186 In-Depth Analytics and Decision Support Questions for Professionals

What is involved in Analytics and Decision Support

Find out what the related areas are that Analytics and Decision Support 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 Analytics and Decision Support thinking-frame.

How far is your company on its Analytics and Decision Support journey?

Take this short survey to gauge your organization’s progress toward Analytics and Decision Support 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 Analytics and Decision Support related domains to cover and 186 essential critical questions to check off in that domain.

The following domains are covered:

Analytics and Decision Support, Predictive analytics, Dimensionality reduction, Self service software, Decision theory, MultiDimensional eXpressions, Quality assurance, Data mart, Surrogate key, Project management software, Netflix Prize, Artificial intelligence, Knowledge-based systems, Sixth normal form, Similarity search, Fact table, Decision-making software, Integrated Authority File, Data access, Enterprise decision management, Judge–advisor system, Preference elicitation, Anchor Modeling, Knowledge environment, Column-oriented DBMS, Decision engineering, Cold start, Data loading, Content discovery platform, Data warehouse automation, Knowledge base, Land allocation decision support system, Online analytical processing, XML for Analysis, Systems architecture, Microsoft SharePoint Workspace, Operational data store, Collaborative filtering, Analytics and Decision Support, Expert system, OLAP cube, Social Loafing, Henk G. Sol, Decision making, Extract, transform, load, Executive dashboard, Problem-Oriented Medical Information System, Intelligent decision support system, Data mining, Data transformation, Comparison of OLAP Servers, Dimension table, Medical diagnosis, United Airlines, User interface, Sustainable development, Open source:

Analytics and Decision Support Critical Criteria:

Ventilate your thoughts about Analytics and Decision Support engagements and describe the risks of Analytics and Decision Support sustainability.

– What are your key performance measures or indicators and in-process measures for the control and improvement of your Analytics and Decision Support processes?

– Does Analytics and Decision Support systematically track and analyze outcomes for accountability and quality improvement?

– What threat is Analytics and Decision Support addressing?

Predictive analytics Critical Criteria:

Model after Predictive analytics management and probe Predictive analytics strategic alliances.

– Think about the kind of project structure that would be appropriate for your Analytics and Decision Support project. should it be formal and complex, or can it be less formal and relatively simple?

– How does the organization define, manage, and improve its Analytics and Decision Support processes?

– What are direct examples that show predictive analytics to be highly reliable?

– What is Effective Analytics and Decision Support?

Dimensionality reduction Critical Criteria:

Systematize Dimensionality reduction tasks and report on the economics of relationships managing Dimensionality reduction and constraints.

– Think about the people you identified for your Analytics and Decision Support 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?

– What are our best practices for minimizing Analytics and Decision Support project risk, while demonstrating incremental value and quick wins throughout the Analytics and Decision Support project lifecycle?

– Are assumptions made in Analytics and Decision Support stated explicitly?

Self service software Critical Criteria:

Incorporate Self service software decisions and pioneer acquisition of Self service software systems.

– What are the success criteria that will indicate that Analytics and Decision Support objectives have been met and the benefits delivered?

– Who will be responsible for documenting the Analytics and Decision Support requirements in detail?

– How will you measure your Analytics and Decision Support effectiveness?

Decision theory Critical Criteria:

Tête-à-tête about Decision theory decisions and slay a dragon.

– What is the purpose of Analytics and Decision Support in relation to the mission?

– How do we manage Analytics and Decision Support Knowledge Management (KM)?

MultiDimensional eXpressions Critical Criteria:

Apply MultiDimensional eXpressions goals and plan concise MultiDimensional eXpressions education.

– To what extent does management recognize Analytics and Decision Support as a tool to increase the results?

– What tools and technologies are needed for a custom Analytics and Decision Support project?

– Is there any existing Analytics and Decision Support governance structure?

Quality assurance Critical Criteria:

Brainstorm over Quality assurance quality and pay attention to the small things.

– Does a quality plan exist for significant it functions (e.g., system development and deployment) and does it provide a consistent approach to address both general and project-specific Quality Assurance activities?

– What is your Quality Assurance process to ensure that the large volumes of data gathered in the monitoring process are handled efficiently?

