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 191 essential critical questions to check off in that domain.

The following domains are covered:

Analytics and Decision Support, Social Loafing, Artificial intelligence, Medical diagnosis, Content discovery platform, Expert system, Surrogate key, Precision agriculture, Strategic planning software, Microsoft SharePoint Workspace, Netflix Prize, Collective intelligence, Early-arriving fact, Executive dashboard, Music Genome Project, Business intelligence, Intelligent agent, Operational data store, Henk G. Sol, Data mining, Data warehouse automation, Decision support system, Online analytical processing, Judge–advisor system, Executive information system, Extract, transform, load, User interface, XML for Analysis, Data mart, Collaborative search engine, Comparison of OLAP Servers, Decision theory, Fact table, Degenerate dimension, Data Mining Extensions, Cognitive assets, Knowledge base, Time series, Anchor Modeling, GroupLens Research, O’Hare International Airport, Data dictionary, Decision engineering, Data loading, Decision making process, Analytics and Decision Support, Open source, Preference elicitation, Slowly changing dimension, Data warehouse, Collaborative filtering, Enterprise decision management, Texas Instruments, Self service software, Systems architecture, Similarity search:

Analytics and Decision Support Critical Criteria:

Test Analytics and Decision Support risks and pay attention to the small things.

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

– How would one define Analytics and Decision Support leadership?

– What is our Analytics and Decision Support Strategy?

Social Loafing Critical Criteria:

Dissect Social Loafing projects and oversee Social Loafing management by competencies.

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

– Who will be responsible for deciding whether Analytics and Decision Support goes ahead or not after the initial investigations?

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

Artificial intelligence Critical Criteria:

Huddle over Artificial intelligence leadership and point out Artificial intelligence tensions in leadership.

– Are there any disadvantages to implementing Analytics and Decision Support? There might be some that are less obvious?

– How do we Identify specific Analytics and Decision Support investment and emerging trends?

Medical diagnosis Critical Criteria:

Participate in Medical diagnosis tactics and know what your objective is.

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

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

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

Content discovery platform Critical Criteria:

Apply Content discovery platform planning and overcome Content discovery platform skills and management ineffectiveness.

– 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?

– Who sets the Analytics and Decision Support standards?

Expert system Critical Criteria:

Categorize Expert system adoptions and gather Expert system models .

– What are your results for key measures or indicators of the accomplishment of your Analytics and Decision Support strategy and action plans, including building and strengthening core competencies?

– Which individuals, teams or departments will be involved in Analytics and Decision Support?

Surrogate key Critical Criteria:

Accelerate Surrogate key failures and drive action.

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

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

– What will drive Analytics and Decision Support change?

Precision agriculture Critical Criteria:

Closely inspect Precision agriculture strategies and spearhead techniques for implementing Precision agriculture.

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

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

Strategic planning software Critical Criteria:

Revitalize Strategic planning software quality and define what do we need to start doing with Strategic planning software.

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

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

– What about Analytics and Decision Support Analysis of results?

Microsoft SharePoint Workspace Critical Criteria:

Investigate Microsoft SharePoint Workspace management and develop and take control of the Microsoft SharePoint Workspace initiative.

– What new services of functionality will be implemented next with Analytics and Decision Support ?

– How will we insure seamless interoperability of Analytics and Decision Support moving forward?

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

Netflix Prize Critical Criteria:

Paraphrase Netflix Prize leadership and handle a jump-start course to Netflix Prize.

– How do your measurements capture actionable Analytics and Decision Support information for use in exceeding your customers expectations and securing your customers engagement?

– 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?

– Do those selected for the Analytics and Decision Support team have a good general understanding of what Analytics and Decision Support is all about?

Collective intelligence Critical Criteria:

Investigate Collective intelligence risks and grade techniques for implementing Collective intelligence controls.

– How will you know that the Analytics and Decision Support project has been successful?

– What are internal and external Analytics and Decision Support relations?

Early-arriving fact Critical Criteria:

Merge Early-arriving fact tactics and describe the risks of Early-arriving fact sustainability.

– How do mission and objectives affect the Analytics and Decision Support processes of our organization?

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

– Who will provide the final approval of Analytics and Decision Support deliverables?

