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Anzo Smart Data Lake 4.0 Bootcamp

To coincide with our 4.0 product release, Cambridge Semantics is pleased to announce Anzo Smart Data Lake 4.0 Bootcamp Training. This training covers the core concepts of Anzo and focuses on the new innovative features of ASDL 4.0. Participants will learn how to ingest data from various sources and auto-generate ontologies, navigate the catalog of Anzo objects generated, and visualize insights using our HiRes Analytics interface.

As the name implies, Anzo Bootcamp is an intensive 8-hour course that includes 4 instructor-led sessions, each accompanied by a hands-on lab. Courses will be delivered once a month via GotoMeeting.

Next Course Date/ Time: Now enrolling for the Friday, November 17th session (8 am – 5 pm ET).

Course Cost: $1,500 per student

Course Overview: The course begins by arming students with foundational semantic technology concepts and why Anzo leverages them. The introductory module places particular emphasis on comparing and contrasting semantic technologies with relational databases and traditional data lake technologies through illustrative examples. With these concepts in place, participants perform standard data management activities leveraging each of the Anzo platform components, including:

Data Modeling (creating and editing ontologies)
Automated ingestion of data from structured sources
Preparing data for export to BI tools
Knowledge Discovery through exploratory analytics and visualization of diverse harmonized data
Instructor-led modules and labs leverage a common, complex but intuitive dataset that illustrates the power of the graph model and how data is harmonized. Labs are provisioned in the cloud for each student and can be made available to participants after the course for continued work against lab exercises and the exploration of other features.

Course Package: The course package comprises a cloud instance for lab exercises and a Lab Guide. Extended time within the cloud provisioned lab environment is available. The Lab Guide offers step-by-step instructions to participants to perform hands-on lab exercises and reinforces key concepts on topics covered in the instructor-led modules.

Duration: 8 hours via GoToMeeting.

Prerequisites: This class is designed for beginner to intermediate audiences. Resources are available on our website for participants who wish to explore Anzo in advance. Participants are expected to have at least basic familiarity with data management workflow and analysis. Prior exposure to data analysis tools is helpful.

Course Objectives: At the end of this class, you will be able to:

Develop an understanding and appreciation of how ASDL can enable you to perform extensive knowledge discovery through harmonization of diverse data
Address common business analytic use cases
Build a complex ontology that meet your business
Automatically ingest and structured data
Publish advanced visualizations to analytic users
Integrate Anzo with other analytic and machine learning tools

Course Structure: The course comprises instructor-led modules and corresponding lab modules.

Module 1: Overview of Anzo Smart Data Lake

Overview of ASDL
Why ASDL Uses Semantic Technologies
Overview of Key Concepts Enabling ASDL
Data modeling (model creation)
Lab 1: Structured Data Ingestion

Demonstration of automated structured data ingestion
Lab exercise: Commence auto ingestion of a relational database and a CSV
Module 2: The Catalog and Anzo Objects

Overview of ASDL Menu Items
Function of each menu item
Sample applications and examples
Lab 2: ASDL Catalog Exploration

Tutorial on ingesting structured data
Lab exercise: Exploring each sub menu item of ASDL Catalog to develop deep understanding of the ingested data and available resources for data management
Module 3: Ingestion and HiRes Analytics

Overview of structured data ingestion
Overview of HiRes analytics
Best practices and solutions approach
Lab 3: Building Dashboards for Exploratory Analysis

Demonstration of data harmonization
Tutorial on graph traversal
Tutorial on building lenses and dashboards
Lab exercise: Complete the data ingestion process. Answer a dataset-based exploratory analysis question
Module 4: ASDL Practice Ideas

Workflow ideas for ASDL deployment
Key considerations for workflow selection
Lab 4: Data Layers and HiRes Analytics Deep Dive

Tutorial on Data Layers
Lab exercise: Perform HiRes Analytics to answer knowledge discovery-driven questions
To register for this course, simply fill out the form below and we will be in touch shortly to complete the registration process.