This document provides an overview and introduction to Cambridge Semantics Inc. and their Anzo Smart Data Platform for building smart data lakes using semantics. Key points include: - Cambridge Semantics was founded in 2007 and their Anzo software suite uses open semantic web standards to create data analytics and management solutions from diverse data sources. - While data lakes make it easy to assemble large volumes of data, identifying and linking data across sources remains challenging without harmonization of meanings. Semantic models and tools can help address these issues. - The Anzo Analytics and Data Integration Suite uses business understandable semantic models to describe, search, query and analyze data from various structured and unstructured sources to build a smart data lake.

1. ©2015 Cambridge Semantics Inc. All rights reserved.
How to Build a Smart Data Lake™
Using Semantics
Presenters:
Marty Loughlin, Vice President
Curt Wright, Director Engineering
Cambridge Semantics Contact:
Marty Loughlin
Vice President
Cambridge Semantics
141 Tremont St., 6th Floor, Boston, MA
www.cambridgesemantics.com
marty@cambridgesemantics.com
(o) 617.855.9565

2. ©2015 Cambridge Semantics Inc. All rights reserved. Page 2
Introduction to Cambridge Semantics Inc (CSI)
The Anzo Smart Data Platform is used to create data analytics and
management solutions with diverse data from varied sources
Company:
 Founded in 2007 by senior team from IBM’s Advanced Internet Technology Group
 Complemented by database team responsible for Netezza & ParAccel
Software:
 Market leading Anzo software suite is built on open Semantic Web standards
 Currently 3rd generation of the product in production use
Business Intelligence /
Analytics Solutions
2013(Winner) 2014(Finalist)
2015(Finalist)
2014 Innovation Showcase

3. ©2015 Cambridge Semantics Inc. All rights reserved. Page 3
The State of the Data Lake
• Great way to rapidly and inexpensively assemble large volumes of unfiltered data
• However, challenging to identify and link data
• Getting value requires harmonization of meaning across diverse sources and making it
accessible to business users
• And, you also need good data governance, quality, lineage and security
Leading organizations are looking to Semantic Models and
Tools to address these challenges
Source: 2015 EDM Council Benchmarking Study

4. ©2015 Cambridge Semantics Inc. All rights reserved. Page 4
Why Semantic Models & Tools?
• Semantic models enable harmonization of data through
common business meaning
• Model driven transformation enables active meta data
management
• Business analyst tools for cataloging, harmonizing, transforming,
discovering and analyzing data
• Agile, flexible and adaptable to new requirements

5. ©2015 Cambridge Semantics Inc. All rights reserved. Page 5
Anzo Analytics and Data Integration Suite
Reference
Data
Holdings
Data
Trading
Data
Source Data
Map & Load Link & Query

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• Business understandable models describe
data and transformations
• Searchable Catalog of Data Sources, Maps
& Metadata
• Query model for data lineage, impact
analysis, data quality
Anzo Smart Data Lake
Anzo Smart Data Integration Server
Anzo Enterprise Server
• Standardized reports and self-service data
discovery for diverse use cases
• Data curation, annotation and application
workflow
Anzo Graph Query Engine
• Load, transform and harmonize diverse
internal and external data sources
• Link to business meaning (e.g., FIBO)
Data Store
Third party
BI/Analytics
Data ProvidersStructured Sources Unstructured
Sources

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Build a Smart Data Lake with
Anzo Smart Data Integration Server
• Register sources & capture configurable metadata
• Automatically retrieve/create schema and sample data
• Supports databases (JDBC), CSV, TSV, Hadoop HDFS, RDF
• Smart mapper based on familiar Excel interface
• Supports mapping and transformation
• Create jobs by combining maps
• Generate code for Apache Spark, Informatica, Pentaho
• Ingest data or transform in lake
• Self-service data catalog and in-memory analytics
• Data Lineage
• Configurable model driven reports and analytics
1. Catalog
Sources
2. Map Data
3. Load, Link,
Transform
4. Self-Service
Analytics

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