What is involved in Risk Analytics
Find out what the related areas are that Risk Analytics 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 Risk Analytics thinking-frame.
How far is your company on its Risk Analytics journey?
Take this short survey to gauge your organization’s progress toward Risk Analytics 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 Risk Analytics related domains to cover and 204 essential critical questions to check off in that domain.
The following domains are covered:
Risk Analytics, Academic discipline, Analytic applications, Architectural analytics, Behavioral analytics, Big data, Business analytics, Business intelligence, Cloud analytics, Complex event processing, Computer programming, Continuous analytics, Cultural analytics, Customer analytics, Data mining, Data presentation architecture, Embedded analytics, Enterprise decision management, Fraud detection, Google Analytics, Human resources, Learning analytics, Machine learning, Marketing mix modeling, Mobile Location Analytics, Neural networks, News analytics, Online analytical processing, Online video analytics, Operational reporting, Operations research, Over-the-counter data, Portfolio analysis, Predictive analytics, Predictive engineering analytics, Predictive modeling, Prescriptive analytics, Price discrimination, Risk analysis, Security information and event management, Semantic analytics, Smart grid, Social analytics, Software analytics, Speech analytics, Statistical discrimination, Stock-keeping unit, Structured data, Telecommunications data retention, Text analytics, Text mining, Time series, Unstructured data, User behavior analytics, Visual analytics, Web analytics, Win–loss analytics:
Risk Analytics Critical Criteria:
Unify Risk Analytics tasks and oversee Risk Analytics requirements.
– A compounding model resolution with available relevant data can often provide insight towards a solution methodology; which Risk Analytics models, tools and techniques are necessary?
– Who will be responsible for documenting the Risk Analytics requirements in detail?
– How do we go about Comparing Risk Analytics approaches/solutions?
Academic discipline Critical Criteria:
Test Academic discipline planning and arbitrate Academic discipline techniques that enhance teamwork and productivity.
– What are your key performance measures or indicators and in-process measures for the control and improvement of your Risk Analytics processes?
– Will Risk Analytics have an impact on current business continuity, disaster recovery processes and/or infrastructure?
– What is our Risk Analytics Strategy?
Analytic applications Critical Criteria:
Model after Analytic applications quality and remodel and develop an effective Analytic applications strategy.
– In the case of a Risk Analytics project, the criteria for the audit derive from implementation objectives. an audit of a Risk Analytics project involves assessing whether the recommendations outlined for implementation have been met. in other words, can we track that any Risk Analytics project is implemented as planned, and is it working?
– How likely is the current Risk Analytics plan to come in on schedule or on budget?
– Have all basic functions of Risk Analytics been defined?
– How do you handle Big Data in Analytic Applications?
– Analytic Applications: Build or Buy?
Architectural analytics Critical Criteria:
Do a round table on Architectural analytics governance and get the big picture.
– Marketing budgets are tighter, consumers are more skeptical, and social media has changed forever the way we talk about Risk Analytics. How do we gain traction?
– Who are the people involved in developing and implementing Risk Analytics?
– What is our formula for success in Risk Analytics ?
Behavioral analytics Critical Criteria:
Pilot Behavioral analytics engagements and get answers.
– How do we know that any Risk Analytics analysis is complete and comprehensive?
– Are accountability and ownership for Risk Analytics clearly defined?
– How to Secure Risk Analytics?
Big data Critical Criteria:
Pay attention to Big data tactics and reinforce and communicate particularly sensitive Big data decisions.
– 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?
– If this nomination is completed on behalf of the customer, has that customer been made aware of this nomination in advance of this submission?
– What is (or would be) the added value of collaborating with other entities regarding data sharing in your sector?
– Should we use data without the permission of individual owners, such as copying publicly available data?
– Does big data threaten the traditional data warehouse business intelligence model stack?
– What type(s) of data does your organization find relevant but has not yet been able to exploit?
– What are the primary business drivers for our initiative. What business challenges do we face?
– What is the Quality of the Result if the Quality of the Data/Metadata is poor?
– How can the benefits of Big Data collection and applications be measured?
– Can good algorithms, models, heuristics overcome Data Quality problems?
