Title: Enterprise Data
Management:
Author: Toraj Khavari
Date: August 19, 2015
Objective: Outline a high level
introduction to Enterprise Data Management.
Article Body: Companies
large and small are moving toward Enterprise computer solutions. E.g., Asset
Management, Product Configuration (Infor), Enterprise Resource Planning system
(Dynamics AX), HR and Payroll (Ultipro), Manufacturing Execution System
(Dassault Systems), and Identity Management (EmpowerID). Enterprise computer
solutions are individual vertical information (stovepipe).
Different data sources
compiled in a common environment for analysis is the fundamental, first step
for “Data Management”. Accurate, reliable, scalable, maintainable, and high
quality information (data, reports) are paramount to continuous success and
growth.
The Enterprise
Data Management minimum requirements encompass the following items.
•
Create a reliable, scalable, enterprise solution to support
and sustain Enterprise information integrity, quality and accuracy.
•
Provide accurate and high quality business intelligence information
and reports to meet the business objectives.
•
Implement data and information governance to uphold and
support the business goals and continued growth.
Enhancing
effective and accurate business communication increases success, reduce
surprises, improves the probability of meeting the client needs, reduces
complexity and enhances quality. John
Dewey said “There is all the difference in the world between having
something to say and having to say something.” In any company, the individual
contributors have the largest exposure to the company’s processes, procedures,
and tasks. The largest scope of accurate information are available at the
individual contributors’ level. As the company management hierarchy layers are added,
the scope of information reduces. Rightfully! Supervisors, Directors, Vice
Presidents, etc. are removed from day-to-day duties. The decisions are made
based on the accurate information which is based on day-to-day duties. The raw
data must converge to information leading to decisions. The accurate and
concise information will lead to good decisions. Although raw large data sets
are important in the decision making process, good information is the basic
ingredient. Distinguish the difference between “Data” and “Information”.
Mark
Twain said “The difference between the right word and the almost right word is
the difference between lightning and a lightning bug.” A common mistake in
business communication is too much data and not enough good information. A
Centralized Repository for data facts and information to perform data analysis
and support the business goals with high quality, productivity, prosperity are
paramount to support business goals and visions.
A Business Framework runs
the company. Enterprise Architecture is a collection of Process and Data
Models. Enterprise Architecture is supported by Application Discovery and Understanding
(ADU). The ADU includes all applications solutions, fat apps, data bases, excels
and their macros, web apps, etc.
A Centralized Repository
of data by itself, commonly referred to as Data Warehouse, although a good
start, is not a complete solution. Data analysis tools play an important role
to interface with centralized data repositories. Tools justification at minimum
must include the following functions.
•
Provides
business and technical users with a single version of truth about data and
systems across the enterprise
•
Maintains
a scalable, open architecture to facilitate growth as an organization’s needs
change
•
Provides
global impact, gap, and integration analysis
•
Offers
a transparent regulatory audit trail and enables corporate governance of
information
•
Presents
information according to end-user preferences, including language, graphical
and textual formats, and business vs. technical detail
•
Automates
the capture and integration of metadata context across the organization
•
Enables
integrated views across custom developed and packaged application systems (such
as AX, Infor, UltiPro, Dassault Systems, etc.)
•
Provides
source-to-target data lineage and transformation context across the enterprise
•
Models
and relates “anything-to-anything”
•
Provides
Web-based read/write access to all metadata with graphical and textual views
•
Integrates
with any existing application through Web Services, XML, and/or a range of open
APIs (Application Program Interfaces)
•
Provides
sophisticated version and configuration management
•
Supports
standards such as Common Warehouse Metamodel (CWM)
•
Provides
a powerful metadata management system that supports both business and technical
metadata throughout the enterprise. It provides a common user interface
semantically across different solution collections and systems, regardless of
Data Base type.
Let us put all of the
above in a practical application. The company’s president and Sr. Management
describe a business objective. Vice President of Finance, Controller, and
management team establish processes and audits to meet the business objective,
while accepting, rejecting, or enhancing the business framework. Metadata
Repository is the centralized data warehouse supporting the business framework.
Information services architects align technologies and data to meet the
business objective. Sales and Dealers, Manufacturing, and other departments are
subscribers of business framework,
Enterprise Data
Management is the ability of a business to precisely define, easily integrate
and effectively retrieve data for both internal applications and external
communication. Make the implementation of Enterprise Data Warehouse stepwise, evolutionary,
and methodical while focusing on business priorities. Strategize and consider
tools to interface with Data Warehouse. Make it easy, fun, and impactful.
Enjoy high tech and
enterprise solutions.
References:
