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 202 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:
Guide Risk Analytics engagements and summarize a clear Risk Analytics focus.
– Do several people in different organizational units assist with the Risk Analytics process?
– Meeting the challenge: are missed Risk Analytics opportunities costing us money?
Academic discipline Critical Criteria:
Revitalize Academic discipline tasks and inform on and uncover unspoken needs and breakthrough Academic discipline results.
– Does Risk Analytics analysis isolate the fundamental causes of problems?
– Are there Risk Analytics problems defined?
– Is Risk Analytics Required?
Analytic applications Critical Criteria:
Have a session on Analytic applications quality and proactively manage Analytic applications risks.
– How can you measure Risk Analytics in a systematic way?
– How do you handle Big Data in Analytic Applications?
– Who needs to know about Risk Analytics ?
– Analytic Applications: Build or Buy?
– How do we Lead with Risk Analytics in Mind?
Architectural analytics Critical Criteria:
Analyze Architectural analytics governance and gather Architectural analytics models .
– Will Risk Analytics have an impact on current business continuity, disaster recovery processes and/or infrastructure?
– What are the top 3 things at the forefront of our Risk Analytics agendas for the next 3 years?
– Is Risk Analytics dependent on the successful delivery of a current project?
Behavioral analytics Critical Criteria:
Scan Behavioral analytics leadership and find out what it really means.
– What prevents me from making the changes I know will make me a more effective Risk Analytics leader?
– What are the record-keeping requirements of Risk Analytics activities?
– How will you measure your Risk Analytics effectiveness?
Big data Critical Criteria:
Debate over Big data adoptions and get the big picture.
– From all data collected by your organization, what is approximately the share of external data (collected from external sources), compared to internal data (produced by your operations)?
– Do you see the need for actions in the area of standardisation (including both formal standards and the promotion of/agreement on de facto standards) related to your sector?
– New roles. Executives interested in leading a big data transition can start with two simple techniques. First, they can get in the habit of asking What do the data say?
– What are the main obstacles that prevent you from having access to all the datasets that are relevant for your organization?
– What rules and regulations should exist about combining data about individuals into a central repository?
– The real challenge: are you willing to get better value and more innovation for some loss of privacy?
– What are some strategies for capacity planning for big data processing and cloud computing?
– How can the best Big Data solution be chosen based on use case requirements?
– How will systems and methods evolve to remove Big Data solution weaknesses?
– What is the contribution of subsets of the data to the problem solution?
– Can analyses improve with better system and environment models?
– Where do you see the need for standardisation actions?
– What are our tools for big data analytics?
– How much data correction can we do at the edges?
– What if the data cannot fit on your computer?
– How much data might be lost to pruning?
– How to deal with too much data?
– Find traffic bottlenecks ?
– What are we missing?
Business analytics Critical Criteria:
Understand Business analytics projects and track iterative Business analytics results.
– 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 your key performance measures or indicators and in-process measures for the control and improvement of your Risk Analytics processes?
– 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?
– What are the trends shaping the future of business analytics?
Business intelligence Critical Criteria:
Have a round table over Business intelligence governance and proactively manage Business intelligence risks.
– Does the software provide fast query performance, either via its own fast in-memory software or by directly connecting to fast data stores?
– Can your software connect to all forms of data, from text and Excel files to cloud and enterprise-grade databases, with a few clicks?
– Is Data Warehouseing necessary for a business intelligence service?
– What are the pros and cons of outsourcing business intelligence?
– What BI functionality do we need, and what are we using today?
– What else does the data tell us that we never thought to ask?
– What are the top trends in the business intelligence space?
– No single business unit responsible for enterprise data?
– What business intelligence systems are available?
– Where is the business intelligence bottleneck?
– Is the product accessible from the internet?
– What are typical reporting applications?
– Describe any training materials offered?
– Do you offer formal user training?
– Types of data sources supported?
– Business Intelligence Tools?
– Why BI?
Cloud analytics Critical Criteria:
Huddle over Cloud analytics adoptions and create a map for yourself.
– Does Risk Analytics 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?
– How do we ensure that implementations of Risk Analytics products are done in a way that ensures safety?
– Are there Risk Analytics Models?
