What is involved in data centric training model
Find out what the related areas are that data centric training model connects with, associates with, correlates with or affects, and which require thought, deliberation, analysis, review and discussion. This unique checklist stands out in a sense that it is not per-se designed to give answers, but to engage the reader and lay out a data centric training model thinking-frame.
How far is your company on its data centric training model journey?
Take this short survey to gauge your organization’s progress toward data centric training model leadership. Learn your strongest and weakest areas, and what you can do now to create a strategy that delivers results.
To address the criteria in this checklist for your organization, extensive selected resources are provided for sources of further research and information.
Start the Checklist
Below you will find a quick checklist designed to help you think about which data centric training model related domains to cover and 172 essential critical questions to check off in that domain.
The following domains are covered:
data centric training model, Transaction log, Distributed computing, Concurrency control, U.S. Environmental Protection Agency, Decision support system, Apollo program, Data transformation, Mobile database, Log shipping, Business System 12, Cincom Systems, Unstructured data, Two-phase commit protocol, American National Standards Institute, Operational data store, User interface, Operational database, Data vault modeling, data centric training model, Human resources, Physical security, Bibliographic database, Anchor Modeling, Halloween Problem, Main memory, Computer data storage, C. Wayne Ratliff, Knowledge management, Database trigger, Slowly changing dimension, Object-oriented programming, Query plan, Conceptual data model, Apache Cassandra, Materialized view, Database engine, Technical standard, Computer network, Character encoding, Deductive database, Journal of Database Management, Database refactoring, Network model, Extract, transform, load, Universal Product Code, Data dictionary, Codd’s 12 rules, Database log, Computer software, Fault tolerance, Associative model of data, Stored procedure, Database transaction, Create, read, update and delete, Column-oriented DBMS, Surrogate key, Multivalue model:
data centric training model Critical Criteria:
Chart data centric training model management and do something to it.
– What tools do you use once you have decided on a data centric training model strategy and more importantly how do you choose?
– How will you know that the data centric training model project has been successful?
– How can the value of data centric training model be defined?
Transaction log Critical Criteria:
Steer Transaction log issues and visualize why should people listen to you regarding Transaction log.
– What are specific data centric training model Rules to follow?
– How would one define data centric training model leadership?
Distributed computing Critical Criteria:
Scan Distributed computing projects and probe using an integrated framework to make sure Distributed computing is getting what it needs.
– what is the best design framework for data centric training model organization now that, in a post industrial-age if the top-down, command and control model is no longer relevant?
– Meeting the challenge: are missed data centric training model opportunities costing us money?
– Which data centric training model goals are the most important?
Concurrency control Critical Criteria:
Audit Concurrency control risks and change contexts.
– What are the key elements of your data centric training model performance improvement system, including your evaluation, organizational learning, and innovation processes?
– What are all of our data centric training model domains and what do they do?
– What are the business goals data centric training model is aiming to achieve?
U.S. Environmental Protection Agency Critical Criteria:
Detail U.S. Environmental Protection Agency engagements and do something to it.
– How do you determine the key elements that affect data centric training model workforce satisfaction? how are these elements determined for different workforce groups and segments?
– What is the total cost related to deploying data centric training model, including any consulting or professional services?
– What are current data centric training model Paradigms?
Decision support system Critical Criteria:
Co-operate on Decision support system results and balance specific methods for improving Decision support system results.
– At what point will vulnerability assessments be performed once data centric training model is put into production (e.g., ongoing Risk Management after implementation)?
– A heuristic, a decision support system, or new practices to improve current project management?
– Do data centric training model rules make a reasonable demand on a users capabilities?
– How do we Lead with data centric training model in Mind?
Apollo program Critical Criteria:
Analyze Apollo program failures and create a map for yourself.
Data transformation Critical Criteria:
Consult on Data transformation engagements and balance specific methods for improving Data transformation results.
– Think about the people you identified for your data centric training model project and the project responsibilities you would assign to them. what kind of training do you think they would need to perform these responsibilities effectively?
– Among the data centric training model product and service cost to be estimated, which is considered hardest to estimate?
– Risk factors: what are the characteristics of data centric training model that make it risky?
– Describe the process of data transformation required by your system?
– What is the process of data transformation required by your system?
Mobile database Critical Criteria:
Unify Mobile database goals and be persistent.
