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 194 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:
Powwow over People Analytics goals and learn.
– what is the best design framework for People Analytics organization now that, in a post industrial-age if the top-down, command and control model is no longer relevant?
– Is there a People Analytics Communication plan covering who needs to get what information when?
– What are the legal risks in using Big Data/People Analytics in hiring?
– What are the business goals People Analytics is aiming to achieve?
Academic discipline Critical Criteria:
X-ray Academic discipline outcomes and visualize why should people listen to you regarding Academic discipline.
– What new services of functionality will be implemented next with People Analytics ?
– What are your most important goals for the strategic People Analytics objectives?
– What vendors make products that address the People Analytics needs?
Analytic applications Critical Criteria:
Investigate Analytic applications strategies and define what our big hairy audacious Analytic applications goal is.
– What will be the consequences to the business (financial, reputation etc) if People Analytics does not go ahead or fails to deliver the objectives?
– How do senior leaders actions reflect a commitment to the organizations People Analytics values?
– How do you handle Big Data in Analytic Applications?
– Analytic Applications: Build or Buy?
Architectural analytics Critical Criteria:
Brainstorm over Architectural analytics results and arbitrate Architectural analytics techniques that enhance teamwork and productivity.
– What are your results for key measures or indicators of the accomplishment of your People Analytics strategy and action plans, including building and strengthening core competencies?
– How is the value delivered by People Analytics being measured?
– How do we go about Securing People Analytics?
Behavioral analytics Critical Criteria:
Define Behavioral analytics outcomes and secure Behavioral analytics creativity.
– How do your measurements capture actionable People Analytics information for use in exceeding your customers expectations and securing your customers engagement?
– What will drive People Analytics change?
Big data Critical Criteria:
Guide Big data decisions and look in other fields.
– A compounding model resolution with available relevant data can often provide insight towards a solution methodology; which People Analytics models, tools and techniques are necessary?
– Have we let algorithms and large centralized data centres not only control the remembering but also the meaning and interpretation of the data?
– Do we address the daunting challenge of Big Data: how to make an easy use of highly diverse data and provide knowledge?
– What is (or would be) the added value of collaborating with other entities regarding data sharing in your sector?
– Does your organization perceive the need for more effort to promote security and trust in data technologies?
– What is the quantifiable ROI for this solution (cost / time savings / data error minimization / etc)?
– What are the disruptive innovations in the middle-term that provide near-term domain leadership?
– what is needed to build a data-driven application that runs on streams of fast and big data?
– Wheres the evidence that using big data intelligently will improve business performance?
– In which way does big data create, or is expected to create, value in the organization?
– How does big data impact Data Quality and governance best practices?
– Can good algorithms, models, heuristics overcome Data Quality problems?
– Which Oracle Data Integration products are used in your solution?
– Can we really afford to store and process all that data?
– Are our Big Data investment programs results driven?
– What metrics do we use to assess the results?
– So how are managers using big data?
– Does Big Data Really Need HPC?
– What s limiting the task?
– What is Big Data to us?
Business analytics Critical Criteria:
Cut a stake in Business analytics issues and prioritize challenges of Business analytics.
– What are your current levels and trends in key measures or indicators of People 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 is the most effective tool for Statistical Analysis Business Analytics and Business Intelligence?
– Does People Analytics systematically track and analyze outcomes for accountability and quality improvement?
– 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?
– Do we have past People Analytics Successes?
Business intelligence Critical Criteria:
Closely inspect Business intelligence failures and pioneer acquisition of Business intelligence systems.
– Self-service analysis is meaningless unless users can trust that the data comes from an approved source and is up to date. Does your BI solution create a strong partnership with IT to ensure that data, whether from extracts or live connections, is 100-percent accurate?
– Forget right-click and control+z. mobile interactions are fundamentally different from those on a desktop. does your mobile solution allow you to interact with desktop-authored dashboards using touchscreen gestures like taps, flicks, and pinches?