– What are the new developments that are included in Big Data solutions?
– When we plan and design, how well do we capture previous experience?
– Future Plans What is the future plan to expand this solution?
– Is recruitment of staff with strong data skills crucial?
– Isnt big data just another way of saying analytics?
– Why should we adopt a Risk Analytics framework?
– How to attract and keep the community involved?
– What preprocessing do we need to do?
– How to use in practice?
– What are we collecting?
Business analytics Critical Criteria:
Demonstrate Business analytics adoptions and differentiate in coordinating Business analytics.
– For your Risk Analytics project, identify and describe the business environment. is there more than one layer to the business environment?
– what is the most effective tool for Statistical Analysis Business Analytics and Business Intelligence?
– What is the difference between business intelligence business analytics and data mining?
– Is there a mechanism to leverage information for business analytics and optimization?
– What is the difference between business intelligence and business analytics?
– what is the difference between Data analytics and Business Analytics If Any?
– How do you pick an appropriate ETL tool or business analytics tool?
– Which individuals, teams or departments will be involved in Risk Analytics?
– What are the trends shaping the future of business analytics?
– How can we improve Risk Analytics?
Business intelligence Critical Criteria:
Accelerate Business intelligence planning and suggest using storytelling to create more compelling Business intelligence projects.
– Does your BI solution honor distinctions with dashboards that automatically authenticate and provide the appropriate level of detail based on a users privileges to the data source?
– Does the software let users work with the existing data infrastructure already in place, freeing your IT team from creating more cubes, universes, and standalone marts?
– Can your software connect to all forms of data, from text and Excel files to cloud and enterprise-grade databases, with a few clicks?
– What is the difference between Key Performance Indicators KPI and Critical Success Factors CSF in a Business Strategic decision?
– Does your bi software work well with both centralized and decentralized data architectures and vendors?
– Are business intelligence solutions starting to include social media data and analytics features?
– What is the difference between Enterprise Information Management and Data Warehousing?
– Is business intelligence set to play a key role in the future of Human Resources?
– Social Data Analytics Are you integrating social into your business intelligence?
– What types of courses do you run and what are their durations?
– Are there any on demand analytics tools in the cloud?
– What are some real time data analysis frameworks?
– What business intelligence systems are available?
– What level of training would you recommend?
– How is business intelligence disseminated?
– What is your licensing model and prices?
– Why do we need business intelligence?
– Do you offer formal user training?
– What is your annual maintenance?
– Does your system provide apis?
Cloud analytics Critical Criteria:
Bootstrap Cloud analytics tactics and finalize specific methods for Cloud analytics acceptance.
– Is there a Risk Analytics Communication plan covering who needs to get what information when?
– Is the Risk Analytics organization completing tasks effectively and efficiently?
Complex event processing Critical Criteria:
Check Complex event processing adoptions and find the essential reading for Complex event processing researchers.
– What are your results for key measures or indicators of the accomplishment of your Risk Analytics strategy and action plans, including building and strengthening core competencies?
– What sources do you use to gather information for a Risk Analytics study?
Computer programming Critical Criteria:
Coach on Computer programming governance and raise human resource and employment practices for Computer programming.
– What will be the consequences to the business (financial, reputation etc) if Risk Analytics does not go ahead or fails to deliver the objectives?
– What are internal and external Risk Analytics relations?
Continuous analytics Critical Criteria:
Look at Continuous analytics failures and get answers.
– To what extent does management recognize Risk Analytics as a tool to increase the results?
– Why is Risk Analytics important for you now?
– Do we have past Risk Analytics Successes?
Cultural analytics Critical Criteria:
Design Cultural analytics engagements and budget for Cultural analytics challenges.
– Consider your own Risk Analytics project. what types of organizational problems do you think might be causing or affecting your problem, based on the work done so far?
– What tools do you use once you have decided on a Risk Analytics strategy and more importantly how do you choose?
Customer analytics Critical Criteria:
Unify Customer analytics risks and correct Customer analytics management by competencies.
– Is Risk Analytics Realistic, or are you setting yourself up for failure?
– What potential environmental factors impact the Risk Analytics effort?