Log shipping Critical Criteria:
Reconstruct Log shipping decisions and report on setting up Log shipping without losing ground.
– Do we cover the five essential competencies-Communication, Collaboration,Innovation, Adaptability, and Leadership that improve an organizations ability to leverage the new data centric training model in a volatile global economy?
– Are there data centric training model Models?
Business System 12 Critical Criteria:
Prioritize Business System 12 tasks and correct better engagement with Business System 12 results.
– Who is the main stakeholder, with ultimate responsibility for driving data centric training model forward?
– What tools and technologies are needed for a custom data centric training model project?
– What are the record-keeping requirements of data centric training model activities?
Cincom Systems Critical Criteria:
Do a round table on Cincom Systems management and work towards be a leading Cincom Systems expert.
– Who will be responsible for documenting the data centric training model requirements in detail?
– Are accountability and ownership for data centric training model clearly defined?
Unstructured data Critical Criteria:
Study Unstructured data risks and document what potential Unstructured data megatrends could make our business model obsolete.
– What tools do you consider particularly important to handle unstructured data expressed in (a) natural language(s)?
– What role does communication play in the success or failure of a data centric training model project?
– Does your organization have the right tools to handle unstructured data expressed in (a) natural language(s)?
– How to Secure data centric training model?
Two-phase commit protocol Critical Criteria:
Brainstorm over Two-phase commit protocol leadership and be persistent.
– How do mission and objectives affect the data centric training model processes of our organization?
– Think of your data centric training model project. what are the main functions?
– How do we Identify specific data centric training model investment and emerging trends?
American National Standards Institute Critical Criteria:
Prioritize American National Standards Institute failures and research ways can we become the American National Standards Institute company that would put us out of business.
– Who is responsible for ensuring appropriate resources (time, people and money) are allocated to data centric training model?
– What new services of functionality will be implemented next with data centric training model ?
Operational data store Critical Criteria:
Map Operational data store projects and frame using storytelling to create more compelling Operational data store projects.
– What may be the consequences for the performance of an organization if all stakeholders are not consulted regarding data centric training model?
– How can we improve data centric training model?
User interface Critical Criteria:
Administer User interface quality and handle a jump-start course to User interface.
– What if we substitute prototyping for user interface screens on paper?
– What are the usability implications of data centric training model actions?
– Does a User interface survey show which search ui is better ?
Operational database Critical Criteria:
Investigate Operational database outcomes and inform on and uncover unspoken needs and breakthrough Operational database results.
– For your data centric training model project, identify and describe the business environment. is there more than one layer to the business environment?
– What are our data centric training model Processes?
Data vault modeling Critical Criteria:
Align Data vault modeling planning and know what your objective is.
– Record-keeping requirements flow from the records needed as inputs, outputs, controls and for transformation of a data centric training model process. ask yourself: are the records needed as inputs to the data centric training model process available?
– What prevents me from making the changes I know will make me a more effective data centric training model leader?
– What sources do you use to gather information for a data centric training model study?
data centric training model Critical Criteria:
Weigh in on data centric training model failures and explain and analyze the challenges of data centric training model.
– Which customers cant participate in our data centric training model domain because they lack skills, wealth, or convenient access to existing solutions?
– What are the success criteria that will indicate that data centric training model objectives have been met and the benefits delivered?
Human resources Critical Criteria:
Wrangle Human resources issues and grade techniques for implementing Human resources controls.
– Who will be responsible for leading the various bcp teams (e.g., crisis/emergency, recovery, technology, communications, facilities, Human Resources, business units and processes, Customer Service)?
– If there is recognition by both parties of the potential benefits of an alliance, but adequate qualified human resources are not available at one or both firms?
– What finance, procurement and Human Resources business processes should be included in the scope of a erp solution?
– Should pay levels and differences reflect what workers are used to in their own countries?
– Does the cloud service provider have necessary security controls on their human resources?
– What are strategies that we can undertake to reduce job fatigue and reduced productivity?
– To satisfy our customers and stakeholders, what financial objectives must we accomplish?
– Where can an employee go for further information about the dispute resolution program?
– Is the crisis management team comprised of members from Human Resources?
– What is the important thing that human resources management should do?
– Are there types of data to which the employee does not have access?
– To achieve our goals, how must our organization learn and innovate?
– What steps are taken to promote compliance with the hr principles?