– Is the records center well-maintained, orderly, and free of clutter that could lead to misplaced or lost records?

– Has the board demonstrated a willingness to provide appropriate resources to Quality Assurance programs?

– What are the best practices for software quality assurance when using agile development methodologies?

– How does the company create high performance relationships with its independent trade partners?

– Are Quality Assurance records stored in folders, binders, or other suitable protection?

– Does the Quality Assurance record center contain the selected documents?

– Were adequate human factors considered in the design of the equipment?

– What are your key indicators that you will measure, analyze and track?

– Is the performance measure improving, degrading, or remaining stable?

– Who closes the loop with the person that submitted a complaint?

– How to balance level of oversight with level of risk ?

– Do you keep track of unsuccessfully performed skills?

– How do you investigate complaints from the public?

– Can the test data be processed in a timely manner?

– How will you measure your qa plan effectiveness?

– How often are your current policies evaluated?

– Who provides training for any new protocol?

– Is specialized equipment necessary?

Data mart Critical Criteria:

Think about Data mart visions and create Data mart explanations for all managers.

– Is maximizing Analytics and Decision Support protection the same as minimizing Analytics and Decision Support loss?

– What other jobs or tasks affect the performance of the steps in the Analytics and Decision Support process?

– What are the Essentials of Internal Analytics and Decision Support Management?

– What is the purpose of data warehouses and data marts?

Surrogate key Critical Criteria:

Grasp Surrogate key quality and get the big picture.

– Do several people in different organizational units assist with the Analytics and Decision Support process?

Project management software Critical Criteria:

Consider Project management software planning and reduce Project management software costs.

– Can we add value to the current Analytics and Decision Support decision-making process (largely qualitative) by incorporating uncertainty modeling (more quantitative)?

– What knowledge, skills and characteristics mark a good Analytics and Decision Support project manager?

– How can you measure Analytics and Decision Support in a systematic way?

Netflix Prize Critical Criteria:

Value Netflix Prize projects and budget for Netflix Prize challenges.

– How can you negotiate Analytics and Decision Support successfully with a stubborn boss, an irate client, or a deceitful coworker?

– When a Analytics and Decision Support manager recognizes a problem, what options are available?

– What vendors make products that address the Analytics and Decision Support needs?

Artificial intelligence Critical Criteria:

Accelerate Artificial intelligence management and correct Artificial intelligence management by competencies.

– Are there any easy-to-implement alternatives to Analytics and Decision Support? Sometimes other solutions are available that do not require the cost implications of a full-blown project?

– How to deal with Analytics and Decision Support Changes?

Knowledge-based systems Critical Criteria:

Illustrate Knowledge-based systems failures and reinforce and communicate particularly sensitive Knowledge-based systems decisions.

– What may be the consequences for the performance of an organization if all stakeholders are not consulted regarding Analytics and Decision Support?

– Are there Analytics and Decision Support problems defined?

– What is our Analytics and Decision Support Strategy?

Sixth normal form Critical Criteria:

Explore Sixth normal form projects and don’t overlook the obvious.

– What management system can we use to leverage the Analytics and Decision Support experience, ideas, and concerns of the people closest to the work to be done?

– Is a Analytics and Decision Support Team Work effort in place?

Similarity search Critical Criteria:

Probe Similarity search goals and diversify by understanding risks and leveraging Similarity search.

– Record-keeping requirements flow from the records needed as inputs, outputs, controls and for transformation of a Analytics and Decision Support process. ask yourself: are the records needed as inputs to the Analytics and Decision Support process available?

– Meeting the challenge: are missed Analytics and Decision Support opportunities costing us money?

– Do Analytics and Decision Support rules make a reasonable demand on a users capabilities?

Fact table Critical Criteria:

Distinguish Fact table failures and report on setting up Fact table without losing ground.

– Why is it important to have senior management support for a Analytics and Decision Support project?

– Have you identified your Analytics and Decision Support key performance indicators?

– How is the value delivered by Analytics and Decision Support being measured?

Decision-making software Critical Criteria:

Experiment with Decision-making software strategies and ask what if.

– Why should we adopt a Analytics and Decision Support framework?

– How much does Analytics and Decision Support help?

