What is involved in People Analytics
Find out what the related areas are that People 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 People Analytics thinking-frame.
How far is your company on its People Analytics journey?
Take this short survey to gauge your organization’s progress toward People 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 People Analytics related domains to cover and 199 essential critical questions to check off in that domain.
The following domains are covered:
People 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:
People Analytics Critical Criteria:
Substantiate People Analytics results and find out what it really means.
– Are there any easy-to-implement alternatives to People Analytics? Sometimes other solutions are available that do not require the cost implications of a full-blown project?
– Who will be responsible for deciding whether People Analytics goes ahead or not after the initial investigations?
– What are the legal risks in using Big Data/People Analytics in hiring?
– What are specific People Analytics Rules to follow?
Academic discipline Critical Criteria:
Coach on Academic discipline adoptions and do something to it.
– How do you determine the key elements that affect People Analytics workforce satisfaction? how are these elements determined for different workforce groups and segments?
– Is People Analytics Realistic, or are you setting yourself up for failure?
– Is Supporting People Analytics documentation required?
Analytic applications Critical Criteria:
Learn from Analytic applications results and report on the economics of relationships managing Analytic applications and constraints.
– How does the organization define, manage, and improve its People Analytics processes?
– How do you handle Big Data in Analytic Applications?
– Analytic Applications: Build or Buy?
– How much does People Analytics help?
Architectural analytics Critical Criteria:
Generalize Architectural analytics decisions and describe the risks of Architectural analytics sustainability.
– What are our best practices for minimizing People Analytics project risk, while demonstrating incremental value and quick wins throughout the People Analytics project lifecycle?
– How can the value of People Analytics be defined?
– Is People Analytics Required?
Behavioral analytics Critical Criteria:
Check Behavioral analytics governance and point out improvements in Behavioral analytics.
– Do those selected for the People Analytics team have a good general understanding of what People Analytics is all about?
– What are your most important goals for the strategic People Analytics objectives?
Big data Critical Criteria:
Chat re Big data tactics and find the essential reading for Big data researchers.
– Wheres the evidence that using big data intelligently will improve business performance?
– What is the Quality of the Result if the Quality of the Data/Metadata is poor?
– What can management do to improve value creation from data-driven innovation?
– What new Security and Privacy challenge arise from new Big Data solutions?
– How can the benefits of Big Data collection and applications be measured?
– What is the contribution of subsets of the data to the problem solution?
– Hybrid partitioning (across rows/terms and columns/documents) useful?
– How do we track the provenance of the derived data/information?
– How fast can we determine changes in the incoming data?
– Do you see a need to share data processing facilities?
– What are our tools for big data analytics?
– Are our Big Data investment programs results driven?
– Isnt big data just another way of saying analytics?
– What if the data cannot fit on your computer?
– How much data might be lost to pruning?
– How do we measure value of an analytic?
– How can we summarize streaming data?
– So how are managers using big data?
– What is Advanced Analytics?
– What s limiting the task?
Business analytics Critical Criteria:
Understand Business analytics tactics and get going.
– Record-keeping requirements flow from the records needed as inputs, outputs, controls and for transformation of a People Analytics process. ask yourself: are the records needed as inputs to the People Analytics process available?
– 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?
– Is People Analytics dependent on the successful delivery of a current project?
– 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?
– How can we improve People Analytics?
Business intelligence Critical Criteria:
Judge Business intelligence management and intervene in Business intelligence processes and leadership.
– As we develop increasing numbers of predictive models, then we have to figure out how do you pick the targets, how do you optimize the models?
– What is the difference between Key Performance Indicators KPI and Critical Success Factors CSF in a Business Strategic decision?
– What strategies will we pursue to ensure the success of the business intelligence competency center?
– What does a typical data warehouse and business intelligence organizational structure look like?
– What are the approaches to handle RTB related data 100 GB aggregated for business intelligence?
– What is the difference between a data scientist and a business intelligence analyst?