Executive dashboard Critical Criteria:

Infer Executive dashboard visions and display thorough understanding of the Executive dashboard process.

– Where do ideas that reach policy makers and planners as proposals for Analytics and Decision Support strengthening and reform actually originate?

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

Music Genome Project Critical Criteria:

Merge Music Genome Project strategies and question.

– What is the total cost related to deploying Analytics and Decision Support, including any consulting or professional services?

Business intelligence Critical Criteria:

Give examples of Business intelligence failures and arbitrate Business intelligence techniques that enhance teamwork and productivity.

– Does your mobile solution allow you to interact with desktop-authored dashboards using touchscreen gestures like taps, flicks, and pinches?

– Does the software provide fast query performance, either via its own fast in-memory software or by directly connecting to fast data stores?

– What are the main differences between a business intelligence team compared to a team of data scientists?

– Does big data threaten the traditional data warehouse business intelligence model stack?

– Was your software written by your organization or acquired from a third party?

– Which other Oracle Business Intelligence products are used in your solution?

– Does your BI solution require weeks or months to deploy or change?

– What are some best practices for managing business intelligence?

– Number of data sources that can be simultaneously accessed?

– What is your anticipated learning curve for Report Users?

– How can data extraction from dashboards be automated?

– To create parallel systems or custom workflows?

– Will your product work from a mobile device?

– What level of training would you recommend?

– What are our tools for big data analytics?

– How is business intelligence disseminated?

– What are typical reporting applications?

– Do you offer formal user training?

– What is your annual maintenance?

Intelligent agent Critical Criteria:

Scan Intelligent agent strategies and drive action.

– 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?

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

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

Operational data store Critical Criteria:

Sort Operational data store decisions and oversee Operational data store management by competencies.

– 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?

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

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

Henk G. Sol Critical Criteria:

Analyze Henk G. Sol decisions and grade techniques for implementing Henk G. Sol controls.

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

– Do we have past Analytics and Decision Support Successes?

Data mining Critical Criteria:

Distinguish Data mining leadership and transcribe Data mining as tomorrows backbone for success.

– 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?

– Will new equipment/products be required to facilitate Analytics and Decision Support delivery for example is new software needed?

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

– 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 do we Lead with Analytics and Decision Support in Mind?

– What programs do we have to teach data mining?

Data warehouse automation Critical Criteria:

Huddle over Data warehouse automation results and pioneer acquisition of Data warehouse automation systems.

– How do we make it meaningful in connecting Analytics and Decision Support with what users do day-to-day?

– What are your most important goals for the strategic Analytics and Decision Support objectives?

Decision support system Critical Criteria:

Co-operate on Decision support system strategies and adjust implementation of Decision support system.

– A heuristic, a decision support system, or new practices to improve current project management?

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

– What are the business goals Analytics and Decision Support is aiming to achieve?

– Which Analytics and Decision Support goals are the most important?

Online analytical processing Critical Criteria:

Consolidate Online analytical processing tactics and describe which business rules are needed as Online analytical processing interface.

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

– Are we Assessing Analytics and Decision Support and Risk?

Judge–advisor system Critical Criteria:

Chat re Judge–advisor system results and document what potential Judge–advisor system megatrends could make our business model obsolete.

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

– What are the usability implications of Analytics and Decision Support actions?

– Is the scope of Analytics and Decision Support defined?

Executive information system Critical Criteria:

Check Executive information system governance and look at the big picture.

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

Extract, transform, load Critical Criteria:

Face Extract, transform, load issues and tour deciding if Extract, transform, load progress is made.

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

User interface Critical Criteria:

Chart User interface management and remodel and develop an effective User interface strategy.

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

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

XML for Analysis Critical Criteria:

Focus on XML for Analysis quality and look for lots of ideas.

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

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

Data mart Critical Criteria:

Air ideas re Data mart results and define Data mart competency-based leadership.

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

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

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

Collaborative search engine Critical Criteria:

Apply Collaborative search engine tasks and document what potential Collaborative search engine megatrends could make our business model obsolete.

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

– Why is Analytics and Decision Support important for you now?

Comparison of OLAP Servers Critical Criteria:

Refer to Comparison of OLAP Servers leadership and get out your magnifying glass.