Data mining Critical Criteria:
Familiarize yourself with Data mining planning and finalize specific methods for Data mining acceptance.
– 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 are the business goals Risk Analytics is aiming to achieve?
– What programs do we have to teach data mining?
– What are current Risk Analytics Paradigms?
Data presentation architecture Critical Criteria:
Shape Data presentation architecture tactics and catalog Data presentation architecture activities.
– Do we cover the five essential competencies-Communication, Collaboration,Innovation, Adaptability, and Leadership that improve an organizations ability to leverage the new Risk Analytics in a volatile global economy?
– How do your measurements capture actionable Risk Analytics information for use in exceeding your customers expectations and securing your customers engagement?
– What are specific Risk Analytics Rules to follow?
Embedded analytics Critical Criteria:
Focus on Embedded analytics decisions and catalog what business benefits will Embedded analytics goals deliver if achieved.
– What are your current levels and trends in key measures or indicators of Risk Analytics product and process performance that are important to and directly serve your customers? how do these results compare with the performance of your competitors and other organizations with similar offerings?
– What are the disruptive Risk Analytics technologies that enable our organization to radically change our business processes?
– What are our Risk Analytics Processes?
Enterprise decision management Critical Criteria:
Check Enterprise decision management engagements and develop and take control of the Enterprise decision management initiative.
– How will you measure your Risk Analytics effectiveness?
Fraud detection Critical Criteria:
Unify Fraud detection issues and look at it backwards.
– Can we do Risk Analytics without complex (expensive) analysis?
Google Analytics Critical Criteria:
Prioritize Google Analytics quality and describe which business rules are needed as Google Analytics interface.
– What are the key elements of your Risk Analytics performance improvement system, including your evaluation, organizational learning, and innovation processes?
– Are we making progress? and are we making progress as Risk Analytics leaders?
Human resources Critical Criteria:
Prioritize Human resources planning and report on setting up Human resources without losing ground.
– Do we have processes for managing Human Resources across the business. (eg. staffing skills and numbers are known and predictions are made of future needs? new staff are inducted and trained to suit needs? succession planning is catered for?
– Have we adopted and promoted the companys culture of integrity management, including ethics, business practices and Human Resources evaluations?
– what is to keep those with access to some of an individuals personal data from browsing through other parts of it for other reasons?
– Think about the functions involved in your Risk Analytics project. what processes flow from these functions?
– Do we perform an environmental scan of hr strategies within the hr community (what/how are others planning)?
– How is Staffs willingness to help or refer questions to the proper level?
– How do financial reports support the various aspects of accountability?
– What steps are taken to promote compliance with the hr principles?
– Do you have Human Resources available to support your policies?
– Are you a manager interested in increasing your effectiveness?
– How can we more efficiently on-board and off-board employees?
– How do you view the department and staff members as a whole?
– Do you understand the parameters set by the algorithm?
– Does the company retain personal data indefinitely?
– Are we complying with existing security policies?
– Do you need to develop a Human Resources manual?
– Is our company developing its Human Resources?
– How do we engage the stakeholders?
– What is personal data?
Learning analytics Critical Criteria:
Closely inspect Learning analytics projects and know what your objective is.
– When a Risk Analytics manager recognizes a problem, what options are available?
– Think of your Risk Analytics project. what are the main functions?
Machine learning Critical Criteria:
Debate over Machine learning failures and find out what it really means.
– What are the long-term implications of other disruptive technologies (e.g., machine learning, robotics, data analytics) converging with blockchain development?
– Does Risk Analytics systematically track and analyze outcomes for accountability and quality improvement?
Marketing mix modeling Critical Criteria:
Accumulate Marketing mix modeling decisions and report on the economics of relationships managing Marketing mix modeling and constraints.
– Think about the kind of project structure that would be appropriate for your Risk Analytics project. should it be formal and complex, or can it be less formal and relatively simple?
– Do we monitor the Risk Analytics decisions made and fine tune them as they evolve?
– What is the source of the strategies for Risk Analytics strengthening and reform?
Mobile Location Analytics Critical Criteria:
Categorize Mobile Location Analytics leadership and be persistent.