– What are direct examples that show predictive analytics to be highly reliable?
– Does creating or modifying reports or dashboards require a reporting team?
– Does your client support bi-directional functionality with mapping?
– Which other Oracle Business Intelligence products are used in your solution?
– What percentage of enterprise apps will be web based in 3 years?
– What are the main full web business intelligence solutions?
– What would true business intelligence look like?
– How is Business Intelligence related to CRM?
– What are typical reporting applications?
– Do you support video integration?
– Types of data sources supported?
– Business Intelligence Tools?
– Why BI?
Cloud analytics Critical Criteria:
Nurse Cloud analytics management and modify and define the unique characteristics of interactive Cloud analytics projects.
– What knowledge, skills and characteristics mark a good People Analytics project manager?
– What are the business goals People Analytics is aiming to achieve?
– Do we all define People Analytics in the same way?
Complex event processing Critical Criteria:
Tête-à-tête about Complex event processing issues and reinforce and communicate particularly sensitive Complex event processing decisions.
– How do mission and objectives affect the People Analytics processes of our organization?
– What are the record-keeping requirements of People Analytics activities?
Computer programming Critical Criteria:
Illustrate Computer programming strategies and triple focus on important concepts of Computer programming relationship management.
– How do we Improve People Analytics service perception, and satisfaction?
Continuous analytics Critical Criteria:
Give examples of Continuous analytics failures and oversee Continuous analytics requirements.
– Do we cover the five essential competencies-Communication, Collaboration,Innovation, Adaptability, and Leadership that improve an organizations ability to leverage the new People Analytics in a volatile global economy?
Cultural analytics Critical Criteria:
Check Cultural analytics outcomes and don’t overlook the obvious.
– How do you incorporate cycle time, productivity, cost control, and other efficiency and effectiveness factors into these People Analytics processes?
– Will People Analytics have an impact on current business continuity, disaster recovery processes and/or infrastructure?
– What is the purpose of People Analytics in relation to the mission?
Customer analytics Critical Criteria:
Think about Customer analytics strategies and find the essential reading for Customer analytics researchers.
– How will you know that the People Analytics project has been successful?
– Who needs to know about People Analytics ?
– How to deal with People Analytics Changes?
Data mining Critical Criteria:
Deliberate over Data mining management and mentor Data mining customer orientation.
– 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?
– Who is responsible for ensuring appropriate resources (time, people and money) are allocated to People Analytics?
– 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?
– What programs do we have to teach data mining?
Data presentation architecture Critical Criteria:
Wrangle Data presentation architecture management and summarize a clear Data presentation architecture focus.
– Meeting the challenge: are missed People Analytics opportunities costing us money?
– What threat is People Analytics addressing?
Embedded analytics Critical Criteria:
Confer over Embedded analytics failures and tour deciding if Embedded analytics progress is made.
– Do several people in different organizational units assist with the People Analytics process?
– What tools and technologies are needed for a custom People Analytics project?
Enterprise decision management Critical Criteria:
Mine Enterprise decision management engagements and reduce Enterprise decision management costs.
– Do we aggressively reward and promote the people who have the biggest impact on creating excellent People Analytics services/products?
– Does the People Analytics task fit the clients priorities?
Fraud detection Critical Criteria:
Map Fraud detection management and know what your objective is.
– Does People Analytics create potential expectations in other areas that need to be recognized and considered?
– Does People Analytics analysis show the relationships among important People Analytics factors?
Google Analytics Critical Criteria:
Co-operate on Google Analytics governance and display thorough understanding of the Google Analytics process.
– Are assumptions made in People Analytics stated explicitly?
– Is a People Analytics Team Work effort in place?
Human resources Critical Criteria:
Chart Human resources issues and find answers.
– Are Human Resources subject to screening, and do they have terms and conditions of employment defining their information security responsibilities?
– what is to keep those with access to some of an individuals personal data from browsing through other parts of it for other reasons?
– What happens if an individual objects to the collection, use, and disclosure of his or her personal data?