Integrated Authority File Critical Criteria:

Familiarize yourself with Integrated Authority File issues and clarify ways to gain access to competitive Integrated Authority File services.

– Among the Analytics and Decision Support product and service cost to be estimated, which is considered hardest to estimate?

– What role does communication play in the success or failure of a Analytics and Decision Support project?

– Does our organization need more Analytics and Decision Support education?

Data access Critical Criteria:

Accelerate Data access leadership and diversify disclosure of information – dealing with confidential Data access information.

– Have internal procedural controls been established to manage user data access, including security screenings, training, and confidentiality agreements required for staff with pii access privileges?

– Who will be responsible for making the decisions to include or exclude requested changes once Analytics and Decision Support is underway?

– What impact would the naming conventions and the use of homegrown software have on later data access?

– What are the data access requirements for standard file, message, and data management?

– What should be our public authorities policy with regards to data access?

– What impact would the naming conventions have on later data access?

– What are the effects software updates have on later data access?

– What are the implications of tracking/monitoring data access?

– What are the long-term Analytics and Decision Support goals?

– How would one define Analytics and Decision Support leadership?

– How are data accessed?

Enterprise decision management Critical Criteria:

Define Enterprise decision management failures and create a map for yourself.

– Is there a Analytics and Decision Support Communication plan covering who needs to get what information when?

– What are the Key enablers to make this Analytics and Decision Support move?

Judge–advisor system Critical Criteria:

Air ideas re Judge–advisor system issues and do something to it.

– Risk factors: what are the characteristics of Analytics and Decision Support that make it risky?

Preference elicitation Critical Criteria:

Align Preference elicitation projects and do something to it.

– How do you determine the key elements that affect Analytics and Decision Support workforce satisfaction? how are these elements determined for different workforce groups and segments?

– What are the barriers to increased Analytics and Decision Support production?

Anchor Modeling Critical Criteria:

Revitalize Anchor Modeling goals and forecast involvement of future Anchor Modeling projects in development.

– Marketing budgets are tighter, consumers are more skeptical, and social media has changed forever the way we talk about Analytics and Decision Support. How do we gain traction?

Knowledge environment Critical Criteria:

Substantiate Knowledge environment strategies and balance specific methods for improving Knowledge environment results.

– Who needs to know about Analytics and Decision Support ?

Column-oriented DBMS Critical Criteria:

Grasp Column-oriented DBMS failures and look at the big picture.

– Do we monitor the Analytics and Decision Support decisions made and fine tune them as they evolve?

– How do we measure improved Analytics and Decision Support service perception, and satisfaction?

Decision engineering Critical Criteria:

Group Decision engineering strategies and devote time assessing Decision engineering and its risk.

Cold start Critical Criteria:

Depict Cold start failures and innovate what needs to be done with Cold start.

– Which customers cant participate in our Analytics and Decision Support domain because they lack skills, wealth, or convenient access to existing solutions?

Data loading Critical Criteria:

Familiarize yourself with Data loading decisions and pay attention to the small things.

– Can we do Analytics and Decision Support without complex (expensive) analysis?

Content discovery platform Critical Criteria:

Judge Content discovery platform goals and gather practices for scaling Content discovery platform.

– Think about the functions involved in your Analytics and Decision Support project. what processes flow from these functions?

– Is Analytics and Decision Support Required?

Data warehouse automation Critical Criteria:

Steer Data warehouse automation leadership and budget the knowledge transfer for any interested in Data warehouse automation.

– What are the record-keeping requirements of Analytics and Decision Support activities?

– What are specific Analytics and Decision Support Rules to follow?

Knowledge base Critical Criteria:

Co-operate on Knowledge base results and track iterative Knowledge base results.

– Do we support the certified Cybersecurity professional and cyber-informed operations and engineering professionals with advanced problem-solving tools, communities of practice, canonical knowledge bases, and other performance support tools?

– Can specialized social networks replace learning management systems?

Land allocation decision support system Critical Criteria:

Mix Land allocation decision support system failures and look in other fields.

– Does Analytics and Decision Support appropriately measure and monitor risk?

Online analytical processing Critical Criteria:

Reorganize Online analytical processing risks and figure out ways to motivate other Online analytical processing users.

