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Data engineers and analysts are at the forefront of creating and managing the data stack, which means they are at the forefront of solving the enterprise’s data chaos. Data chaos comes from the staggering number of data tools people use and the expectations that those tools will generate the same answers (this is rarely true).
The answer? Leverage a semantic layer to reduce data chaos.
But why is it important? The importance of semantic layers
Semantic layers play a fundamental role in data analysis. They act as bridges between raw data and actionable insights, helping organizations realize the full potential of their data. A semantic layer consolidates complex data into an understandable format across different teams and tools, effectively translating raw data into standard business terms.
Read GigaOm Sonar’s report on semantic layers
This recently published GigaOm report focuses on emerging technologies and market segments. It helps organizations of all sizes understand new technologies, their strengths, their weaknesses, and how they can fit into an overall technology strategy. The report is organized into five sections:
- General description: An overview of the technology, its main benefits and possible use cases, as well as an exploration of product implementations already available on the market.
- Considerations for adoption: An analysis of the potential risks and benefits of introducing products based on this technology in a business scenario. It analyzes the issues at stake and key differentiating features, as well as considerations for how to integrate the new product into the existing environment.
- GigaOm probe table: A graphic representation of the market and its most important players, focused on its value proposition and its future roadmap.
- Supplier information: A breakdown of each vendor’s offering in the sector, scored on key features for enterprise adoption.
- Short-term roadmap: A 12 to 18 month forecast of the future development of the technology, its ecosystem and the main players in this market segment.
Semantic layers are not independent entities but complementary components of a powerful data ecosystem. Semantic layers provide the context and structure necessary to understand the data.
Cube stands out in the GigaOm Sonar Report as a leader and fast mover. They noted that Cube’s strengths include a strong code-first orientation, native API support, and its analytical preprocessing through caching and pre-aggregations.
Get the full report and see for yourself
For a complete look at Cube’s performance and a deeper dive into the world of semantic layers, we recommend reading the full GigaOm Sonar report. We offer the report here for free..