantic layer, while not a new concept, has gained huge traction in the last couple of years in the data, analytics and BI domain. But what does a semantic layer really mean and why is it becoming increasingly important? Let’s figure it out.
A semantic layer is nothing but a layer of abstraction that simplifies complex terms into easily understandable business terms for end users. This reduces their dependency on IT or technical teams for insights. Different teams across an organization often work in silos and use different BI tools for their specific analytics needs. As each BI tool can have its own semantic layer, it often creates various versions of the same logic which leads to inconsistencies in data interpretation.
With enterprises moving to the cloud, the need for a universal semantic layer has increased now more than ever. A universal semantic layer solves the challenge of data inconsistency by getting multiple business logic from different tools in one place and changing them centrally to provide a single source of truth across the enterprise irrespective of the BI tools in use.
How Businesses Can Benefit from a Universal Semantic Layer
A universal semantic layer is one of the most important aspects of a modern data analytics tool today. With data sources growing rapidly, getting accurate insights is the need of the hour and a universal semantic layer helps enterprises achieve that while providing different business benefits. Let’s go through some of those.
Self-serve analytics for business users
Business users often need to depend on data and technical teams to make sense of their massive datasets. This dependency often keeps them from getting timely insights. Using a universal semantic layer enables them to simplify complex business logic and get a consistent, comprehensive view of all the data, without having to wait for any assistance from the technical teams. This ensures that all business users get easy, self-service access to data and use common definitions irrespective of the data source, allowing them to perform seamless self-serve analysis.
Remove data silos and get a single source of truth
Multiple departments of an enterprise tend to use different BI tools, create their own data sets and maintain their own terminology. Hence, analytics and KPI metrics from one department do not match that of another’s. As a result, there are data silos, inaccurate insights, erosion of data trust and slow business decisions. Having a universal semantic layer in place solves these challenges and delivers a single source of truth irrespective of different BI tools in place.
Lower costs on the cloud
Organizations are moving to the cloud to leverage the benefits of scalability and elasticity. However, simply making that move isn’t enough. Increasing complexities in calculations because of massively growing data volumes makes analytics extremely expensive and exhausting. In fact, if not utilized properly, businesses tend to pay more for cloud resources and yet get slow query performance.
A well-defined universal semantic layer ensures efficient data analysis on the cloud by processing or aggregating all possible combinations and using it as a base for analytics. With these price-performant, reusable querying models created, business users can simply get instant responses with reduced access to cloud data platforms, thus saving costs and query processing times.
Centralize data security and governance
A universal semantic layer is extremely important to establish data security and centralized governance policies. It can authenticate users with single sign-on solutions through user authentication platforms and provide enhanced data security with role-based data access and row and column security, where privileges can be assigned based on user roles, departments, or specific data elements. These features ensure flexibility, access control as well as security within an enterprise when analyzing growing datasets.
To summarize, in today’s paradigm of modern cloud-native BI stack, a semantic layer offers much more than just a business abstraction. It also abstracts the complexities of data blending, data silos, advanced calculations and data modelling, making it effortless for business users to derive meaningful insights with end-to-end security. It is also a gateway to unparalleled query performance, whether you’re exploring years of historical data or harnessing real-time streaming data, it ensures instant query responses.
A semantic layer is designed to deliver instant answers to user queries and exceptionally high query performance on enterprise-wide data, even with extremely high data workloads. The true power of data can only be unleashed when decision-makers have self-service, interactive and secured access to all their business data. A universal semantic layer delivers all that, enabling decision-makers to make business decisions with ease.