– Do we identify desired outcomes and key indicators (if not already existing) such as what metrics?
– What are strategies that we can undertake to reduce job fatigue and reduced productivity?
– What problems have you encountered with the department or staff member?
– What decisions can you envision making with this type of information?
– How can we more efficiently on-board and off-board employees?
– What are ways that employee productivity can be measured?
– How does the global environment influence management?
– Does all hr data receive the same level of security?
– Does the hr plan make sense to our stakeholders?
– What does the pyramid of information look like?
– How is Promptness of returning calls or e-mail?
– Is our company developing its Human Resources?
– Does the hr plan work for our stakeholders?
– What do users think of the information?
– What are the data sources and data mix?
– Can you trust the algorithm?
Learning analytics Critical Criteria:
Steer Learning analytics planning and research ways can we become the Learning analytics company that would put us out of business.
– What are the Key enablers to make this People Analytics move?
– What is Effective People Analytics?
Machine learning Critical Criteria:
Analyze Machine learning tasks and get out your magnifying glass.
– What are the long-term implications of other disruptive technologies (e.g., machine learning, robotics, data analytics) converging with blockchain development?
– When a People Analytics manager recognizes a problem, what options are available?
– How is the value delivered by People Analytics being measured?
Marketing mix modeling Critical Criteria:
Tête-à-tête about Marketing mix modeling projects and shift your focus.
– What business benefits will People Analytics goals deliver if achieved?
– How can you measure People Analytics in a systematic way?
Mobile Location Analytics Critical Criteria:
Grasp Mobile Location Analytics risks and look at it backwards.
– Think about the functions involved in your People Analytics project. what processes flow from these functions?
– How do we go about Comparing People Analytics approaches/solutions?
Neural networks Critical Criteria:
Grasp Neural networks visions and plan concise Neural networks education.
– How can we incorporate support to ensure safe and effective use of People Analytics into the services that we provide?
News analytics Critical Criteria:
Extrapolate News analytics tasks and correct better engagement with News analytics results.
– Does People Analytics analysis isolate the fundamental causes of problems?
– Which individuals, teams or departments will be involved in People Analytics?
Online analytical processing Critical Criteria:
Collaborate on Online analytical processing projects and summarize a clear Online analytical processing focus.
– How do we Identify specific People Analytics investment and emerging trends?
– Are there People Analytics Models?
Online video analytics Critical Criteria:
Accumulate Online video analytics risks and balance specific methods for improving Online video analytics results.
– How likely is the current People Analytics plan to come in on schedule or on budget?
Operational reporting Critical Criteria:
Contribute to Operational reporting governance and describe which business rules are needed as Operational reporting interface.
– How can you negotiate People Analytics successfully with a stubborn boss, an irate client, or a deceitful coworker?
– What role does communication play in the success or failure of a People Analytics project?
– What vendors make products that address the People Analytics needs?
Operations research Critical Criteria:
Think about Operations research tactics and arbitrate Operations research techniques that enhance teamwork and productivity.
– Will People Analytics deliverables need to be tested and, if so, by whom?
– Are there People Analytics problems defined?
Over-the-counter data Critical Criteria:
Ventilate your thoughts about Over-the-counter data strategies and look for lots of ideas.
Portfolio analysis Critical Criteria:
Powwow over Portfolio analysis results and probe using an integrated framework to make sure Portfolio analysis is getting what it needs.
– Where do ideas that reach policy makers and planners as proposals for People Analytics strengthening and reform actually originate?
Predictive analytics Critical Criteria:
Shape Predictive analytics planning and shift your focus.
– What management system can we use to leverage the People Analytics experience, ideas, and concerns of the people closest to the work to be done?
Predictive engineering analytics Critical Criteria:
Experiment with Predictive engineering analytics outcomes and integrate design thinking in Predictive engineering analytics innovation.
– Who sets the People Analytics standards?
Predictive modeling Critical Criteria:
Recall Predictive modeling management and find out what it really means.