– Does all hr data receive the same level of security?
– Does the hr plan make sense to our stakeholders?
– How is Promptness of returning calls or e-mail?
– What does the pyramid of information look like?
– What are the data sources and data mix?
– How do we engage the stakeholders?
– Can you trust the algorithm?
Physical security Critical Criteria:
Chart Physical security quality and create a map for yourself.
– Are there multiple physical security controls (such as badges, escorts, or mantraps) in place that would prevent unauthorized individuals from gaining access to the facility?
– Are information security policies, including policies for access control, application and system development, operational, network and physical security, formally documented?
– Does your Cybersecurity plan contain both cyber and physical security components, or does your physical security plan identify critical cyber assets?
– Has Cybersecurity been identified in the physical security plans for the assets, reflecting planning for a blended cyber/physical attack?
– Secured Offices, Rooms and Facilities: Are physical security for offices, rooms and facilities designed and applied?
– Is the security product consistent with physical security and other policy requirements?
Bibliographic database Critical Criteria:
Adapt Bibliographic database adoptions and integrate design thinking in Bibliographic database innovation.
– Do we aggressively reward and promote the people who have the biggest impact on creating excellent data centric training model services/products?
– Do we monitor the data centric training model decisions made and fine tune them as they evolve?
– To what extent does management recognize data centric training model as a tool to increase the results?
Anchor Modeling Critical Criteria:
Devise Anchor Modeling outcomes and cater for concise Anchor Modeling education.
– Have the types of risks that may impact data centric training model been identified and analyzed?
– Why should we adopt a data centric training model framework?
Halloween Problem Critical Criteria:
Graph Halloween Problem goals and find out what it really means.
– Are assumptions made in data centric training model stated explicitly?
Main memory Critical Criteria:
Learn from Main memory engagements and define what our big hairy audacious Main memory goal is.
– Is maximizing data centric training model protection the same as minimizing data centric training model loss?
– Does our organization need more data centric training model education?
– How can skill-level changes improve data centric training model?
Computer data storage Critical Criteria:
Look at Computer data storage risks and find answers.
– Does data centric training model systematically track and analyze outcomes for accountability and quality improvement?
– Is the data centric training model organization completing tasks effectively and efficiently?
– What are the Key enablers to make this data centric training model move?
C. Wayne Ratliff Critical Criteria:
Study C. Wayne Ratliff quality and define what our big hairy audacious C. Wayne Ratliff goal is.
– Can we do data centric training model without complex (expensive) analysis?
– What is Effective data centric training model?
Knowledge management Critical Criteria:
Chat re Knowledge management tasks and get out your magnifying glass.
– Learning Systems Analysis: once one has a good grasp of the current state of the organization, there is still an important question that needs to be asked: what is the organizations potential for developing and changing – in the near future and in the longer term?
– What will be the consequences to the business (financial, reputation etc) if data centric training model does not go ahead or fails to deliver the objectives?
– What are the best practices in knowledge management for IT Service management ITSM?
– What best practices in knowledge management for Service management do we use?
– How do we manage data centric training model Knowledge Management (KM)?
– When is Knowledge Management Measured?
– How is Knowledge Management Measured?
Database trigger Critical Criteria:
Think about Database trigger planning and define what our big hairy audacious Database trigger goal is.
– What will drive data centric training model change?
Slowly changing dimension Critical Criteria:
Test Slowly changing dimension management and differentiate in coordinating Slowly changing dimension.
– Who will be responsible for making the decisions to include or exclude requested changes once data centric training model is underway?
Object-oriented programming Critical Criteria:
Demonstrate Object-oriented programming strategies and observe effective Object-oriented programming.
– What are our needs in relation to data centric training model skills, labor, equipment, and markets?
Query plan Critical Criteria:
Sort Query plan visions and spearhead techniques for implementing Query plan.
– What is the source of the strategies for data centric training model strengthening and reform?
Conceptual data model Critical Criteria:
Revitalize Conceptual data model tactics and learn.
– In what ways are data centric training model vendors and us interacting to ensure safe and effective use?
– How do we Improve data centric training model service perception, and satisfaction?
Apache Cassandra Critical Criteria:
Be responsible for Apache Cassandra tasks and question.
– While a move from Oracles MySQL may be necessary because of its inability to handle key big data use cases, why should that move involve a switch to Apache Cassandra and DataStax Enterprise?