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

Decision theory Critical Criteria:

Add value to Decision theory quality and look at it backwards.

– 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?

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

– How do senior leaders actions reflect a commitment to the organizations Analytics and Decision Support values?

Fact table Critical Criteria:

Participate in Fact table tactics and stake your claim.

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

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

Degenerate dimension Critical Criteria:

Transcribe Degenerate dimension planning and assess and formulate effective operational and Degenerate dimension strategies.

– 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?

– Are there recognized Analytics and Decision Support problems?

Data Mining Extensions Critical Criteria:

Map Data Mining Extensions issues and mentor Data Mining Extensions customer orientation.

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

– Do we all define Analytics and Decision Support in the same way?

– How do we go about Securing Analytics and Decision Support?

Cognitive assets Critical Criteria:

Confer re Cognitive assets projects and find out what it really means.

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

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

Knowledge base Critical Criteria:

Accumulate Knowledge base tactics and proactively manage Knowledge base risks.

– 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 Management personnel recognize the monetary benefit of Analytics and Decision Support?

– Can specialized social networks replace learning management systems?

Time series Critical Criteria:

Conceptualize Time series visions and oversee Time series requirements.

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

– How important is Analytics and Decision Support to the user organizations mission?

– Is Supporting Analytics and Decision Support documentation required?

Anchor Modeling Critical Criteria:

Group Anchor Modeling failures and shift your focus.

– For your Analytics and Decision Support project, identify and describe the business environment. is there more than one layer to the business environment?

– What is Effective Analytics and Decision Support?

GroupLens Research Critical Criteria:

Revitalize GroupLens Research management and balance specific methods for improving GroupLens Research results.

– Does Analytics and Decision Support include applications and information with regulatory compliance significance (or other contractual conditions that must be formally complied with) in a new or unique manner for which no approved security requirements, templates or design models exist?

O’Hare International Airport Critical Criteria:

Recall O’Hare International Airport management and forecast involvement of future O’Hare International Airport projects in development.

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

Data dictionary Critical Criteria:

Mix Data dictionary tasks and differentiate in coordinating Data dictionary.

– What types of information should be included in the data dictionary?

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

– Are there Analytics and Decision Support problems defined?

– Is there a data dictionary?

Decision engineering Critical Criteria:

Investigate Decision engineering tactics and handle a jump-start course to Decision engineering.

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

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

Data loading Critical Criteria:

Grade Data loading governance and oversee Data loading requirements.

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

Decision making process Critical Criteria:

Discourse Decision making process quality and suggest using storytelling to create more compelling Decision making process projects.

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

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

– What is our formula for success in Analytics and Decision Support ?

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

– Who will be involved in the decision making process?

Analytics and Decision Support Critical Criteria:

Pay attention to Analytics and Decision Support issues and slay a dragon.

– Consider your own Analytics and Decision Support project. what types of organizational problems do you think might be causing or affecting your problem, based on the work done so far?

– 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?

Open source Critical Criteria:

Substantiate Open source issues and give examples utilizing a core of simple Open source skills.

– 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?

– Is there an open source alternative to adobe captivate?

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

– What are the open source alternatives to Moodle?

Preference elicitation Critical Criteria:

Give examples of Preference elicitation outcomes and learn.

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

Slowly changing dimension Critical Criteria:

Powwow over Slowly changing dimension tactics and innovate what needs to be done with Slowly changing dimension.

– Does Analytics and Decision Support analysis isolate the fundamental causes of problems?

Data warehouse Critical Criteria:

Troubleshoot Data warehouse issues and test out new things.

– What tier data server has been identified for the storage of decision support data contained in a data warehouse?

– Do we need an enterprise data warehouse, a Data Lake, or both as part of our overall data architecture?

– What does a typical data warehouse and business intelligence organizational structure look like?

– Is Data Warehouseing necessary for a business intelligence service?

– What is the difference between a database and data warehouse?

– What are alternatives to building a data warehouse?

– Do we offer a good introduction to data warehouse?

– Data Warehouse versus Data Lake (Data Swamp)?

– Do you still need a data warehouse?

– Centralized data warehouse?