Complex event processing Critical Criteria:
Consolidate Complex event processing projects and summarize a clear Complex event processing focus.
– Where do ideas that reach policy makers and planners as proposals for Risk Analytics strengthening and reform actually originate?
– Is there a Risk Analytics Communication plan covering who needs to get what information when?
Computer programming Critical Criteria:
Examine Computer programming governance and devote time assessing Computer programming and its risk.
– How do we go about Comparing Risk Analytics approaches/solutions?
– What about Risk Analytics Analysis of results?
Continuous analytics Critical Criteria:
Deliberate over Continuous analytics risks and cater for concise Continuous analytics education.
– Think about the functions involved in your Risk Analytics project. what processes flow from these functions?
– How can you negotiate Risk Analytics successfully with a stubborn boss, an irate client, or a deceitful coworker?
– Who is the main stakeholder, with ultimate responsibility for driving Risk Analytics forward?
Cultural analytics Critical Criteria:
Graph Cultural analytics results and balance specific methods for improving Cultural analytics results.
– Does Risk Analytics systematically track and analyze outcomes for accountability and quality improvement?
– Think of your Risk Analytics project. what are the main functions?
– How do we go about Securing Risk Analytics?
Customer analytics Critical Criteria:
Win new insights about Customer analytics strategies and differentiate in coordinating Customer analytics.
Data mining Critical Criteria:
Review Data mining quality and acquire concise Data mining education.
– 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 total cost related to deploying Risk Analytics, including any consulting or professional services?
– What is the difference between Data Analytics Data Analysis Data Mining and Data Science?
– Is business intelligence set to play a key role in the future of Human Resources?
– Are accountability and ownership for Risk Analytics clearly defined?
– What programs do we have to teach data mining?
Data presentation architecture Critical Criteria:
Add value to Data presentation architecture tasks and report on developing an effective Data presentation architecture strategy.
– what is the best design framework for Risk Analytics organization now that, in a post industrial-age if the top-down, command and control model is no longer relevant?
– Do you monitor the effectiveness of your Risk Analytics activities?
– How do we Identify specific Risk Analytics investment and emerging trends?
Embedded analytics Critical Criteria:
Air ideas re Embedded analytics governance and shift your focus.
– What management system can we use to leverage the Risk Analytics experience, ideas, and concerns of the people closest to the work to be done?
– How do we know that any Risk Analytics analysis is complete and comprehensive?
Enterprise decision management Critical Criteria:
Map Enterprise decision management leadership and pioneer acquisition of Enterprise decision management systems.
– How do you incorporate cycle time, productivity, cost control, and other efficiency and effectiveness factors into these Risk Analytics processes?
– When a Risk Analytics manager recognizes a problem, what options are available?
– Is Supporting Risk Analytics documentation required?
Fraud detection Critical Criteria:
Examine Fraud detection tactics and remodel and develop an effective Fraud detection strategy.
– Are there any easy-to-implement alternatives to Risk Analytics? Sometimes other solutions are available that do not require the cost implications of a full-blown project?
– How important is Risk Analytics to the user organizations mission?
– What will drive Risk Analytics change?
Google Analytics Critical Criteria:
Set goals for Google Analytics projects and describe which business rules are needed as Google Analytics interface.
– Does Risk Analytics create potential expectations in other areas that need to be recognized and considered?
– Does the Risk Analytics task fit the clients priorities?
Human resources Critical Criteria:
Troubleshoot Human resources risks and find the ideas you already have.
– Imagine you work in the Human Resources department of a company considering a policy to protect its data on employees mobile devices. in advising on this policy, what rights should be considered?
– Are Human Resources subject to screening, and do they have terms and conditions of employment defining their information security responsibilities?
– What are the procedures for filing an internal complaint about the handling of personal data?
– Does the cloud service provider have necessary security controls on their human resources?
– What are strategies that we can undertake to reduce job fatigue and reduced productivity?
– To satisfy customers and stakeholders, which internal business process must we excel in?
– What are the Human Resources we can bring to establishing new business?
– How do financial reports support the various aspects of accountability?
– What is the important thing that human resources management should do?
– What internal dispute resolution mechanisms are available?
– How can we promote retention of high performing employees?