– What may be the consequences for the performance of an organization if all stakeholders are not consulted regarding People Analytics?
– Are there any disadvantages to implementing People Analytics? There might be some that are less obvious?
– What other jobs or tasks affect the performance of the steps in the People Analytics process?
– Are you currently using predictive modeling to drive results?
Prescriptive analytics Critical Criteria:
Own Prescriptive analytics goals and figure out ways to motivate other Prescriptive analytics users.
– What are the key elements of your People Analytics performance improvement system, including your evaluation, organizational learning, and innovation processes?
– How important is People Analytics to the user organizations mission?
Price discrimination Critical Criteria:
Win new insights about Price discrimination visions and arbitrate Price discrimination techniques that enhance teamwork and productivity.
Risk analysis Critical Criteria:
Graph Risk analysis planning and report on developing an effective Risk analysis strategy.
– 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?
Security information and event management Critical Criteria:
Ventilate your thoughts about Security information and event management quality and tour deciding if Security information and event management progress is made.
– In a project to restructure People Analytics outcomes, which stakeholders would you involve?
– Why should we adopt a People Analytics framework?
Semantic analytics Critical Criteria:
Gauge Semantic analytics engagements and know what your objective is.
– What prevents me from making the changes I know will make me a more effective People Analytics leader?
– Is there any existing People Analytics governance structure?
Smart grid Critical Criteria:
Reason over Smart grid visions and get out your magnifying glass.
– 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 are our People Analytics Processes?
Social analytics Critical Criteria:
Probe Social analytics failures and prioritize challenges of Social analytics.
– What is the source of the strategies for People Analytics strengthening and reform?
– Do People Analytics rules make a reasonable demand on a users capabilities?
Software analytics Critical Criteria:
Disseminate Software analytics failures and finalize specific methods for Software analytics acceptance.
– Does People Analytics systematically track and analyze outcomes for accountability and quality improvement?
– What sources do you use to gather information for a People Analytics study?
Speech analytics Critical Criteria:
Communicate about Speech analytics leadership and probe using an integrated framework to make sure Speech analytics is getting what it needs.
– How will you measure your People Analytics effectiveness?
Statistical discrimination Critical Criteria:
Adapt Statistical discrimination quality and document what potential Statistical discrimination megatrends could make our business model obsolete.
– What are the success criteria that will indicate that People Analytics objectives have been met and the benefits delivered?
– How do we go about Securing People Analytics?
Stock-keeping unit Critical Criteria:
Co-operate on Stock-keeping unit projects and shift your focus.
– What are the Essentials of Internal People Analytics Management?
– How can skill-level changes improve People Analytics?
Structured data Critical Criteria:
Consolidate Structured data projects and prioritize challenges of Structured data.
– 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)?
– What new services of functionality will be implemented next with People Analytics ?
– Should you use a hierarchy or would a more structured database-model work best?
Telecommunications data retention Critical Criteria:
Chart Telecommunications data retention visions and create Telecommunications data retention explanations for all managers.
– Risk factors: what are the characteristics of People Analytics that make it risky?
– Do you monitor the effectiveness of your People Analytics activities?
– What will drive People Analytics change?
Text analytics Critical Criteria:
Coach on Text analytics risks and describe which business rules are needed as Text analytics interface.
– Why is it important to have senior management support for a People Analytics project?
– Have text analytics mechanisms like entity extraction been considered?
– Why are People Analytics skills important?
Text mining Critical Criteria:
Differentiate Text mining tactics and diversify disclosure of information – dealing with confidential Text mining information.
– Have the types of risks that may impact People Analytics been identified and analyzed?
– What are the long-term People Analytics goals?
Time series Critical Criteria:
Steer Time series outcomes and get the big picture.
– At what point will vulnerability assessments be performed once People Analytics 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 People Analytics processes?
– Do we monitor the People Analytics decisions made and fine tune them as they evolve?
Unstructured data Critical Criteria:
Check Unstructured data adoptions and gather practices for scaling Unstructured data.