– What are our best practices for minimizing Risk Analytics project risk, while demonstrating incremental value and quick wins throughout the Risk Analytics project lifecycle?
– What threat is Risk Analytics addressing?
Neural networks Critical Criteria:
Depict Neural networks decisions and give examples utilizing a core of simple Neural networks skills.
– What will drive Risk Analytics change?
News analytics Critical Criteria:
Confer re News analytics risks and shift your focus.
– Who is responsible for ensuring appropriate resources (time, people and money) are allocated to Risk Analytics?
– How is the value delivered by Risk Analytics being measured?
Online analytical processing Critical Criteria:
Define Online analytical processing tactics and correct better engagement with Online analytical processing results.
– Who will be responsible for making the decisions to include or exclude requested changes once Risk Analytics is underway?
– How does the organization define, manage, and improve its Risk Analytics processes?
– Are assumptions made in Risk Analytics stated explicitly?
Online video analytics Critical Criteria:
Group Online video analytics leadership and learn.
– What role does communication play in the success or failure of a Risk Analytics project?
– What are the long-term Risk Analytics goals?
– How do we maintain Risk Analyticss Integrity?
Operational reporting Critical Criteria:
Chat re Operational reporting risks and optimize Operational reporting leadership as a key to advancement.
– At what point will vulnerability assessments be performed once Risk Analytics is put into production (e.g., ongoing Risk Management after implementation)?
Operations research Critical Criteria:
Accommodate Operations research engagements and integrate design thinking in Operations research innovation.
– Who sets the Risk Analytics standards?
– Are there Risk Analytics problems defined?
Over-the-counter data Critical Criteria:
Experiment with Over-the-counter data decisions and transcribe Over-the-counter data as tomorrows backbone for success.
– How do we Identify specific Risk Analytics investment and emerging trends?
– What business benefits will Risk Analytics goals deliver if achieved?
Portfolio analysis Critical Criteria:
Generalize Portfolio analysis quality and learn.
– How do we make it meaningful in connecting Risk Analytics with what users do day-to-day?
– Risk factors: what are the characteristics of Risk Analytics that make it risky?
Predictive analytics Critical Criteria:
Chart Predictive analytics strategies and tour deciding if Predictive analytics progress is made.
– What other organizational variables, such as reward systems or communication systems, affect the performance of this Risk Analytics process?
– What are our needs in relation to Risk Analytics skills, labor, equipment, and markets?
– What are direct examples that show predictive analytics to be highly reliable?
Predictive engineering analytics Critical Criteria:
Troubleshoot Predictive engineering analytics tactics and shift your focus.
– What are the barriers to increased Risk Analytics production?
– What about Risk Analytics Analysis of results?
Predictive modeling Critical Criteria:
Collaborate on Predictive modeling outcomes and modify and define the unique characteristics of interactive Predictive modeling projects.
– Are there any disadvantages to implementing Risk Analytics? There might be some that are less obvious?
– Why is it important to have senior management support for a Risk Analytics project?
– Are you currently using predictive modeling to drive results?
Prescriptive analytics Critical Criteria:
Value Prescriptive analytics projects and explore and align the progress in Prescriptive analytics.
Price discrimination Critical Criteria:
Start Price discrimination quality and correct better engagement with Price discrimination results.
– Does Risk Analytics create potential expectations in other areas that need to be recognized and considered?
– Is the scope of Risk Analytics defined?
Risk analysis Critical Criteria:
Co-operate on Risk analysis tasks and finalize specific methods for Risk analysis acceptance.
– How do risk analysis and Risk Management inform your organizations decisionmaking processes for long-range system planning, major project description and cost estimation, priority programming, and project development?
– What levels of assurance are needed and how can the risk analysis benefit setting standards and policy functions?
– In which two Service Management processes would you be most likely to use a risk analysis and management method?
– How does the business impact analysis use data from Risk Management and risk analysis?
– How do we do risk analysis of rare, cascading, catastrophic events?
– With risk analysis do we answer the question how big is the risk?
– Do we all define Risk Analytics in the same way?
Security information and event management Critical Criteria:
Weigh in on Security information and event management leadership and don’t overlook the obvious.