– 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?
– When users are more fluid and guest access is a must, can you choose hardware-based licensing that is tailored to your exact configuration needs?
– Does your mobile solution allow you to interact with desktop-authored dashboards using touchscreen gestures like taps, flicks, and pinches?
– What strategies will we pursue to ensure the success of the business intelligence competency center?
– Why does animosity endure between IT and business when it comes to business intelligence?
– Does big data threaten the traditional data warehouse business intelligence model stack?
– What is the future scope for combination of Business Intelligence and Cloud Computing?
– What are some best practices for gathering business intelligence about a competitor?
– Is business intelligence set to play a key role in the future of human resources?
– Does creating or modifying reports or dashboards require a reporting team?
– What tools are there for publishing sharing and visualizing data online?
– How will marketing change in the next 10 years?
– Where is the business intelligence bottleneck?
– How is Business Intelligence related to CRM?
– Describe any training materials offered?
– Do you still need a data warehouse?
Cloud analytics Critical Criteria:
Graph Cloud analytics outcomes and get the big picture.
– What is the purpose of People Analytics in relation to the mission?
– How do we Lead with People Analytics in Mind?
– Are there People Analytics problems defined?
Complex event processing Critical Criteria:
Revitalize Complex event processing tasks and get out your magnifying glass.
– Who will provide the final approval of People Analytics deliverables?
– How can you measure People Analytics in a systematic way?
Computer programming Critical Criteria:
Recall Computer programming tactics and catalog what business benefits will Computer programming goals deliver if achieved.
– What sources do you use to gather information for a People Analytics study?
– What is Effective People Analytics?
Continuous analytics Critical Criteria:
Confer over Continuous analytics projects and define what our big hairy audacious Continuous analytics goal is.
– Are assumptions made in People Analytics stated explicitly?
– Are there recognized People Analytics problems?
Cultural analytics Critical Criteria:
Scan Cultural analytics projects and simulate teachings and consultations on quality process improvement of Cultural analytics.
– Does People 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?
– 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?
– Are we Assessing People Analytics and Risk?
Customer analytics Critical Criteria:
Reorganize Customer analytics risks and point out Customer analytics tensions in leadership.
– Are there any disadvantages to implementing People Analytics? There might be some that are less obvious?
– Can we do People Analytics without complex (expensive) analysis?
Data mining Critical Criteria:
Illustrate Data mining planning and diversify by understanding risks and leveraging Data mining.
– 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?
– How do we ensure that implementations of People Analytics products are done in a way that ensures safety?
– What is the difference between Data Analytics Data Analysis Data Mining and Data Science?
– What are all of our People Analytics domains and what do they do?
– What programs do we have to teach data mining?
Data presentation architecture Critical Criteria:
Coach on Data presentation architecture tactics and report on developing an effective Data presentation architecture strategy.
– What are the disruptive People Analytics technologies that enable our organization to radically change our business processes?
– Is People Analytics Realistic, or are you setting yourself up for failure?
Embedded analytics Critical Criteria:
Match Embedded analytics issues and devote time assessing Embedded analytics and its risk.
– Marketing budgets are tighter, consumers are more skeptical, and social media has changed forever the way we talk about People Analytics. How do we gain traction?
– How do we know that any People Analytics analysis is complete and comprehensive?
– How to Secure People Analytics?
Enterprise decision management Critical Criteria:
Contribute to Enterprise decision management tactics and diversify by understanding risks and leveraging Enterprise decision management.
– What knowledge, skills and characteristics mark a good People Analytics project manager?
– Is the People Analytics organization completing tasks effectively and efficiently?
– How do we go about Comparing People Analytics approaches/solutions?
Fraud detection Critical Criteria:
Conceptualize Fraud detection tactics and ask what if.
– Among the People Analytics product and service cost to be estimated, which is considered hardest to estimate?