– Is Analytics and Decision Support Realistic, or are you setting yourself up for failure?

XML for Analysis Critical Criteria:

Audit XML for Analysis failures and report on setting up XML for Analysis without losing ground.

– Are there recognized Analytics and Decision Support problems?

Systems architecture Critical Criteria:

Facilitate Systems architecture governance and document what potential Systems architecture megatrends could make our business model obsolete.

– Who is responsible for ensuring appropriate resources (time, people and money) are allocated to Analytics and Decision Support?

– Have the types of risks that may impact Analytics and Decision Support been identified and analyzed?

Microsoft SharePoint Workspace Critical Criteria:

Consider Microsoft SharePoint Workspace visions and gather Microsoft SharePoint Workspace models .

– A compounding model resolution with available relevant data can often provide insight towards a solution methodology; which Analytics and Decision Support models, tools and techniques are necessary?

– How do we keep improving Analytics and Decision Support?

Operational data store Critical Criteria:

Think carefully about Operational data store governance and correct better engagement with Operational data store results.

– What will be the consequences to the business (financial, reputation etc) if Analytics and Decision Support does not go ahead or fails to deliver the objectives?

Collaborative filtering Critical Criteria:

Examine Collaborative filtering failures and find the essential reading for Collaborative filtering researchers.

Analytics and Decision Support Critical Criteria:

Distinguish Analytics and Decision Support adoptions and correct better engagement with Analytics and Decision Support results.

– At what point will vulnerability assessments be performed once Analytics and Decision Support is put into production (e.g., ongoing Risk Management after implementation)?

– Do we aggressively reward and promote the people who have the biggest impact on creating excellent Analytics and Decision Support services/products?

– Does Analytics and Decision Support analysis show the relationships among important Analytics and Decision Support factors?

Expert system Critical Criteria:

Align Expert system outcomes and separate what are the business goals Expert system is aiming to achieve.

OLAP cube Critical Criteria:

Collaborate on OLAP cube tasks and define OLAP cube competency-based leadership.

– Who is the main stakeholder, with ultimate responsibility for driving Analytics and Decision Support forward?

Social Loafing Critical Criteria:

Have a meeting on Social Loafing failures and assess what counts with Social Loafing that we are not counting.

– Is the Analytics and Decision Support organization completing tasks effectively and efficiently?

Henk G. Sol Critical Criteria:

Sort Henk G. Sol governance and plan concise Henk G. Sol education.

– What are our needs in relation to Analytics and Decision Support skills, labor, equipment, and markets?

Decision making Critical Criteria:

Jump start Decision making projects and attract Decision making skills.

– Is there a timely attempt to prepare people for technological and organizational changes, e.g., through personnel management, training, or participatory decision making?

– Do the Analytics and Decision Support decisions we make today help people and the planet tomorrow?

– What kind of processes and tools could serve both the vertical and horizontal analysis and decision making?

– What s the protocol for interaction, decision making, project management?

– What role do analysts play in the decision making process?

– Who will be involved in the decision making process?

– What about Analytics and Decision Support Analysis of results?

– Are the data needed for corporate decision making?

Extract, transform, load Critical Criteria:

Contribute to Extract, transform, load engagements and oversee Extract, transform, load management by competencies.

– How can skill-level changes improve Analytics and Decision Support?

Executive dashboard Critical Criteria:

Think about Executive dashboard adoptions and figure out ways to motivate other Executive dashboard users.

– How do you incorporate cycle time, productivity, cost control, and other efficiency and effectiveness factors into these Analytics and Decision Support processes?

– In what ways are Analytics and Decision Support vendors and us interacting to ensure safe and effective use?

– What potential environmental factors impact the Analytics and Decision Support effort?

Problem-Oriented Medical Information System Critical Criteria:

Concentrate on Problem-Oriented Medical Information System governance and slay a dragon.

– Have all basic functions of Analytics and Decision Support been defined?

– What will drive Analytics and Decision Support change?

Intelligent decision support system Critical Criteria:

Chat re Intelligent decision support system decisions and balance specific methods for improving Intelligent decision support system results.

– How do we ensure that implementations of Analytics and Decision Support products are done in a way that ensures safety?