– What are the success criteria that will indicate that Risk Analytics objectives have been met and the benefits delivered?
– How do we manage Risk Analytics Knowledge Management (KM)?
Semantic analytics Critical Criteria:
Conceptualize Semantic analytics adoptions and track iterative Semantic analytics results.
– How do we Lead with Risk Analytics in Mind?
Smart grid Critical Criteria:
Gauge Smart grid strategies and get the big picture.
– Does your organization perform vulnerability assessment activities as part of the acquisition cycle for products in each of the following areas: Cybersecurity, SCADA, smart grid, internet connectivity, and website hosting?
Social analytics Critical Criteria:
Adapt Social analytics issues and create Social analytics explanations for all managers.
– How do we measure improved Risk Analytics service perception, and satisfaction?
– Who will provide the final approval of Risk Analytics deliverables?
Software analytics Critical Criteria:
Have a session on Software analytics management and probe the present value of growth of Software analytics.
– Who will be responsible for deciding whether Risk Analytics goes ahead or not after the initial investigations?
– Does our organization need more Risk Analytics education?
Speech analytics Critical Criteria:
Grade Speech analytics decisions and figure out ways to motivate other Speech analytics users.
Statistical discrimination Critical Criteria:
Design Statistical discrimination risks and reinforce and communicate particularly sensitive Statistical discrimination decisions.
– Why are Risk Analytics skills important?
Stock-keeping unit Critical Criteria:
Brainstorm over Stock-keeping unit failures and probe using an integrated framework to make sure Stock-keeping unit is getting what it needs.
– What are the usability implications of Risk Analytics actions?
– Which Risk Analytics goals are the most important?
Structured data Critical Criteria:
Examine Structured data tasks and triple focus on important concepts of Structured data relationship management.
– What tools do you consider particularly important to handle unstructured data expressed in (a) natural language(s)?
– Does your organization have the right tools to handle unstructured data expressed in (a) natural language(s)?
– Should you use a hierarchy or would a more structured database-model work best?
Telecommunications data retention Critical Criteria:
Frame Telecommunications data retention outcomes and suggest using storytelling to create more compelling Telecommunications data retention projects.
– Among the Risk Analytics product and service cost to be estimated, which is considered hardest to estimate?
– How do senior leaders actions reflect a commitment to the organizations Risk Analytics values?
– How do we keep improving Risk Analytics?
Text analytics Critical Criteria:
Paraphrase Text analytics engagements and overcome Text analytics skills and management ineffectiveness.
– How do you incorporate cycle time, productivity, cost control, and other efficiency and effectiveness factors into these Risk Analytics processes?
– What may be the consequences for the performance of an organization if all stakeholders are not consulted regarding Risk Analytics?
– Have text analytics mechanisms like entity extraction been considered?
– How do we go about Securing Risk Analytics?
Text mining Critical Criteria:
Categorize Text mining issues and define Text mining competency-based leadership.
– What are the short and long-term Risk Analytics goals?
– Are we Assessing Risk Analytics and Risk?
Time series Critical Criteria:
Review Time series governance and budget for Time series challenges.
– What vendors make products that address the Risk Analytics needs?
Unstructured data Critical Criteria:
Check Unstructured data governance and find answers.
– What are the top 3 things at the forefront of our Risk Analytics agendas for the next 3 years?
– What knowledge, skills and characteristics mark a good Risk Analytics project manager?
User behavior analytics Critical Criteria:
Confer over User behavior analytics projects and stake your claim.
– Have the types of risks that may impact Risk Analytics been identified and analyzed?
Visual analytics Critical Criteria:
Match Visual analytics visions and gather practices for scaling Visual analytics.
– How can skill-level changes improve Risk Analytics?
Web analytics Critical Criteria:
Design Web analytics leadership and acquire concise Web analytics education.
– In a project to restructure Risk Analytics outcomes, which stakeholders would you involve?
– What statistics should one be familiar with for business intelligence and web analytics?
– How will you know that the Risk Analytics project has been successful?
– How is cloud computing related to web analytics?
Win–loss analytics Critical Criteria:
Be responsible for Win–loss analytics visions and reinforce and communicate particularly sensitive Win–loss analytics decisions.