– Will new equipment/products be required to facilitate data centric training model delivery for example is new software needed?
– How can you measure data centric training model in a systematic way?
– How do we go about Securing data centric training model?
Materialized view Critical Criteria:
Judge Materialized view projects and define Materialized view competency-based leadership.
– Are there recognized data centric training model problems?
Database engine Critical Criteria:
Accumulate Database engine issues and slay a dragon.
– How likely is the current data centric training model plan to come in on schedule or on budget?
Technical standard Critical Criteria:
Deliberate Technical standard tactics and improve Technical standard service perception.
– What are the Essentials of Internal data centric training model Management?
Computer network Critical Criteria:
Have a session on Computer network adoptions and define what our big hairy audacious Computer network goal is.
– Does data centric training model analysis show the relationships among important data centric training model factors?
– What are the top 3 things at the forefront of our data centric training model agendas for the next 3 years?
– Is the illegal entry into a private computer network a crime in your country?
Character encoding Critical Criteria:
Jump start Character encoding goals and acquire concise Character encoding education.
– What are the short and long-term data centric training model goals?
– Is Supporting data centric training model documentation required?
– What is our formula for success in data centric training model ?
Deductive database Critical Criteria:
Devise Deductive database adoptions and probe using an integrated framework to make sure Deductive database is getting what it needs.
– What is our data centric training model Strategy?
Journal of Database Management Critical Criteria:
Match Journal of Database Management strategies and assess and formulate effective operational and Journal of Database Management strategies.
– Why is it important to have senior management support for a data centric training model project?
Database refactoring Critical Criteria:
Be responsible for Database refactoring governance and proactively manage Database refactoring risks.
– Will data centric training model have an impact on current business continuity, disaster recovery processes and/or infrastructure?
– Do you monitor the effectiveness of your data centric training model activities?
Network model Critical Criteria:
Derive from Network model quality and explain and analyze the challenges of Network model.
– How do we make it meaningful in connecting data centric training model with what users do day-to-day?
– How much does data centric training model help?
Extract, transform, load Critical Criteria:
Check Extract, transform, load outcomes and gather Extract, transform, load models .
– A compounding model resolution with available relevant data can often provide insight towards a solution methodology; which data centric training model models, tools and techniques are necessary?
– Is data centric training model Required?
Universal Product Code Critical Criteria:
Be clear about Universal Product Code engagements and probe the present value of growth of Universal Product Code.
– What other jobs or tasks affect the performance of the steps in the data centric training model process?
Data dictionary Critical Criteria:
Familiarize yourself with Data dictionary engagements and correct Data dictionary management by competencies.
– How will we insure seamless interoperability of data centric training model moving forward?
– Is data centric training model Realistic, or are you setting yourself up for failure?
– What types of information should be included in the data dictionary?
– Is there a data dictionary?
Codd’s 12 rules Critical Criteria:
Categorize Codd’s 12 rules outcomes and find the ideas you already have.
Database log Critical Criteria:
Inquire about Database log strategies and interpret which customers can’t participate in Database log because they lack skills.
– In the case of a data centric training model project, the criteria for the audit derive from implementation objectives. an audit of a data centric training model project involves assessing whether the recommendations outlined for implementation have been met. in other words, can we track that any data centric training model project is implemented as planned, and is it working?
– In a project to restructure data centric training model outcomes, which stakeholders would you involve?
– What is the purpose of data centric training model in relation to the mission?
Computer software Critical Criteria:
Review Computer software quality and pay attention to the small things.
– What are our best practices for minimizing data centric training model project risk, while demonstrating incremental value and quick wins throughout the data centric training model project lifecycle?
– When a data centric training model manager recognizes a problem, what options are available?
Fault tolerance Critical Criteria:
Accommodate Fault tolerance quality and stake your claim.
– What are the fault tolerance, failover, and disaster recovery plans?
Associative model of data Critical Criteria:
Reorganize Associative model of data failures and stake your claim.
– What business benefits will data centric training model goals deliver if achieved?
Stored procedure Critical Criteria:
Graph Stored procedure strategies and track iterative Stored procedure results.
– What are your key performance measures or indicators and in-process measures for the control and improvement of your data centric training model processes?
Database transaction Critical Criteria:
Consider Database transaction tasks and test out new things.