– Do you understand the parameters set by the algorithm?
– Ease of contacting the Human Resources staff members?
– What does the pyramid of information look like?
– How is the Ease of navigating the hr website?
– Why study Human Resources management (hrm)?
– What do users think of the information?
– Is the hr plan effective ?
– What is personal data?
Learning analytics Critical Criteria:
Map Learning analytics planning and learn.
– Do we aggressively reward and promote the people who have the biggest impact on creating excellent Risk Analytics services/products?
– How do senior leaders actions reflect a commitment to the organizations Risk Analytics values?
Machine learning Critical Criteria:
Refer to Machine learning decisions and tour deciding if Machine learning progress is made.
– Think about the people you identified for your Risk Analytics 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 the long-term implications of other disruptive technologies (e.g., machine learning, robotics, data analytics) converging with blockchain development?
– Is a Risk Analytics Team Work effort in place?
Marketing mix modeling Critical Criteria:
Think about Marketing mix modeling goals and budget for Marketing mix modeling challenges.
– 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 are the usability implications of Risk Analytics actions?
Mobile Location Analytics Critical Criteria:
Depict Mobile Location Analytics engagements and innovate what needs to be done with Mobile Location Analytics.
– 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?
Neural networks Critical Criteria:
Consolidate Neural networks failures and ask questions.
– 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?
News analytics Critical Criteria:
Merge News analytics failures and integrate design thinking in News analytics innovation.
– 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?
Online analytical processing Critical Criteria:
Familiarize yourself with Online analytical processing tasks and slay a dragon.
– What other jobs or tasks affect the performance of the steps in the Risk Analytics process?
– Is there any existing Risk Analytics governance structure?
Online video analytics Critical Criteria:
Graph Online video analytics governance and shift your focus.
– What are the key elements of your Risk Analytics performance improvement system, including your evaluation, organizational learning, and innovation processes?
– Is maximizing Risk Analytics protection the same as minimizing Risk Analytics loss?
Operational reporting Critical Criteria:
Mine Operational reporting tactics and observe effective Operational reporting.
– Do we monitor the Risk Analytics decisions made and fine tune them as they evolve?
– Are we making progress? and are we making progress as Risk Analytics leaders?
– What sources do you use to gather information for a Risk Analytics study?
Operations research Critical Criteria:
Track Operations research planning and stake your claim.
– What is the purpose of Risk Analytics in relation to the mission?
– Do Risk Analytics rules make a reasonable demand on a users capabilities?
Over-the-counter data Critical Criteria:
Scan Over-the-counter data engagements and use obstacles to break out of ruts.
– 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?
– What are the disruptive Risk Analytics technologies that enable our organization to radically change our business processes?
– How do we make it meaningful in connecting Risk Analytics with what users do day-to-day?
Portfolio analysis Critical Criteria:
Be clear about Portfolio analysis issues and inform on and uncover unspoken needs and breakthrough Portfolio analysis results.
– Is Risk Analytics Realistic, or are you setting yourself up for failure?
– Are there recognized Risk Analytics problems?
Predictive analytics Critical Criteria:
Jump start Predictive analytics management and slay a dragon.
– 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 direct examples that show predictive analytics to be highly reliable?
Predictive engineering analytics Critical Criteria:
Judge Predictive engineering analytics leadership and proactively manage Predictive engineering analytics risks.
– At what point will vulnerability assessments be performed once Risk Analytics is put into production (e.g., ongoing Risk Management after implementation)?
– How do we keep improving Risk Analytics?
Predictive modeling Critical Criteria:
Detail Predictive modeling tactics and create a map for yourself.
– Are you currently using predictive modeling to drive results?
Prescriptive analytics Critical Criteria:
Dissect Prescriptive analytics management and stake your claim.
– How likely is the current Risk Analytics plan to come in on schedule or on budget?
Price discrimination Critical Criteria:
Have a session on Price discrimination risks and assess what counts with Price discrimination that we are not counting.
– What is our Risk Analytics Strategy?
Risk analysis Critical Criteria:
Apply Risk analysis tactics and shift your focus.
– 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 does the organization define, manage, and improve its Risk Analytics processes?