Google Analytics Critical Criteria:
Transcribe Google Analytics leadership and tour deciding if Google Analytics progress is made.
– Risk factors: what are the characteristics of People Analytics that make it risky?
Human resources Critical Criteria:
Explore Human resources tactics and innovate what needs to be done with Human resources.
– Who will be responsible for leading the various bcp teams (e.g., crisis/emergency, recovery, technology, communications, facilities, Human Resources, business units and processes, Customer Service)?
– Describe your views on the value of human assets in helping an organization achieve its goals. how important is it for organizations to train and develop their Human Resources?
– If there is recognition by both parties of the potential benefits of an alliance, but adequate qualified human resources are not available at one or both firms?
– Are Human Resources subject to screening, and do they have terms and conditions of employment defining their information security responsibilities?
– Do the response plans address damage assessment, site restoration, payroll, Human Resources, information technology, and administrative support?
– Is there a role for employees to play in maintaining the accuracy of personal data the company maintains?
– Is the crisis management team comprised of members from Human Resources?
– What is the important thing that human resources management should do?
– To achieve our goals, how must our organization learn and innovate?
– How does the company provide notice of its information practices?
– How should any risks to privacy and civil liberties be managed?
– How is Staffs knowledge of procedures and regulations?
– Are we complying with existing security policies?
– How is the Content updated of the hr website?
– Does the hr plan work for our stakeholders?
– Who should appraise performance?
Learning analytics Critical Criteria:
Revitalize Learning analytics engagements and correct better engagement with Learning analytics results.
– Does People Analytics analysis isolate the fundamental causes of problems?
– How will you measure your People Analytics effectiveness?
– Why are People Analytics skills important?
Machine learning Critical Criteria:
Win new insights about Machine learning risks and create Machine learning explanations for all managers.
– What are the long-term implications of other disruptive technologies (e.g., machine learning, robotics, data analytics) converging with blockchain development?
– Do we monitor the People Analytics decisions made and fine tune them as they evolve?
Marketing mix modeling Critical Criteria:
Steer Marketing mix modeling leadership and question.
– What are the barriers to increased People Analytics production?
– How much does People Analytics help?
Mobile Location Analytics Critical Criteria:
Discourse Mobile Location Analytics tactics and look in other fields.
– In what ways are People Analytics vendors and us interacting to ensure safe and effective use?
– Does the People Analytics task fit the clients priorities?
– How can the value of People Analytics be defined?
Neural networks Critical Criteria:
Illustrate Neural networks goals and create a map for yourself.
– Is People Analytics Required?
News analytics Critical Criteria:
Substantiate News analytics risks and maintain News analytics for success.
– Can we add value to the current People Analytics decision-making process (largely qualitative) by incorporating uncertainty modeling (more quantitative)?
– What are the top 3 things at the forefront of our People Analytics agendas for the next 3 years?
– What business benefits will People Analytics goals deliver if achieved?
Online analytical processing Critical Criteria:
Meet over Online analytical processing outcomes and adopt an insight outlook.
– What are our needs in relation to People Analytics skills, labor, equipment, and markets?
Online video analytics Critical Criteria:
Brainstorm over Online video analytics visions and describe which business rules are needed as Online video analytics interface.
– Think about the people you identified for your People 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?
– Is the scope of People Analytics defined?
Operational reporting Critical Criteria:
Transcribe Operational reporting projects and devise Operational reporting key steps.
– How will we insure seamless interoperability of People Analytics moving forward?
– Does our organization need more People Analytics education?
Operations research Critical Criteria:
Add value to Operations research projects and attract Operations research skills.
– 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?
– Who is the main stakeholder, with ultimate responsibility for driving People Analytics forward?
Over-the-counter data Critical Criteria:
Analyze Over-the-counter data decisions and look at it backwards.
– How can we incorporate support to ensure safe and effective use of People Analytics into the services that we provide?
Portfolio analysis Critical Criteria:
Consult on Portfolio analysis management and probe Portfolio analysis strategic alliances.