– What are the barriers to increased data centric training model production?
Create, read, update and delete Critical Criteria:
Analyze Create, read, update and delete strategies and slay a dragon.
– Who will provide the final approval of data centric training model deliverables?
Column-oriented DBMS Critical Criteria:
Exchange ideas about Column-oriented DBMS strategies and check on ways to get started with Column-oriented DBMS.
Surrogate key Critical Criteria:
Conceptualize Surrogate key planning and maintain Surrogate key for success.
– Are we Assessing data centric training model and Risk?
Multivalue model Critical Criteria:
Collaborate on Multivalue model tasks and differentiate in coordinating Multivalue model.
– How is the value delivered by data centric training model being measured?
This quick readiness checklist is a selected resource to help you move forward. Learn more about how to achieve comprehensive insights with the data centric training model Self Assessment:
Author: Gerard Blokdijk
CEO at The Art of Service | http://theartofservice.com
Gerard is the CEO at The Art of Service. He has been providing information technology insights, talks, tools and products to organizations in a wide range of industries for over 25 years. Gerard is a widely recognized and respected information expert. Gerard founded The Art of Service consulting business in 2000. Gerard has authored numerous published books to date.
To address the criteria in this checklist, these selected resources are provided for sources of further research and information:
Transaction log External links:
Shrinking the Transaction Log – technet.microsoft.com
Transaction Log In – tponlinepay.com
Recover from a full transaction log in a SQL Server database
Distributed computing External links:
What is distributed computing? – Definition from WhatIs.com
Concurrency control External links:
Concurrency Control | Database Management | FANDOM …
AdvDB: Concurrency Control Flashcards | Quizlet
Types of Concurrency Control
U.S. Environmental Protection Agency External links:
U.S. Environmental Protection Agency – YouTube
Contact EPA | U.S. Environmental Protection Agency | US EPA
U.S. Environmental Protection Agency – Home | Facebook
Decision support system External links:
[PDF]Appendix N Wildland Fire Decision Support System …
Decision Support System – DSS – Investopedia
North Carolina Accounting System Decision Support System
Apollo program External links:
Most Popular “Apollo Program” Titles – IMDb
Apollo Program | National Air and Space Museum
Apollo Program (eVideo, 2011) [WorldCat.org]
Mobile database External links:
T-Mobile database hacked: How did it happen? – USA TODAY
[PDF]Mobile Database – University of Illinois at Chicago
Log shipping External links:
How to: Remove Log Shipping (Transact-SQL)
How to configure security for SQL Server log shipping
Business System 12 External links:
Business System 12 (BS12) – www.mcjones.org
BS12 – Business System 12 | AcronymFinder
How is Business System 12 abbreviated? – TheFreeDictionary
Cincom Systems External links:
Cincom Systems – Home | Facebook
Cincom Systems – Google+
About Cincom – Cincom Systems
Unstructured data External links:
What is Unstructured Data? – Datamation
Two-phase commit protocol External links:
Two-phase commit protocol – YouTube
Two-phase commit protocol | Thoughts from James H. Lui
The Two-Phase Commit Protocol – Undergraduate Courses
American National Standards Institute External links:
ANSI – American National Standards Institute – EDI Basics
Operational data store External links:
[PDF]Banner Operational Data Store – Software and Services …
Operational Data Store (ODS) Defined | James Serra’s Blog
User interface External links:
Portal Web Mail User Interface – MyCopper.net
Datatel User Interface 5.4
What is User Interface (UI)? Webopedia Definition
Operational database External links:
How to Move the Operational Database | Microsoft Docs
Operational Database | Cloudera
Magic Quadrant for Operational Database Management …
Data vault modeling External links:
Data Vault Modeling Methodology Jobs, Employment | …
What is DATA VAULT MODELING? What does DATA …
Data Vault Modeling and Snowflake | Snowflake
Human resources External links:
Human Resources Job Titles – The Balance
Title Human Resources HR Jobs, Employment | Indeed.com
myDHR | Maryland Department of Human Resources
Physical security External links:
Army COOL Summary – ASI H3 – Physical Security Operations
ADC LTD NM Leader In Personnel & Physical Security
Bibliographic database External links:
Bibliographic database – New World Encyclopedia
Bibliographic Database Standards and Procedures Manual
Bibliographic Database By Title
Anchor Modeling External links:
Tutorials – Anchor Modeling
An Introduction to Anchor Modeling – Teachable
Anchor Modeling (@anchormodeling) | Twitter
Halloween Problem External links:
The Halloween Problem | SQL Studies
SML Movie: Bowser Junior’s Halloween Problem! – YouTube
Bowser Junior’s Halloween Problem! | SuperMarioLogan …
Main memory External links:
Main memory | computer technology | Britannica.com
Main Memory – Central Connecticut State University
Chapter 8 Main Memory Flashcards | Quizlet
Computer data storage External links:
Computer Data Storage Jobs, Employment | Indeed.com
Computer Data Storage Options – Ferris State University
C. Wayne Ratliff External links:
C. Wayne Ratliff – Revolvy
https://broom02.revolvy.com/topic/C. Wayne Ratliff&item_type=topic
Knowledge management External links:
What Will Scare Knowledge Management in 2018 – APQC
KA Connect 2018 – A Knowledge Management Conference …
[PDF]Army Regulation 25-1, ‘Army Knowledge Management …
Database trigger External links:
What is a Database Trigger? – Essential SQL
Database trigger that communicates with an external program
Slowly changing dimension External links:
SSIS Slowly Changing Dimension Type 2 – Tutorial Gateway
Object-oriented programming External links:
What is object-oriented programming? – Quora
Apache Cassandra External links:
Getting Started With Apache Cassandra | Udemy
Materialized view External links:
How to refresh materialized view in oracle – Stack Overflow
Materialized View Concepts and Architecture
http://In computing, a materialized view is a database object that contains the results of a query. For example, it may be a local copy of data located remotely, or may be a subset of the rows and/or columns of a table or join result, or may be a summary using an aggregate function.
Database engine External links:
Using Database Engine Tuning Advisor – …
Lesson 1: Connecting to the Database Engine
Technical standard External links:
Technical standard legal definition of Technical standard
[PDF]NASA TECHNICAL STANDARD
[PDF]Technical Standard Order – faa.gov
Computer network External links:
Computer network | Britannica.com
Character encoding External links:
Choosing & applying a character encoding
ECG signal compression using ASCII character encoding …
Unicode – Character encoding – Android Apps on Google Play
Deductive database External links:
DES: A Deductive Database System – ScienceDirect
[PDF]An Introduction to Deductive Database Languages – VLDB
Deductive Database Exercise – part 2 of 3 – YouTube
Journal of Database Management External links:
Journal of Database Management (JDM): 1063-8016, 1533 …
Database refactoring External links:
liquibase.org – Liquibase | Database Refactoring | Liquibase
What is Database Refactoring | IGI Global
Liquibase | Database Refactoring | Databasechangelog
Network model External links:
Common Questions and Answers on the OSI Network Model
Extract, transform, load External links:
What is ETL (Extract, Transform, Load)? Webopedia Definition
ETL (Extract, transform, load) Salary | PayScale
http://www.payscale.com › United States › Skill/Specialty
Universal Product Code External links:
Comment Request – National Universal Product Code …
Universal Product Code (UPC) Barcodes – Infinity Graphics
UNIVERSAL PRODUCT CODE – AudioEnglish.org
Data dictionary External links:
What is a Data Dictionary? – Bridging the Gap
Codd’s 12 rules External links:
Codd’s 12 rules – A Gentle Introduction to SQL – Google Sites
Codd’s 12 Rules for Relational Database Management
Codd’s 12 Rules – RDBMS Basics – RDBMS for Begineers
Computer software External links:
See shopping results for computer software
Computer Software Programs | Quill.com
Computer Software | HSN
Fault tolerance External links:
Enabling vMotion and Fault tolerance logging (1036145)
Associative model of data External links:
Simon Guy Williams (Author of Associative Model Of Data, The)
The associative model of data | SpringerLink
The associative model of data (Book, 2000) [WorldCat.org]
Create, read, update and delete External links:
Column-oriented DBMS External links:
Paper Review: C-Store: A column-oriented DBMS
Column-oriented DBMS | Robert Goodman
Column-oriented DBMS |THWACK
Surrogate key External links:
Surrogate key – How is Surrogate key abbreviated?
Unknown Surrogate Key – Benny Austin
INSERT ALL INTO and Sequence.nextval for a Surrogate Key