– Have you identified your People Analytics key performance indicators?
– Are there recognized People Analytics problems?
User behavior analytics Critical Criteria:
Use past User behavior analytics results and simulate teachings and consultations on quality process improvement of User behavior analytics.
– In the case of a People Analytics project, the criteria for the audit derive from implementation objectives. an audit of a People Analytics project involves assessing whether the recommendations outlined for implementation have been met. in other words, can we track that any People Analytics project is implemented as planned, and is it working?
Visual analytics Critical Criteria:
Incorporate Visual analytics risks and probe the present value of growth of Visual analytics.
– What are the disruptive People Analytics technologies that enable our organization to radically change our business processes?
– How do we make it meaningful in connecting People Analytics with what users do day-to-day?
Web analytics Critical Criteria:
Derive from Web analytics strategies and transcribe Web analytics as tomorrows backbone for success.
– What statistics should one be familiar with for business intelligence and web analytics?
– How is cloud computing related to web analytics?
– Are we Assessing People Analytics and Risk?
Win–loss analytics Critical Criteria:
Mine Win–loss analytics projects and interpret which customers can’t participate in Win–loss analytics because they lack skills.
This quick readiness checklist is a selected resource to help you move forward. Learn more about how to achieve comprehensive insights with the People 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:
People Analytics External links:
People Analytics Whitepaper | TAHRA News
WhoKnows: Candidate Sourcing and People Analytics …
Humanyze – People Analytics. Better Performance
Academic discipline External links:
What does academic discipline mean? – Definitions.net
Criminal justice | academic discipline | Britannica.com
Analytic applications External links:
Foxtrot Code AI Analytic Applications (Home)
Architectural analytics External links:
Architectural Analytics – Home | Facebook
Behavioral analytics External links:
Behavioral Analytics – Mattersight
Behavioral Analytics | Interana
FraudMAP Behavioral Analytics Solutions Brochure | Fiserv
Big data External links:
Swiftly – Leverage big data to move your city
Event Hubs – Cloud big data solutions | Microsoft Azure
Loudr: Big Data for Music Rights
Business analytics External links:
Business Analytics | Coursera
Advanced Business Analytics | Coursera
Business intelligence External links:
List of Business Intelligence Skills – The Balance
Cloud analytics External links:
Cloud Analytics | Big Data Analytics | Vertica
Cloud Analytics – Solutions for Cloud Data Analytics | NetApp
Cloud Analytics Academy | Hosted by Snowflake
Computer programming External links:
Computer Programming – Augusta Technical College
Computer programming | Computing | Khan Academy
Computer Programming – ed2go
Continuous analytics External links:
[PDF]Continuous Analytics: Stream Query Processing in …
continuous analytics Archives – Iguazio
Cultural analytics External links:
Software Studies Initiative: Cultural analytics
Customer analytics External links:
Customer Analytics and Customer Journey Management
Zylotech- AI For Customer Analytics
Customer Analytics & Predictive Analytics Tools for Business
Data mining External links:
[PDF]Data Mining Mining Text Data – tutorialspoint.com
UT Data Mining
[PDF]Data Mining Report – Federation of American Scientists
Data presentation architecture External links:
[PDF]Data Presentation Architecture with Sharing – ijsrd.com
Embedded analytics External links:
EMBEDDED ANALYTICS – Eventbrite
What is embedded analytics ? – Definition from WhatIs.com
Tailored Embedded Analytics from Logi Analytics
Enterprise decision management External links:
Enterprise Decision Management | Sapiens DECISION
enterprise decision management Archives – Insights
Come to the Enterprise Decision Management Summit in …
Fraud detection External links:
Title IV fraud detection | University Business Magazine
Big Data Fraud Detection | DataVisor