– What other organizational variables, such as reward systems or communication systems, affect the performance of this People Analytics process?
– Have you identified your People Analytics key performance indicators?
Predictive analytics Critical Criteria:
Debate over Predictive analytics risks and correct better engagement with Predictive analytics results.
– What are direct examples that show predictive analytics to be highly reliable?
Predictive engineering analytics Critical Criteria:
Concentrate on Predictive engineering analytics governance and explore and align the progress in Predictive engineering analytics.
– Will People Analytics have an impact on current business continuity, disaster recovery processes and/or infrastructure?
– Does People Analytics analysis show the relationships among important People Analytics factors?
Predictive modeling Critical Criteria:
Examine Predictive modeling strategies and budget the knowledge transfer for any interested in Predictive modeling.
– How can you negotiate People Analytics successfully with a stubborn boss, an irate client, or a deceitful coworker?
– Think of your People Analytics project. what are the main functions?
– Are you currently using predictive modeling to drive results?
Prescriptive analytics Critical Criteria:
Deliberate over Prescriptive analytics management and intervene in Prescriptive analytics processes and leadership.
– How does the organization define, manage, and improve its People Analytics processes?
– How would one define People Analytics leadership?
Price discrimination Critical Criteria:
Analyze Price discrimination projects and sort Price discrimination activities.
– Do People Analytics rules make a reasonable demand on a users capabilities?
– How do we manage People Analytics Knowledge Management (KM)?
Risk analysis Critical Criteria:
Jump start Risk analysis goals and summarize a clear Risk analysis 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?
– 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?
– 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?
– Is a People Analytics Team Work effort in place?
– What threat is People Analytics addressing?
Security information and event management Critical Criteria:
Refer to Security information and event management quality and point out Security information and event management tensions in leadership.
– What potential environmental factors impact the People Analytics effort?
Semantic analytics Critical Criteria:
Inquire about Semantic analytics governance and be persistent.
Smart grid Critical Criteria:
Face Smart grid issues and optimize Smart grid leadership as a key to advancement.
– 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?
– Are accountability and ownership for People Analytics clearly defined?
Social analytics Critical Criteria:
Talk about Social analytics leadership and maintain Social analytics for success.
– Why is People Analytics important for you now?
Software analytics Critical Criteria:
Cut a stake in Software analytics governance and get going.
– Why is it important to have senior management support for a People Analytics project?
Speech analytics Critical Criteria:
Distinguish Speech analytics outcomes and find out what it really means.
Statistical discrimination Critical Criteria:
Steer Statistical discrimination decisions and innovate what needs to be done with Statistical discrimination.
– To what extent does management recognize People Analytics as a tool to increase the results?
Stock-keeping unit Critical Criteria:
X-ray Stock-keeping unit visions and look at it backwards.
Structured data Critical Criteria:
Graph Structured data outcomes and define what do we need to start doing with 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)?
– Should you use a hierarchy or would a more structured database-model work best?
Telecommunications data retention Critical Criteria:
Contribute to Telecommunications data retention planning and question.
– Think about the functions involved in your People Analytics project. what processes flow from these functions?
Text analytics Critical Criteria:
Guide Text analytics tasks and acquire concise Text analytics education.
– Where do ideas that reach policy makers and planners as proposals for People Analytics strengthening and reform actually originate?
– Have text analytics mechanisms like entity extraction been considered?
Text mining Critical Criteria:
Distinguish Text mining planning and find out.
– What is our formula for success in People Analytics ?
Time series Critical Criteria:
Dissect Time series engagements and work towards be a leading Time series expert.
– Does People Analytics create potential expectations in other areas that need to be recognized and considered?
– Why should we adopt a People Analytics framework?
Unstructured data Critical Criteria:
Interpolate Unstructured data projects and attract Unstructured data skills.