– How do we do risk analysis of rare, cascading, catastrophic events?
– With risk analysis do we answer the question how big is the risk?
– Why are Risk Analytics skills important?
Security information and event management Critical Criteria:
Match Security information and event management results and maintain Security information and event management for success.
– What potential environmental factors impact the Risk Analytics effort?
Semantic analytics Critical Criteria:
Learn from Semantic analytics governance and define what our big hairy audacious Semantic analytics goal is.
– How will we insure seamless interoperability of Risk Analytics moving forward?
– How much does Risk Analytics help?
Smart grid Critical Criteria:
Chat re Smart grid tasks and don’t overlook the obvious.
– 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?
– What may be the consequences for the performance of an organization if all stakeholders are not consulted regarding Risk Analytics?
– Who sets the Risk Analytics standards?
– What is Effective Risk Analytics?
Social analytics Critical Criteria:
Consult on Social analytics visions and visualize why should people listen to you regarding Social analytics.
Software analytics Critical Criteria:
Accelerate Software analytics tactics and customize techniques for implementing Software analytics controls.
– How do you determine the key elements that affect Risk Analytics workforce satisfaction? how are these elements determined for different workforce groups and segments?
– Have you identified your Risk Analytics key performance indicators?
– How do we Improve Risk Analytics service perception, and satisfaction?
Speech analytics Critical Criteria:
Be responsible for Speech analytics results and reduce Speech analytics costs.
Statistical discrimination Critical Criteria:
Distinguish Statistical discrimination outcomes and triple focus on important concepts of Statistical discrimination relationship management.
– Does Risk Analytics analysis show the relationships among important Risk Analytics factors?
– Do we have past Risk Analytics Successes?
Stock-keeping unit Critical Criteria:
X-ray Stock-keeping unit risks and achieve a single Stock-keeping unit view and bringing data together.
– Which Risk Analytics goals are the most important?
Structured data Critical Criteria:
Have a session on Structured data visions and work towards be a leading Structured data expert.
– 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:
Cut a stake in Telecommunications data retention projects and drive action.
– What are our needs in relation to Risk Analytics skills, labor, equipment, and markets?
– Do we all define Risk Analytics in the same way?
Text analytics Critical Criteria:
Reconstruct Text analytics results and budget the knowledge transfer for any interested in Text analytics.
– Risk factors: what are the characteristics of Risk Analytics that make it risky?
– Have text analytics mechanisms like entity extraction been considered?
– Can Management personnel recognize the monetary benefit of Risk Analytics?
Text mining Critical Criteria:
Recall Text mining visions and catalog Text mining activities.
– Who will be responsible for making the decisions to include or exclude requested changes once Risk Analytics is underway?
– How will you know that the Risk Analytics project has been successful?
– What are specific Risk Analytics Rules to follow?
Time series Critical Criteria:
Model after Time series leadership and proactively manage Time series risks.
– Who will be responsible for documenting the Risk Analytics requirements in detail?
– What are all of our Risk Analytics domains and what do they do?
Unstructured data Critical Criteria:
Use past Unstructured data outcomes and stake your claim.
– Record-keeping requirements flow from the records needed as inputs, outputs, controls and for transformation of a Risk Analytics process. ask yourself: are the records needed as inputs to the Risk Analytics process available?
– What is the source of the strategies for Risk Analytics strengthening and reform?
– Can we do Risk Analytics without complex (expensive) analysis?
User behavior analytics Critical Criteria:
Value User behavior analytics leadership and improve User behavior analytics service perception.
– To what extent does management recognize Risk Analytics as a tool to increase the results?
– Have the types of risks that may impact Risk Analytics been identified and analyzed?
Visual analytics Critical Criteria:
Have a meeting on Visual analytics tactics and intervene in Visual analytics processes and leadership.
– What tools do you use once you have decided on a Risk Analytics strategy and more importantly how do you choose?
Web analytics Critical Criteria:
Reorganize Web analytics projects and ask what if.
– What statistics should one be familiar with for business intelligence and web analytics?
– What are the Essentials of Internal Risk Analytics Management?
– How is cloud computing related to web analytics?
Win–loss analytics Critical Criteria:
Jump start Win–loss analytics planning and find the ideas you already have.