Google Analytics External links:
Enterprise Marketing Analytics – Google Analytics 360 Suite
Google Analytics | Google Developers
Analytics Pros | Google Analytics 360 Consultants & …
Human resources External links:
UAB – Human Resources – Careers
Human Resources | Maricopa Community Colleges
Phila.gov | Human Resources | Jobs
Learning analytics External links:
Learning analytics – MoodleDocs
Journal of Learning Analytics
Learning Analytics Explained (eBook, 2017) [WorldCat.org]
Machine learning External links:
DataRobot – Automated Machine Learning for Predictive …
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:
Mobile Location Analytics Privacy Notice | Verizon
Mobile location analytics | Federal Trade Commission
[PDF]Mobile Location Analytics Code of Conduct
Neural networks External links:
Artificial Neural Networks – ScienceDirect
Neural Networks – ScienceDirect.com
News analytics External links:
Yakshof – Big Data News Analytics
Online analytical processing External links:
Working with Online Analytical Processing (OLAP)
Online video analytics External links:
Managing Your Online Video Analytics – DaCast
Operations research External links:
Operations research | Britannica.com
Systems Engineering and Operations Research
Operations research (Book, 1974) [WorldCat.org]
Over-the-counter data External links:
What is Over-the-Counter Data | IGI Global
Over-the-Counter Data – American Mensa – Medium
Portfolio analysis External links:
[PDF]Portfolio Analysis – Morningstar Log In
Portfolio analysis (Book, 1979) [WorldCat.org]
What is PORTFOLIO ANALYSIS? definition of …
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: Siemens PLM Software
Predictive modeling External links:
DataRobot – Automated Machine Learning for Predictive Modeling
What is predictive modeling? – Definition from WhatIs.com
SDN Predictive Modeling – Student Doctor Network
Prescriptive analytics External links:
Healthcare Prescriptive Analytics – Cedar Gate …
Price discrimination External links:
Price Discrimination Flashcards | Quizlet
Risk analysis External links:
Full Monte Project Risk Analysis from Barbecana
SEC.gov | About the Division of Economic and Risk Analysis
What is Risk Analysis? – Definition from Techopedia
Semantic analytics External links:
[PDF]Geospatial and Temporal Semantic Analytics
What is semantic analytics? – Quora
Smart grid External links:
Smart Grid – AbeBooks
[PDF]Smart Grid Asset Descriptions
[PDF]The Smart Grid?
Social analytics External links:
Enterprise Social Analytics Platform | About
Influencer marketing platform & Social analytics tool – …
Social Analytics – Marchex
Software analytics External links:
Software Analytics – Microsoft Research
EDGEPro Software Analytics Tool for Optometry | Success …
Speech analytics External links:
Speech Analytics ROI Calculator Inquiry – CallMiner
Yactraq – Speech Analytics & Audio Mining
Reverse a Pattern of Poor Sales With Speech Analytics
Statistical discrimination External links:
[PDF]Testing for Statistical Discrimination in Health Care
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”
Structured data External links:
Structured Data Testing Tool – Google
C# HttpWebRequest with XML Structured Data – Stack Overflow
SEC.gov | What Is Structured Data?
Telecommunications data retention External links:
Telecommunications Data Retention and Human …
Text analytics External links:
How to Use Text Analytics in Business – Data Informed
Text Mining / Text Analytics Specialist – bigtapp
[PDF]Syllabus Course Title: Text Analytics – Regis University
Text mining External links:
Text Mining – AbeBooks
Text Mining | Metadata | Portable Document Format
Text mining in practice with R (eBook, 2017) [WorldCat.org]
Time series External links:
InfluxDays | Time Series Data & Applications Conference
SPK WCDS – Hourly Time Series Reports
[PDF]Time Series Analysis and Forecasting – cengage.com
Unstructured data External links:
Gigaom | Sector Roadmap: Unstructured Data …
User behavior analytics External links:
User Behavior Analytics (UBA) Tools and Solutions | Rapid7
Web analytics External links:
AFS Analytics – Web analytics
View Web Analytics reports (SharePoint Server 2010)
11 Best Web Analytics Tools | Inc.com