Learn about using a semantic layer to enable actionable insights for everyone and streamline data and analytics access throughout your organization. This session will offer practical advice based on a decade of experience making semantic layers work for Enterprise customers. Attend this session to learn about: - Delivering critical business data to users faster than ever at scale using a semantic layer - Enabling data teams to model and deliver a semantic layer on data in the cloud. - Maintaining a single source of governed metrics and business data - Achieving speed of thought query performance and consistent KPIs across any BI/AI tool like Excel, Power BI, Tableau, Looker, DataRobot, Databricks and more. - Providing dimensional analysis capability that accelerates performance with no need to extract data from the cloud data warehouse Who should attend this session? Data & Analytics leaders and practitioners (e.g., Chief Data Officers, data scientists, data literacy, business intelligence, and analytics professionals).

1. How to Use a Semantic Layer to
Deliver Actionable Insights At Scale
Unlocking the value of your data with a Semantic Layer
Dataversity
Dave Mariani, CTO, Founder
July 26, 2022

2. 2

3. A semantic layer provides
the agility, consistency,
and control needed to
scale enterprise BI and AI
3
SL SL SL
SL
DI
SL
DI
SL
DI
SL
DI
BEFORE AFTER

4. Where does a semantic layer fit in the stack?
SEMANTIC LAYER
DATA CONSUMPTION
DATA MODELING
DATA API LAYER
DATA PREPARATION
RAW DATA
BI TOOLS AI/ML TOOLS APPLICATIONS
CLOUD DATA
WAREHOUSE
DATA LAKE
ENGINES
SAAS APIs
DATA
TRANSFORMATION
TOOLS
DATA LAKES
SAAS
APPLICATIONS
DATA
CATALOG
4

5. How
to
Use
a
Semantic
Layer
on
Big
Data
to
Drive
Al
&
BI
Impact
©
2022
AtScale.
All
rights
reserved.
How
to
Use
a
Semantic
Layer
on
Big
Data
to
Drive
Al
&
BI
Impact
©
2022
AtScale.
All
rights
reserved.
5
The Semantic Model
➔ Business Friendly
➔ Single Source of Truth
➔ Consistent Governance
➔ Performance Optimized

6. The Value of a Universal Semantic Layer
6

7. How is a
semantic layer
used?
CLOUD ANALYTICS OPTIMIZATION
Speed of thought analytics on live
cloud data, agile data integration with
minimal data movement.
ENTERPRISE METRICS STORE
Single source of governed enterprise
metrics that can be self-served from
any AI/BI tool.
BRIDGING AI AND BI
Common view of data assets and
platform for publishing AI-generated
insights to decision makers.
OLAP MODERNIZATION
Migrate legacy OLAP (e.g. SSAS)
models to modern cloud-first
infrastructure.
7

8. Demo
Source
Systems
ETL
Tools
Data
Tables
Aggregates
Data Lake
S3
XMLA
JDBC
ODBC
REST
Spark/Hive
Spectrum
MDX
Python
DAX
SQL
Data Warehouse
Platform
Semantic Layer

9. TPC-DS 10TB Benchmark: Improvements with AtScale
9
1. Elapsed time for executing 1 query five times
2. Elapsed time executing 1 (x5), 5, 25, 50 queries
3. Compute costs for cluster time (Redshift, Snowflake) or bytes read (BigQuery) for user concurrency test
4. Complexity score for SQL queries for number of: functions, operations, tables, objects & subqueries (AtScale = 258, TPC-DS = 1,057)
Test
Improvement Factor with AtScale
BigQuery Redshift Snowflake Synapse Databricks
Query Performance1
4x Faster 11x Faster 3x Faster 6x Faster 4x Faster
User Concurrency2
11x Faster 31x Faster 12x Faster 11x Faster 15x faster
Improved ROI3
3x Better 4x Better 16x Better 2x Better 6x Better
Complexity4
76% less complex SQL queries

10. www.atscale.com