– What are the short and long-term Risk Analytics goals?
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:
Coverys – Risk Analytics Dashboard
Leader in Credit Risk Analytics – CreditEdge.com
Risk analytics (or risk analysis) is the study of the underlying uncertainty of a given course of action. It often work in tandem with forecasting professionals to minimize future negative unforseen effects.
Academic discipline External links:
Criminal justice | academic discipline | Britannica.com
Folklore | academic discipline | Britannica.com
What does academic discipline mean? – Definitions.net
Analytic applications External links:
Foxtrot Code AI Analytic Applications (Home)
Hype Cycle for Back-Office Analytic Applications, 2017
Analytic Applications – Gartner IT Glossary
Architectural analytics External links:
Architectural Analytics – Home | Facebook
Best Master’s Degrees in Architectural Analytics 2018
Top Online Courses in Architectural Analytics 2018
Behavioral analytics External links:
User and Entity Behavioral Analytics Partners | Exabeam
Fortscale | Behavioral Analytics for Everyone
Behavioral Analytics – Mattersight
Business analytics External links:
Master’s in Business Analytics | Daniels College of Business
Harvard Business Analytics Program
Master of Science in Business Analytics | UW Tacoma
Business intelligence External links:
Business Intelligence Tools & Software | Square
EnsembleIQ | The premier business intelligence resource
Business Intelligence | Microsoft
Cloud analytics External links:
Cloud Analytics Academy – Official Site
Cloud Analytics World Tour | Snowflake
Complex event processing External links:
Complex Event Processing (CEP) for Big Data Streaming
Computer programming External links:
Coding for Kids | Computer Programming | AgentCubes online
Gwinnett Technical College- Computer Programming
Computer Programming, Robotics & Engineering – STEM For Kids
Customer analytics External links:
Customer Analytics & Predictive Analytics Tools for Business
Customer Analytics and Customer Journey Management
Customer Analytics Services and Solutions | TransUnion
Data mining External links:
Data Mining | Coursera
UT Data Mining
Analytics and Data Mining Programs
Embedded analytics External links:
Power BI Embedded analytics | Microsoft Azure
What Is Embedded Analytics? | Logi Analytics Blog
LaunchWorks | Embedded Analytics Solutions
Enterprise decision management External links:
enterprise decision management Archives – Insights
Enterprise Decision Management | Sapiens DECISION
Enterprise Decision Management (EDM) – Techopedia.com
Fraud detection External links:
Fraud Detection and Anti-Money Laundering Software – Verafin
Business Fraud Detection | Fraud Shield by Experian
Debit Card Security | Fraud Detection & Protection | RushCard
Google Analytics External links:
Welcome to the Texas Board of Nursing – Google Analytics
Google Analytics | Google Developers
Google Analytics Solutions – Marketing Analytics & …
Human resources External links:
Title Human Resources HR Jobs, Employment | Indeed.com
Office of Human Resources – TITLE IX
Human Resources Job Titles | Enlighten Jobs
Learning analytics External links:
Watershed | Learning Analytics for Organizations
Deep Learning Analytics
“Using Learning Analytics to Predict Academic Success …
Machine learning External links:
Microsoft Azure Machine Learning Studio
Amazon EC2 P3 – Ideal for Machine Learning and HPC – AWS
Endpoint Protection – Machine Learning Security | …
Marketing mix modeling External links:
What is an Example of Marketing Mix Modeling?
Marketing Mix Modeling | Marketing Management Analytics
Marketing Mix Modeling – Decision Analyst
Mobile Location Analytics External links:
[PDF]Mobile Location Analytics Code of Conduct
Mobile Location Analytics Privacy Notice | Verizon
Mobile location analytics | Federal Trade Commission
Neural networks External links:
Neural Networks and Deep Learning | Coursera
What is the learning rate in neural networks? – Quora
News analytics External links:
RavenPack News Analytics – RavenPack
Online analytical processing External links:
Working with Online Analytical Processing (OLAP)
Online video analytics External links:
Ooyala Videomind | Online Video Analytics
Online Video Analytics & Marketing Software | Vidooly
Global Online Video Analytics Market Market Research
Operational reporting External links:
Operational Reporting – InfoSync Services
Operations research External links:
Operations Research: INFORMS
Operations Research (O.R.), or operational research in the U.K, is a discipline that deals with the application of advanced analytical methods to help make better decisions.
