EeS Data Products and Training

“It is a capital mistake to theorize before one has data” - Arthur Conan Doyle
The number one challenge faced by businesses today is not being able to discover and consume their own data in a timely manner. Organizations need On-Demand capabilities to unlock and distribute their data. To provide access to data and make it available for consumption in a self-service manner, organizations are looking to build data assets catalog, facilitate data lineage, context and dictionaries around their data. Unlock your data with EeS data products and training for a richer data analytics and decision making experience.

    

Product: EeS EIM v1.0

The EeS Enterprise Information Management (EIM) tool offers a simple GUI driven interface to its customers which aids
in classifying and managing their data assets and facilitates building of data assets catalog. The tool focuses on
creating a standards-based hierarchical classification for your metadata, which then allows you to create a line of
sight into your data assets. This lineage can then be leveraged through our tool to facilitate self-service and easily
sub select sections of data that you need for decision making. Additionally, the tool also provides features to
import/export your current classification, mapping and data assets and generates impact reports.

Classification:

Create a customized hierarchical classification for your data. With the ability to organize your data into
Subject Areas and link across them, you can establish a line of sight that helps you find the right piece of data
at the right time.

Mapping:

Connect your data assets to your established classification to take full advantage of the line of sight you have
prepared.

Self Service:

The ability to get an insight into your connected data assets mean that you can create the dataset that you
require to have your mission running smoothly.

National Information Exchange Model:

Organize your organizational data with mappings to established data models to simplify information exchange.
Generate reports and Information Exchange Package Documents (IEPD) that help others understand your data.

EeS EIM v1.0 Features:

  • Classification and Mapping of Data
  • Seamless Connection to Data Assets
  • Self-Service via Data Assets Catalog
  • Data Dictionary for Data Assets
  • Scalable Deployments
  • Flexible API for Metadata Integration
  • Permissions Management
  • Change Impact and Other Reporting
  • Search Data Assets
  • Visualization of Data Assets Catalog
  • Data Assets Collectors
  • Import/Export and Impact Reports

EeS EIM v1.0 Benefits:

  • Optimization of Data Environment
  • Visibility of Data Architecture
  • Self-Service to Unlock Data
  • Facilitate Change using Impact Reports
  • Define Single Source of Truth
  • Data Warehousing
  • Privacy and Masking Data
  • Redefine Data Stewardship
  • Records Information Management
  • NIEM Standardization
Product: EeS NIEM PE v1.1


The EeS National Information Exchange Model (NIEM) tool offers a simple GUI driven interface to its customers which aids
in creating context to your data and helps distribute it to internal or external partners in a machine-readable format
such as XML and JSON. The product offers a version of the NIEM dictionary built into the software that can be searched
and NIEM elements mapped to the imported data assets to build information exchanges.

 

NIEM Management:

The software provides ability to search individual NIEM domains or search through all NIEM domains. It further
provides the ability to add and remove elements for easy facilitation of information exchanges with new elements.

 

Data Asset Management:

The ability to import data assets provided via CSV files. It further provides ability to view, edit, and map data
assets.

 

IEPD Life-cycle Management:

The ability to step through planning, analysis, building/loading of selection list, schema subset generation,
editing and validation.

EeS NIEM PE v1.1 Features:

  • Preloaded NIEM
  • Search/Edit NIEM
  • Import, Browse, Edit Data Assets
  • Map Data Assets to NIEM
  • Development Workspace for IEPDs
  • Full Lifecycle Support for IEPDs
  • NIEM Conformance Checks
  • Reporting
  • Built-in XML editor

EeS NIEM PE v1.1 Benefits:

  • Standard Vocabulary for Data
  • Common Context for Data
  • Persistent Data Assets to NIEM Mapping
  • Machine-Readable Data Format
  • Validate Information Exchanges
  • End-to-end Support for NIEM Processes
  • Platform Agnostic (Windows, Linux, MacOS)
  • Out of the Box Start
  • Low Cost Personal Edition
Training

National Information Exchanges Model (NIEM) 101 Training – 1 Day

Problem: Lack of context and common vocabulary makes data exchange difficult between organizations.
Outcome: NIEM common vocabulary, when used, makes data easy to understand and share with partners.
Target Audience: Business users, Information Exchange Developers, and Data Architects.

Module 1
NIEM Concepts
  • What is NIEM and its Benefits?
  • How is NIEM Structured?
  • Organization Data Assets Management
  • Mapping of Organization Data Assets to NIEM
  • Use Case and IEPD/IEP
  • How to use an IEPD/IEP?
Module 2
NIEM Management
  • Reference Schema
  • Core, Domains
  • Namespaces, Types and Properties
  • Extension Schema
Module 3
IEPD Lifecycle
  • Scenario Planning, Requirements Analysis
  • Element Mapping and Model Search and Selection
  • Want-list, Schema Subset Building and Conformance Targets
  • IEPD Assembly
Module 4
Hands-on Exercises
  • Step by Step - IEPD Development Lifecycle
  • NIEM Tools to Support IEPD Development

Enterprise Information Management 101 Training – 1 Day

Problem: Poor governance of data can cause duplicate copies, confusion and result into decision making related inefficiencies.
Outcome: Authoritative data sources and optimized data environment may provide better visibility, control of data.
Target Audience: Business and Technical personnel

Module 1
Concepts of Enterprise Data Management and its Benefits
  • Disadvantages of Stovepipe Data Management
  • Single Source of Truth, Optimization of Data Environment
  • Data Discovery, Data Stewardship, Data Privacy
  • Meta Data, Reference Data and Master Data Management
  • Data Governance, Its Benefits and Relationship to Meta Data Management
Module 2
Development of Data Taxonomy, Collection of Data Assets, Mapping of Data Assets into Data Taxonomy and Self Service
  • Development of Data Taxonomy, Collection of Data Assets, Mapping of Data Assets into Data Taxonomy and Self Service
  • Concepts of Data-Centricity, Cross Linking of Subject Areas
  • Collection of Data Assets
  • Mapping of Data Assets into Enterprise Data Taxonomy
  • Data Assets Catalog
  • Unlock Data for Decision Making as Self Service
Module 3
Modeling Concepts
  • Meta Modeling Best Practices (and EA Model)
  • Data Paradigm and its Touchpoints to Business and Technology
Module 4
Hands-on Exercises
  • Create Classification
  • Ingest Data Assets
  • Map Data Assets and generate Assets Catalog
  • Select Data Elements and Create Datasets

Big Data and Data Lakes 101 Training – 1 Day

Problem: Lack of a central place to host data can cause duplicate copies, data consistency issues.
Outcome: Build Data Lakes to integrate your enterprise solution with holistic view of data.
Target Audience: Data Architects, and Data Modelers/Analysts/Developers/Administrator.

Module 1
Big Data Concept, Tools and Technologies
  • What is Big Data? The Storage and Processing Challenge.
  • HDFS and Map Reduce
  • Data Science and New Insights
  • AI: The Road Ahead
  • Tools and Technologies
Module 2
Data Lakes, ELT and Design Considerations
  • What are Data Lakes? Why Data Lakes?
  • Important Concepts: ETL vs. ELT, Data Governance and Meta Data Management
  • Tools for Ingestion, Access and Analysis of Data
Module 3
Hands-on Exercises
  • Use Tools to Ingest Data into Hadoop Data Lake
  • Set up Access to Hadoop Data
  • Use Tools to Analyze Data in Hadoop
Module 4
Hands-on Exercises
  • Create Classification
  • Ingest Data Assets
  • Map Data Assets and generate Assets Catalog
  • Select Data Elements and Create Datasets
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