Collaborative filtering Critical Criteria:

Mix Collaborative filtering quality and develop and take control of the Collaborative filtering initiative.

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

– Who needs to know about Analytics and Decision Support ?

– How can we improve Analytics and Decision Support?

Enterprise decision management Critical Criteria:

Chart Enterprise decision management issues and diversify disclosure of information – dealing with confidential Enterprise decision management information.

Texas Instruments Critical Criteria:

Accommodate Texas Instruments planning and report on setting up Texas Instruments without losing ground.

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

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

Self service software Critical Criteria:

Deliberate Self service software management and summarize a clear Self service software focus.

Systems architecture Critical Criteria:

Debate over Systems architecture projects and define what our big hairy audacious Systems architecture goal is.

– 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?

Similarity search Critical Criteria:

Define Similarity search projects and explain and analyze the challenges of Similarity search.

– Why are Analytics and Decision Support skills important?


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

[email protected]


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:

Analytics and Decision Support External links:

Analytics and Decision Support – Banner Links

Social Loafing External links:

What Is Social Loafing in Psychology? – Verywell

Social Loafing Flashcards | Quizlet

social loafing – Progress Essays

Artificial intelligence External links:

RPA and Artificial Intelligence Summit 2017 – Official Site

Security analytics and artificial intelligence as a service

Artificial Intelligence for B2B Sales | Collective[i]

Medical diagnosis External links:

McKenzie Method of Medical Diagnosis & Treatment | Drayer

How to Write a Medical Diagnosis: 8 Steps (with Pictures)

Online Medical Diagnosis & Advice | UPMC AnywhereCare

Content discovery platform External links:

A content discovery platform is an implemented software recommendation platform which uses recommender system tools. It utilizes user metadata in order to discover and recommend appropriate content, whilst reducing ongoing maintenance and development costs.
Reference: en.wikipedia.org/wiki/Content_Discovery_Platform

Personalized Content Discovery Platform | TiVo


Expert system External links:

Home – IDEA System Expert System for Internal Dosimetry

Accu-Chek Aviva Expert System | Accu-Chek

CE Expert System – pdotdev2.state.pa.us

Surrogate key External links:

Surrogate key in SCD – Informatica Network

Database Design 25 – Surrogate Key and Natural Key – YouTube

INSERT ALL INTO and Sequence.nextval for a Surrogate Key

Precision agriculture External links:

Precision Agriculture » Raven Slingshot®

Zoner – Precision agriculture software

Precision Agriculture, Farming and Agricultural Technology

Strategic planning software External links:

Strategic Planning Software Pricing | OnStrategy

Strategic Planning Software: What To Demand & What To …

Strategic Planning Software and Tools – Planview

Netflix Prize External links:

How the Netflix Prize Was Won | WIRED

Netflix Prize: Home

Collective intelligence External links:

Collective Intelligence – AbeBooks

Who We Are | Collective Intelligence, Inc.


Early-arriving fact External links:

Early-arriving fact – Revolvy
broom02.revolvy.com/topic/Early-arriving fact

Executive dashboard External links:

Executive Dashboard:Login Page

Executive Dashboard : Driving Organizations to Excellence

Executive dashboard for Agile projects | Dash of Agile

Music Genome Project External links:

Music Genome Project
The Music Genome Project was first conceived by Will Glaser and Tim Westergren in late 1999. In January 2000, they joined forces with Jon Kraft to found Savage Beast Technologies to bring their idea to market. The Music Genome Project is an effort to “capture the essence of music at the most fundamental level” using over 450 attributes to describe songs and a complex mathematical algorithm to organize them. The Music Genome Project is currently made up of 5 sub-genomes: Pop/Rock, Hip-Hop/Electronica, Jazz, World Music, and Classical. Under the direction of Nolan Gasser and a team of musicological experts, the initial attributes were later refined and extended.

