Working with Semantic Models

Applies to: Kyvos Enterprise  Kyvos Cloud (SaaS on AWS) Kyvos AWS Marketplace

Kyvos Azure Marketplace   Kyvos GCP Marketplace Kyvos Single Node Installation (Kyvos SNI)

Once you have created relationships within the dataset, you can create a semantic model. When you define a semantic model, you specify the dimensions and measures and the types of pre-calculated aggregations it will contain.

Design and process a semantic model in three steps

You need to perform a few steps to design and process a semantic model. These are, of course, a one-time thing; once the designer builds these, the business users can use the data as often as they need.

Once you've completed the basic design, you can refine the semantic model by defining the partition, aggregation, and auto cache strategies and setting advanced properties. Then you can schedule the process, get recommendations, analyze queries, review build summaries or data profile results, manage build instances, or add other jobs such as data profile or cache job.

• Step 1: Define Semantics
  In this step, you prepare a physical design of a cube. To do this, you add dimensions, measures, and the types of pre-calculated aggregations it will contain.

• Step 2: Refine Model
  In this step, you refine the semantic model by defining the partition, aggregation, auto cache strategies, and setting advanced properties. 

• Step 3: Process
  In this step, you build the semantic model. To do this, you need to specify semantic model build types, such as full data process, incremental data process, test data process, and the schedule when you want to trigger the process. 

Kyvos semantic model design and process page 

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Before you get started

Before you create a semantic model, you may need to know about the schema, which describes how the tables are arranged in the database. Star, snowflake, multi fact, and single file schemas are common types you will encounter. They are different arrangements of facts (business data) and dimensions (the records in the fact table - for example, information about specific products or customers). A semantic model aggregates facts from various levels of a dimension provided in a schema. For example, you may have data about products, units sold, and sales amounts and match them up by date (month, quarter), store, salesperson, or other combinations.

Kyvos allows you to create a data profile that provides guidance for semantic model design. Additionally, Kyvos provides semantic model recommendations to optimize the semantic model based on historical query data and the data profile. You can calculate aggregates when you do the semantic model build to reduce query times. 

You can also analyze queries created on the cube. The results are displayed in a dashboard in a separate tab in the browser. You can view query performance data and lists of mostly used dimensions and measures to aid you in optimizing your semantic model design.

Related topics

• Creating a data profile