– What are the top 3 things at the forefront of our Analytics and Decision Support agendas for the next 3 years?

Data mining Critical Criteria:

Categorize Data mining tasks and remodel and develop an effective Data mining strategy.

– what is the best design framework for Analytics and Decision Support organization now that, in a post industrial-age if the top-down, command and control model is no longer relevant?

– Do you see the need to clarify copyright aspects of the data-driven innovation (e.g. with respect to technologies such as text and data mining)?

– What types of transactional activities and data mining are being used and where do we see the greatest potential benefits?

– What is the difference between Data Analytics Data Analysis Data Mining and Data Science?

– What is the difference between business intelligence business analytics and data mining?

– Is business intelligence set to play a key role in the future of Human Resources?

– How can the value of Analytics and Decision Support be defined?

– What programs do we have to teach data mining?

Data transformation Critical Criteria:

Deliberate over Data transformation tactics and devise Data transformation key steps.

– Is Analytics and Decision Support dependent on the successful delivery of a current project?

– Describe the process of data transformation required by your system?

– What is the process of data transformation required by your system?

Comparison of OLAP Servers Critical Criteria:

Co-operate on Comparison of OLAP Servers projects and look in other fields.

Dimension table Critical Criteria:

Explore Dimension table adoptions and figure out ways to motivate other Dimension table users.

– In the case of a Analytics and Decision Support project, the criteria for the audit derive from implementation objectives. an audit of a Analytics and Decision Support project involves assessing whether the recommendations outlined for implementation have been met. in other words, can we track that any Analytics and Decision Support project is implemented as planned, and is it working?

– What are all of our Analytics and Decision Support domains and what do they do?

Medical diagnosis Critical Criteria:

Troubleshoot Medical diagnosis tactics and correct better engagement with Medical diagnosis results.

United Airlines Critical Criteria:

Check United Airlines strategies and budget for United Airlines challenges.

– How likely is the current Analytics and Decision Support plan to come in on schedule or on budget?

– What are current Analytics and Decision Support Paradigms?

User interface Critical Criteria:

Examine User interface outcomes and learn.

– Think of your Analytics and Decision Support project. what are the main functions?

– What if we substitute prototyping for user interface screens on paper?

– Does a User interface survey show which search ui is better ?

Sustainable development Critical Criteria:

Discourse Sustainable development tactics and probe the present value of growth of Sustainable development.

– Are we making progress? and are we making progress as Analytics and Decision Support leaders?

– How do we Improve Analytics and Decision Support service perception, and satisfaction?

– How do we go about Comparing Analytics and Decision Support approaches/solutions?

Open source Critical Criteria:

Debate over Open source issues and describe the risks of Open source sustainability.

– Is there any open source personal cloud software which provides privacy and ease of use 1 click app installs cross platform html5?

– How much do political issues impact on the decision in open source projects and how does this ultimately impact on innovation?

– What are the different RDBMS (commercial and open source) options available in the cloud today?

– Is open source software development faster, better, and cheaper than software engineering?

– Vetter, Infectious Open Source Software: Spreading Incentives or Promoting Resistance?

– What are some good open source projects for the internet of things?

– What are the best open source solutions for data loss prevention?

– Is open source software development essentially an agile method?

– What can a cms do for an open source project?

– Is there an open source alternative to adobe captivate?

– What are the open source alternatives to Moodle?


This quick readiness checklist is a selected resource to help you move forward. Learn more about how to achieve comprehensive insights with the Analytics and Decision Support Self Assessment:


Author: Gerard Blokdijk

CEO at The Art of Service | 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.

External links:

To address the criteria in this checklist, these selected resources are provided for sources of further research and information:

Predictive analytics External links:

Predictive Analytics Software, Social Listening | NewBrand

Inventory Optimization for Retail | Predictive Analytics

Predictive Analytics – “Prepare Your Org
Ad · www.sas.com/predictive-analytics

Dimensionality reduction External links:

Dimensionality Reduction Algorithms: Strengths and Weaknesses

[PDF]Lecture 6: Dimensionality reduction (LDA)

Dimensionality Reduction: Principal Components …

Decision theory External links:

Decision theory as philosophy (Book, 1996) [WorldCat.org]