Pandora – Music Genome Project

Evolution of radio and Music Genome Project – YouTube

Business intelligence External links:

[PDF]Position Title: Business Intelligence Analyst – ttra

List of Business Intelligence Skills – The Balance

Operational data store External links:

Operational Data Store – ODS – Gartner Tech Definitions

ECATS OPERATIONAL DATA STORE – ncpublicschools.org

Operational Data Store – YouTube

Henk G. Sol External links:

Henk G. Sol | Publications

Data mining External links:

data aggregation in data mining ppt

[PDF]Data Mining Report – fas.org

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

Data warehouse automation External links:

biGENiUS – Data Warehouse Automation

Decision support system External links:

decision support system | Fort Collins Science Center

What is Decision Support System | InTechOpen

Decision Support System for Air Operating Permits – …

Online analytical processing External links:

SAS Online Analytical Processing Server

Working with Online Analytical Processing (OLAP)

Oracle Online Analytical Processing (OLAP)

Executive information system External links:

[PDF]Transportation Executive Information System …

Best Executive Information System Software – G2 Crowd


Extract, transform, load External links:

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

User interface External links:

Login – Terminal Customer User Interface – Colonial Pipeline

Datatel User Interface 5.3

PKG User Interface Solutions

XML for Analysis External links:

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

[PDF]XML for Analysis Specification

Data mart External links:

[PDF]A Basic Primer on Data Marts – webgrok.com

MPR Data Mart

Comparison of OLAP Servers External links:

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

Comparison of OLAP Servers: Latest News & Videos, …

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

Decision theory External links:

Title: Toward Idealized Decision Theory – arxiv.org

Decision theory (Book, 2006) [WorldCat.org]

Fact table External links:

Fact table – Oracle FAQ

what is dimension table and what is fact table. – Informatica

Factless Fact Table – Wisdomschema

Degenerate dimension External links:

Data Warehousing: What is degenerate dimension? – …

Degenerate Dimension – YouTube

Data Mining Extensions External links:

Data Mining Extensions (DMX) Operator Reference

Data Mining Extensions (DMX) Reference | Microsoft Docs

Data Mining Extensions (DMX) Reference

Knowledge base External links:

Indiana University – IU Knowledge Base

Star2Star Communications Knowledge Base

Welcome to the BroadCloud Knowledge Base

Time series External links:

Azure Time Series Insights API | Microsoft Docs

Time Series Insights | Microsoft Azure

Initial State – Analytics for Time Series Data

Anchor Modeling External links:

Anchor Modeling (@anchormodeling) | Twitter

Publications – Anchor Modeling

Anchor Modeling – Home | Facebook

O’Hare International Airport External links:

Getting To and From O’Hare International Airport

Request Uber at Chicago O’Hare International Airport …

Data dictionary External links:

What is a Data Dictionary? – Bridging the Gap

OpenAir Data Dictionary

What is a Data Dictionary? – Definition from Techopedia

Decision engineering External links:

Decision engineering – encyclopedia article – Citizendium

Data loading External links:

The Data Loading Performance Guide – technet.microsoft.com

Decision making process External links:

Decision Making Process – SlideShare


Decision Making Process Paper – 820 Words – StudyMode

Analytics and Decision Support External links:

Analytics and Decision Support – Banner Links

Open source External links:

Open Source Center – Official Site

Open Source Search & Analytics · Elasticsearch | Elastic

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.

Preference elicitation External links:

Preference Elicitation Tool for Abnormal Uterine …

Preference Elicitation in Proxied Multiattribute Auctions

Preference elicitation in combinatorial auctions

Slowly changing dimension External links:

SSIS Slowly Changing Dimension Type 2 – Tutorial Gateway

SSIS- Slowly Changing Dimension (SCD) Tutorial

Data warehouse External links:

Title 2 Data Warehouse – Data.gov

Cloud Data Warehouse | Snowflake

HRSA Data Warehouse Home Page

Collaborative filtering External links:

[PDF]Collaborative Filtering for Netflix – Courses

Title: Collaborative Filtering Bandits – arXiv

Enterprise decision management External links:

enterprise decision management Archives – Insights

Enterprise Decision Management (EDM) – Techopedia.com

Texas Instruments External links:

Texas Instruments – Home | Facebook

Texas Instruments Perks at Work

TI Analog, DSP and Semiconductor Products – Texas Instruments

Systems architecture External links:

Software Systems Architecture

[PDF]A framework for information systems architecture

Similarity search External links:

FALCONN: Similarity Search Over High-Dimensional Data

Sequence Similarity Search | Planarian Education Resource