– Does Risk Analytics analysis isolate the fundamental causes of problems?
This quick readiness checklist is a selected resource to help you move forward. Learn more about how to achieve comprehensive insights with the Risk Analytics 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:
Risk Analytics External links:
Financial Risk Analytics – Markit
Risk Analytics Intern 2017c at John Deere • JOFDAV
Leader in Credit Risk Analytics – CreditEdge.com
Academic discipline External links:
Academic Discipline – Earl Warren College
Anthrozoology | academic discipline | Britannica.com
Genealogy As an Academic Discipline – Avotaynu
Analytic applications External links:
Analytic Applications – Gartner IT Glossary
Translating IBM Cognos Analytic Applications content …
Foxtrot Code AI Analytic Applications (Home)
Architectural analytics External links:
Architectural Analytics – Home | Facebook
Best Master’s Degrees in Architectural Analytics 2018
Architectural Analytics – Home | Facebook
Behavioral analytics External links:
Fortscale | Behavioral Analytics for Everyone
Behavioral Analytics | Interana
FraudMAP Behavioral Analytics Solutions Brochure | Fiserv
Big data External links:
Databricks – Making Big Data Simple
Presto | Distributed SQL Query Engine for Big Data
Take 5 Media Group – Build an audience using big data
Business analytics External links:
Business Analytics | Coursera
What is Business Analytics? Webopedia Definition
Business intelligence External links:
List of Business Intelligence Skills – The Balance
Cloud analytics External links:
Cloud Analytics Academy | Hosted by Snowflake
Cloud Analytics – Solutions for Cloud Data Analytics | NetApp
Computer programming External links:
Computer programming | Computing | Khan Academy
Computer Programming – ed2go
Continuous analytics External links:
[PDF]Continuous Analytics: Stream Query Processing in …
Customer analytics External links:
Zylotech- AI For Customer Analytics
BlueVenn – Customer Analytics and Customer Journey …
Data mining External links:
Data mining techniques (Book, 2002) [WorldCat.org]
UT Data Mining
Job Titles in Data Mining – KDnuggets
Data presentation architecture External links:
[PDF]Data Presentation Architecture with Sharing – ijsrd.com
Embedded analytics External links:
Embedded Analytics | Tableau
LaunchWorks | Embedded Analytics Solutions
Embedded Analytics | ThoughtSpot
Enterprise decision management External links:
Enterprise Decision Management (EDM) – Techopedia.com
enterprise decision management Archives – Insights
Enterprise Decision Management | Sapiens DECISION
Fraud detection External links:
Title IV fraud detection | University Business Magazine
Google Analytics External links:
Google Analytics – Sign in
Google Analytics Solutions – Marketing Analytics & …
Human resources External links:
UAB – Human Resources – Careers
Human Resources | Maricopa Community Colleges
Human Resources | Medical University of South Carolina
Learning analytics External links:
Watershed | Learning Analytics for Organizations
Deep Learning Analytics for Satellite Imagery – CrowdAI
Journal of Learning Analytics
Machine learning External links:
What is machine learning? – Definition from WhatIs.com
ZestFinance.com: Machine Learning & Big Data …
Microsoft Azure Machine Learning Studio
Marketing mix modeling External links:
Marketing Mix Modeling – Gartner IT Glossary
Marketing Mix Modeling | Marketing Management Analytics
Mobile Location Analytics External links:
[PDF]Mobile Location Analytics Code of Conduct
Mobile Location Analytics Privacy Notice | Verizon
Neural networks External links:
[PDF]Neural Networks – link.springer.com
Artificial Neural Networks – ScienceDirect
Neural Networks – ScienceDirect.com
News analytics External links:
Yakshof – Big Data News Analytics
News Analytics | Amareos
Online video analytics External links:
Online Video Analytics – JWPlayer.com
http://Ad · JWPlayer.com/FullService
Online Video Analytics & Marketing Software | Vidooly
Operations research External links:
Operations research (Book, 1974) [WorldCat.org]
Operations Research on JSTOR
[PDF]Course Syllabus Course Title: Operations Research
Over-the-counter data External links:
[PDF]Over-the-Counter Data’s Impact on Educators’ Data …
Portfolio analysis External links:
Loan Portfolio Analysis | Visible Equity
Portfolio Analysis – AbeBooks
[PPT]Introduction to Portfolio Analysis – DPCPSI
Predictive analytics External links:
Strategic Location Management & Predictive Analytics | …
Predictive Analytics Software, Social Listening | NewBrand
Predictive Analytics for Healthcare | Forecast Health
Predictive engineering analytics External links:
Predictive engineering analytics is the application of multidisciplinary engineering simulation and test with intelligent reporting and data analytics, to develop digital twins that can predict the real world behavior of products throughout the product lifecycle.