Systems Engineering and Operations Research
Over-the-counter data External links:
[PDF]Over-the-Counter Data’s Impact on Educators’ Data …
Over-the-Counter Data – American Mensa – Medium
Portfolio analysis External links:
iCite | NIH Office of Portfolio Analysis
Portfolio Analysis Final-1 Flashcards | Quizlet
Analysis: Portfolio Analysis Flashcards | Quizlet
Predictive analytics External links:
Predictive Analytics Solutions for Global Industry | Uptake
Strategic Location Management & Predictive Analytics | …
What is predictive analytics? – Definition from WhatIs.com
Predictive engineering analytics External links:
Predictive engineering analytics includes both the tactics and tools that manufacturers can leverage to expand traditional design verification and validation into a predictive role in support of systems-driven product development.
Predictive modeling External links:
What is predictive modeling? – Definition from …
DataRobot – Automated Machine Learning for Predictive Modeling
Prescriptive analytics External links:
Prescriptive analytics – ccjdigital.com
Prescriptive Analytics | IBM Analytics
Healthcare Prescriptive Analytics – Cedar Gate …
Price discrimination External links:
Price Discrimination – Investopedia
3 Types of Price Discrimination | Chron.com
MBAecon – 1st, 2nd and 3rd Price discrimination
Risk analysis External links:
What is risk analysis? – Definition from WhatIs.com
Risk Analysis | Investopedia
MyRisk®: Secure Risk Assessment and Risk Analysis …
Security information and event management External links:
A Guide to Security Information and Event Management
Magic Quadrant for Security Information and Event Management
Semantic analytics External links:
SciBite – The Semantic Analytics Company
[PDF]Semantic Analytics in Intelligence: Applying …
[PDF]Semantic Analytics – Northfield
Smart grid External links:
Smart Grid – AbeBooks
[PDF]Smart Grid Asset Descriptions
Smart Grid – Citizens Utility Board
Social analytics External links:
Social Analytics One – Social Analytics One
Google Search with Social Analytics – ctrlq.org
Influencer marketing platform & Social analytics tool – …
Software analytics External links:
EDGEPro | EDGEPro Software Analytics Tool for Optometry
Software Analytics – Microsoft Research
EDGEPro Software Analytics Tool for Optometry | Success …
Speech analytics External links:
Eureka: Speech Analytics Software | CallMiner
Best Speech Analytics Solutions in 2018 | IT Central Station
Speech Analytics & Speech Recognition – TranscribeMe
Statistical discrimination External links:
“Employer Learning and Statistical Discrimination”
Structured data External links:
Structured Data for Dummies – Search Engine Journal
Providing Structured Data | Custom Search | Google Developers
Structured Data Testing Tool – Google
Telecommunications data retention External links:
Telecommunications Data Retention and Human …
Text analytics External links:
The Truth about Text Analytics and Sentiment Analysis
Text Mining / Text Analytics Specialist – bigtapp
Text analytics software| NICE LTD | NICE
Text mining External links:
Text Mining with R
Text Mining / Text Analytics Specialist – bigtapp
Text mining in practice with R (eBook, 2017) [WorldCat.org]
Time series External links:
[PDF]Time Series Analysis and Forecasting – cengage.com
pandas Time Series Basics – chrisalbon.com
1.1 Overview of Time Series Characteristics | STAT 510
Unstructured data External links:
Scale-Out NAS for Unstructured Data | Dell EMC US
Structured vs. Unstructured data – BrightPlanet
Differences Between Structured & Unstructured Data – …
User behavior analytics External links:
User Behavior Analytics (UBA) Tools and Solutions | Rapid7
User Behavior Analytics (UBA) Tools and Solutions | Rapid7
Veriato Recon | User Behavior Analytics Software
Visual analytics External links:
CSE 6242 – Data and Visual Analytics
Web analytics External links:
11 Best Web Analytics Tools | Inc.com
Careers | Mobile & Web Analytics | Mixpanel
Web Analytics in Real Time | Clicky