User behavior analytics Critical Criteria:
Examine User behavior analytics outcomes and look at it backwards.
– What is the source of the strategies for People Analytics strengthening and reform?
– How do we Improve People Analytics service perception, and satisfaction?
Visual analytics Critical Criteria:
Reconstruct Visual analytics planning and cater for concise Visual analytics education.
– Think about the kind of project structure that would be appropriate for your People Analytics project. should it be formal and complex, or can it be less formal and relatively simple?
– Who will be responsible for documenting the People Analytics requirements in detail?
Web analytics Critical Criteria:
Give examples of Web analytics tactics and clarify ways to gain access to competitive Web analytics services.
– What statistics should one be familiar with for business intelligence and web analytics?
– How likely is the current People Analytics plan to come in on schedule or on budget?
– How is cloud computing related to web analytics?
Win–loss analytics Critical Criteria:
Match Win–loss analytics adoptions and display thorough understanding of the Win–loss analytics process.
– How do we Identify specific People Analytics investment and emerging trends?
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:
Wharton People Analytics
WhoKnows – People Analytics & Workforce Management …
People Analytics Software | TrenData
Academic discipline External links:
Academic Discipline Events – Northwest Nazarene …
criminal justice | academic discipline | Britannica.com
Analytic applications External links:
Hype Cycle for Back-Office Analytic Applications, 2017
Architectural analytics External links:
Architectural Analytics – Home | Facebook
Behavioral analytics External links:
Behavioral Analytics | Interana
Niara | No Compromise Behavioral Analytics
Security and IT Risk Intelligence with Behavioral Analytics
Big data External links:
Pepperdata: DevOps for Big Data
Qognify: Big Data Solutions for Physical Security & …
Business Intelligence and Big Data Analytics Software
Business analytics External links:
Business Analytics – The Current State of BI & Analytics
http://Ad · spotfire.tibco.com/analytics
Business Analytics – The Current State of BI & Analytics
http://Ad · spotfire.tibco.com/analytics
Business intelligence External links:
List of Business Intelligence Skills – The Balance
Cloud analytics External links:
Financial Services – Cloud Analytics City Tour
Cloud Analytics | Big Data Analytics | HPE Vertica
Computer programming External links:
Computer Programming – Augusta Technical College
Computer Programming, Robotics & Engineering – STEM For Kids
Computer programming | Computing | Khan Academy
Continuous analytics External links:
[PDF]Continuous Analytics: Stream Query Processing in …
Continuous Analytics: Why You Must Consider It – Zymr
Cultural analytics External links:
Cultural analytics is the exploration and research of massive cultural data sets of visual material – both digitized visual artifacts and contemporary visual and interactive media.
Customer analytics External links:
BlueVenn – Customer Analytics and Customer Journey …
Customer Analytics – Gartner IT Glossary
Data mining External links:
[PDF]Project Title: Data Mining to Improve Water Management
[PDF]Data Mining Report – fas.org
[PDF]Data Mining Mining Text Data – tutorialspoint.com
Embedded analytics External links:
What is embedded analytics ? – Definition from WhatIs.com
Logi Analytics: The #1 Embedded Analytics Platform
Power BI Embedded analytics | Microsoft Azure
Enterprise decision management External links:
Enterprise Decision Management (EDM) – Techopedia.com
Come to the Enterprise Decision Management Summit in …
enterprise decision management Archives – Insights
Fraud detection External links:
Title IV fraud detection | University Business Magazine
Google Analytics External links:
iDimension | Google Analytics Certified Partner
Welcome to the Texas Board of Nursing – Google Analytics
Human resources External links:
Department of Human Resources Home – TN.Gov
Human Resources / For Applicants