Predictive modeling External links:
DataRobot – Automated Machine Learning for Predictive Modeling
Othot Predictive Modeling | Predictive Analytics Company
Casualty Actuarial Society| Predictive Modeling
Prescriptive analytics External links:
Healthcare Prescriptive Analytics – Cedar Gate …
Price discrimination External links:
Price Discrimination – Investopedia
Risk analysis External links:
Full Monte Project Risk Analysis from Barbecana
http://Risk analysis is the study of the underlying uncertainty of a given course of action. Risk analysis refers to the uncertainty of forecasted future cash flows streams, variance of portfolio/stock returns, statistical analysis to determine the probability of a project’s success or failure, and possible future economic states.
Risk Analysis | Investopedia
Security information and event management External links:
A Guide to Security Information and Event Management
Semantic analytics External links:
SciBite – The Semantic Analytics Company
Semantic Analytics – Get Business Intelligence With …
[PDF]Semantic Analytics in Intelligence: Applying …
Smart grid External links:
Smart Grid – Our Company – Duke Energy
Smart Grid Security (eBook, 2015) [WorldCat.org]
Smart Grid – AbeBooks
Social analytics External links:
Social Analytics Company Socialbakers Raises $26M …
Social Analytics – Marchex
Influencer marketing platform & Social analytics tool – …
Software analytics External links:
EDGEPro Software Analytics Tool for Optometry | Success …
Software Analytics – Microsoft Research
Speech analytics External links:
Speech Analytics | NICE
Yactraq – Speech Analytics & Audio Mining
Speech Analytics | Speech Analytics Software & Audio …
Statistical discrimination External links:
Statistical discrimination (economics) Statistical discrimination is an economic theory of racial or gender inequality based on stereotypes. According to this theory, inequality may exist and persist between demographic groups even when economic agents (consumers, workers, employers, etc.) are rational and non-prejudiced.
“Employer Learning and Statistical Discrimination”
[PDF]Testing for Statistical Discrimination in Health Care
Structured data External links:
Formulas and Structured Data in Excel Tables | Excel …
Structured Data Testing Tool – Google
n4e Ltd Structured Data cabling | Electrical Installations
Telecommunications data retention External links:
Telecommunications data retention | German WOTD
Telecommunications Data Retention and Human …
Text analytics External links:
Text Mining / Text Analytics Specialist – bigtapp
Text Analytics Guide
http://Ad · www.sas.com/text-analytics
Text Analytics Guide
http://Ad · www.sas.com/text-analytics
Text mining External links:
Text Mining White Paper – sas.com
http://Ad · www.sas.com/text-mining
[PDF]Text mining and visualization using VOSviewer – arXiv
Text Mining – AbeBooks
Time series External links:
Initial State – Analytics for Time Series Data
SPK WCDS – Hourly Time Series Reports
[PDF]Time Series Analysis and Forecasting – cengage.com
Unstructured data External links:
What is unstructured data? – Definition from WhatIs.com
User behavior analytics External links:
User Behavior Analytics (UBA) Tools and Solutions | Rapid7
Visual analytics External links:
Visual Analytics Made Easy – Qlik Sense® Desktop
http://Ad · www.qlik.com/Qlik-Sense/Download
Visual Analytics Made Easy – Qlik Sense® Desktop
http://Ad · www.qlik.com/Qlik-Sense/Download
Web analytics External links:
AFS Analytics – Web analytics
11 Best Web Analytics Tools | Inc.com
Web analytics | HitsLink