Decision Theory Flashcards | Quizlet

Decision theory | statistics | Britannica.com

Quality assurance External links:

CCQAS – Centralized Credentials Quality Assurance System

Think of quality assurance as before the goods or services have been produced and quality control is during the production of the goods or services. The former ensures that there will be quality and the latter controls the execution to ensure that there was quality.
Reference: asq.org/learn-about-quality/quality-assurance-quality-control/o…

Nursing Care Quality Assurance Commission :: …

Data mart External links:

UNC Data Mart – University of North Carolina

[PDF]Institutional Research Data Mart: Instructor Guide …

MPR Data Mart

Surrogate key External links:

What is a Surrogate Key? – Definition from Techopedia

Difference between a primary key and a surrogate key

INSERT ALL INTO and Sequence.nextval for a Surrogate Key

Project management software External links:

Synchro – Construction project management software …

Project management software, online collaboration: Basecamp

Netflix Prize External links:

Netflix Prize: FAQ

How the Netflix Prize Was Won | WIRED

[PDF]Use of KNN for the Netflix Prize – Machine learning

Artificial intelligence External links:

Logojoy | Artificial Intelligence Logo Design

Robotics & Artificial Intelligence ETF

Knowledge-based systems External links:

Knowledge-Based Systems – ScienceDirect.com

Sixth normal form External links:

Sixth normal form – Google Groups

sql – design – sixth normal form – Stack Overflow

6NF abbreviation stands for Sixth normal form – All Acronyms

Similarity search External links:

FALCONN: Similarity Search Over High-Dimensional Data

eTBLAST and Déjà vu: a Text Similarity Search Engine and …

Multiscale Quantization for Fast Similarity Search

Fact table External links:

Factless Fact Table | Learn about Factless Fact Table

Fact table – Oracle FAQ

Factless Fact Table – Wisdomschema

Decision-making software External links:

Paramount Decisions | Lean Decision-making Software …

Integrated Authority File External links:

MEDLARS indexing: integrated authority file

Integrated Authority File (GND) – Deutsche Nationalbibliothek

Integrated Authority File – iSnare Free Encyclopedia

Data access External links:

BuildFax Data Access Portal: BDAP

NOAA: Data Access Viewer

Colorado State Courts – Data Access – Home

Enterprise decision management External links:

Come to the Enterprise Decision Management Summit in …

Enterprise Decision Management | Sapiens DECISION

enterprise decision management Archives – Insights

Preference elicitation External links:

[PDF]Preference elicitation and learning – Springer

CiteSeerX — Preference Elicitation under Oath1

Preference Elicitation in Proxied Multiattribute Auctions

Anchor Modeling External links:

An Introduction to Anchor Modeling – Teachable

Anchor Modeling – Home | Facebook

Great Minds Think Alike – Anchor Modeling

Knowledge environment External links:

Dynamic Knowledge Environment (DKE) – Doug …

Sophic Cancer Biomarker Knowledge Environment

Studio E&P Knowledge Environment – Schlumberger …

Column-oriented DBMS External links:

ClickHouse — open source distributed column-oriented DBMS

[PDF]C-Store: A Column-oriented DBMS – MIT Database …

C-Store: A Column-oriented DBMS – citeseerx.ist.psu.edu

Decision engineering External links:

Integrated Decision Engineering Analysis, Inc.

Decision engineering – encyclopedia article – Citizendium

decisionz.com – Decision Engineering (NZ) Ltd, Rated …

Cold start External links:

Cold Start Switch | eBay

Instant Pot No Boil Yogurt {Cold Start Method} | This Old Gal

Cold Start, Weekend Warm Up – WHDH

Data loading External links:

The Data Loading Performance Guide – technet.microsoft.com

Content discovery platform External links:

Personalized Content Discovery Platform | TiVo

What is Outbrain? Content Discovery Platform | Outbrain…

Dable – No. 1 Content Discovery Platform

Data warehouse automation External links:

dwh42.de – Data Warehouse Automation – zonwhois.com

Data Warehouse Automation | Attunity

Knowledge base External links:

Knowledge Base – McAfee

Carbonite Support Knowledge Base

Social Research Methods – Knowledge Base – Internal Validity

Land allocation decision support system External links:

Land Allocation Decision Support System – Macaulay …

XML for Analysis External links:

Cover Pages: XML for Analysis

XML for Analysis (XMLA) – technet.microsoft.com

XML for Analysis Specification – msdn.microsoft.com

Systems architecture External links:

The US Navy — Fact File: Open Systems Architecture (OSA)

Software Systems Architecture

Systems Architecture Ch 11/13 Flashcards | Quizlet

Microsoft SharePoint Workspace External links:

Microsoft SharePoint Workspace – Download

Microsoft SharePoint Workspace 2010 – …

Operational data store External links:

Operational Data Store (ODS) Defined | James Serra’s Blog

Operational Data Store – ODS – Gartner Tech Definitions

Collaborative filtering External links:

[PDF]Collaborative Filtering for Netflix

Title: Collaborative Filtering Bandits – arXiv

Expert system External links:

CE Expert System – pdotdev2.state.pa.us

TRACES – Trade Control and Expert System

Expert System | Definition of Expert System by Merriam-Webster
www.merriam-webster.com/dictionary/expert system

OLAP cube External links:

sql – OLAP Cube deployment issues – Stack Overflow

OLAP cube / Analysis Services = error on transport layer

SSAS OLAP cube Dates as measures display |Tableau …

Social Loafing External links:

What Is Social Loafing in Psychology? – Verywell

[PDF]Social Loafing: A Review of the Literature

Social Loafing Flashcards | Quizlet

Henk G. Sol External links:

Henk G. Sol | University of Groningen (RUG) | ResearchGate

Decision making External links:

Mayo Clinic Shared Decision Making National Resource Center

Effective Decision Making | SkillsYouNeed

Extract, transform, load External links:

What is ETL (Extract, Transform, Load)? Webopedia …

Executive dashboard External links:

The Executive Dashboard | PMI Washington DC

What is executive dashboard? – Definition from WhatIs.com

What is executive dashboard? – Definition from …

Problem-Oriented Medical Information System External links:

Problem-Oriented medical information system (PROMIS…

Problem-Oriented Medical Information System | Free …

Problem-Oriented Medical Information System – WOW…

Intelligent decision support system External links:


Data mining External links:

[PDF]Data Mining Mining Text Data – tutorialspoint.com

[PDF]Data Mining Report – Federation of American Scientists

UT Data Mining

Data transformation External links:

Data transformation (Computer file, 1987) [WorldCat.org]

Data transformation | FileMaker Community

[PDF]Data transformation and normality – Evaluation

Comparison of OLAP Servers External links:

Comparison of OLAP Servers – topics.revolvy.com
topics.revolvy.com/topic/Comparison of OLAP Servers


Comparison Of OLAP Servers – theinfolist.com

Dimension table External links:

Dimension Table – msdn.microsoft.com

Pipe Dimension Table – Grating

Tube Dimension Table – McNichols Company – Grating

Medical diagnosis External links:

Online Medical Diagnosis & Advice | UPMC AnywhereCare

United Airlines External links:

United Airlines

$10 off United Airlines Coupons & Codes – January 2018

United Airlines – Rewards for Businesses

User interface External links:

Datatel User Interface 5.3

JSI Multiline User Interface – Optimum

EWS User Interface

Sustainable development External links:

Home .:. Sustainable Development Knowledge Platform

U.S. Indicators For The Sustainable Development Goals

Sustainable development goals – United Nations – un.org

Open source External links:

Linux.com | News for the open source professional

Open source
In production and development, open source as a development model promotes a universal access via a free license to a product’s design or blueprint, and universal redistribution of that design or blueprint, including subsequent improvements to it by anyone. Before the phrase open source became widely adopted, developers and producers used a variety of other terms. Open source gained hold with the rise of the Internet, and the attendant need for massive retooling of the computing source code. Opening the source code enabled a self-enhancing diversity of production models, communication paths, and interactive communities. The open-source software movement arose to clarify the environment that the new copyright, licensing, domain, and consumer issues created. Generally, open source refers to a computer program in which the source code is available to the general public for use and/or modification from its original design. Open-source code is typically a collaborative effort where programmers improve upon the source code and share the changes within the community so that other members can help improve it further.

OpenVPN – Open Source VPN