NC Office of Human Resources
Learning analytics External links:
Journal of Learning Analytics
Learning analytics – MoodleDocs
Chapter 1 | Society for Learning Analytics Research (SoLAR)
Marketing mix modeling External links:
Marketing Mix Modeling – Decision Analyst
Marketing Mix Modeling | Marketing Management Analytics
Mobile Location Analytics External links:
Mobile Location Analytics Privacy Notice | Verizon
[PDF]Mobile Location Analytics Code of Conduct
Critigen Medicare Mapper Mobile Location Analytics …
Neural networks External links:
Neural Networks – Home
Online analytical processing External links:
Working with Online Analytical Processing (OLAP)
Oracle Online Analytical Processing (OLAP)
Operations research External links:
[PDF]Course Syllabus Course Title: Operations Research
Operations research (Book, 2014) [WorldCat.org]
Operations Research on JSTOR
Over-the-counter data External links:
Standards — Over-the-Counter Data
Portfolio analysis External links:
iCite | NIH Office of Portfolio Analysis
What is PORTFOLIO ANALYSIS? definition of …
Portfolio Analysis – AbeBooks
Predictive analytics External links:
Store Lifecycle Management & Predictive Analytics | Tango
Predictive Analytics Software, Social Listening | NewBrand
Customer Analytics & Predictive Analytics Tools for Business
Predictive engineering analytics External links:
Predictive Engineering Analytics: Siemens PLM Software
Predictive modeling External links:
Othot Predictive Modeling | Predictive Analytics Company
Prescriptive analytics External links:
How to Get Started With Prescriptive Analytics
Healthcare Prescriptive Analytics – Cedar Gate …
Price discrimination External links:
What Every Business Should Know About Price Discrimination
ERIC – Marketing Theory Applied to Price Discrimination …
Price Discrimination Flashcards | Quizlet
Risk analysis External links:
What is Risk Analysis? – Definition from Techopedia
Risk Analysis and Risk Management – Decision Making …
What is risk analysis? – Definition from WhatIs.com
Smart grid External links:
Honeywell Smart Grid
SMART GRID SUMMITS
Smart Grid – AbeBooks
Social analytics External links:
The Complete Social Analytics Solution | Simply Measured
Enterprise Social Analytics Platform | About
Dark Social Analytics: Track Private Shares with GetSocial
Speech analytics External links:
Impact 360 Speech Analytics
VoiceBase – APIs for Speech Recognition & Speech Analytics
Speech Analytics – Marchex
Statistical discrimination External links:
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”
Stock-keeping unit External links:
SKU (stock-keeping unit) – Gartner IT Glossary
Structured data External links:
n4e Ltd Structured Data cabling | Electrical Installations
SEC.gov | What Is Structured Data?
Introduction to Structured Data | Search | Google Developers
Telecommunications data retention External links:
Telecommunications Data Retention and Human …
Text analytics External links:
Machine Learning, Cognitive Search & Text Analytics | Attivio
Text analytics software| NICE LTD | NICE
Text mining External links:
Text Mining – AbeBooks
[PDF]Text Mining – UP – paginas.fe.up.pt
Text Mining in R: A Tutorial – Springboard Blog
Time series External links:
Initial State – Analytics for Time Series Data
Unstructured data External links:
Isilon Scale-Out NAS Storage-Unstructured Data | Dell …
Data Governance of Unstructured Data and Active …
Unstructured Data Management in the Cloud | Panzura
User behavior analytics External links:
IBM QRadar User Behavior Analytics – United States
User Behavior Analytics | FairWarning.com
User Behavior Analytics – LogRhythm.com
http://Ad · LogRhythm.com/UEBA
Visual analytics External links:
Visual Analytics Guide – Big Data with SAS Visual Analytics
http://Ad · www.sas.com/visual-analytics-guide
Visual Analytics Guide – Big Data with SAS Visual Analytics
http://Ad · www.sas.com/visual-analytics-guide
[PDF]Peer Reviewed Title: Visual Analytics
Web analytics External links:
View Web Analytics reports (SharePoint Server 2010)
Web Analytics – AFS Analytics
11 Best Web Analytics Tools | Inc.com