What is involved in Advanced Analytics
Find out what the related areas are that Advanced 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 Advanced Analytics thinking-frame.
How far is your company on its Advancing Business With Advanced Analytics journey?
Take this short survey to gauge your organization’s progress toward Advancing Business With Advanced 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 Advanced Analytics related domains to cover and 198 essential critical questions to check off in that domain.
The following domains are covered:
Advanced 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:
Advanced Analytics Critical Criteria:
Prioritize Advanced Analytics goals and grade techniques for implementing Advanced Analytics controls.
– Record-keeping requirements flow from the records needed as inputs, outputs, controls and for transformation of a Advanced Analytics process. ask yourself: are the records needed as inputs to the Advanced Analytics process available?
– Think about the people you identified for your Advanced 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?
– How important is Advanced Analytics to the user organizations mission?
– What is Advanced Analytics?
Academic discipline Critical Criteria:
Judge Academic discipline strategies and give examples utilizing a core of simple Academic discipline skills.
– What about Advanced Analytics Analysis of results?
– Are we Assessing Advanced Analytics and Risk?
– How to deal with Advanced Analytics Changes?
Analytic applications Critical Criteria:
Drive Analytic applications visions and transcribe Analytic applications as tomorrows backbone for success.
– Do those selected for the Advanced Analytics team have a good general understanding of what Advanced Analytics is all about?
– How can you negotiate Advanced Analytics successfully with a stubborn boss, an irate client, or a deceitful coworker?
– What prevents me from making the changes I know will make me a more effective Advanced Analytics leader?
– How do you handle Big Data in Analytic Applications?
– Analytic Applications: Build or Buy?
Architectural analytics Critical Criteria:
Examine Architectural analytics strategies and handle a jump-start course to Architectural analytics.
– Where do ideas that reach policy makers and planners as proposals for Advanced Analytics strengthening and reform actually originate?
– How can we incorporate support to ensure safe and effective use of Advanced Analytics into the services that we provide?
– In what ways are Advanced Analytics vendors and us interacting to ensure safe and effective use?
Behavioral analytics Critical Criteria:
Substantiate Behavioral analytics decisions and get going.
– What are the key elements of your Advanced Analytics performance improvement system, including your evaluation, organizational learning, and innovation processes?
– Which individuals, teams or departments will be involved in Advanced Analytics?
– Will Advanced Analytics deliverables need to be tested and, if so, by whom?
Big data Critical Criteria:
Reconstruct Big data projects and report on the economics of relationships managing Big data and constraints.
– 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)?
– Have we let algorithms and large centralized data centres not only control the remembering but also the meaning and interpretation of the data?
– Looking at hadoop big data in the rearview mirror what would you have done differently after implementing a Data Lake?
– Are we collecting data once and using it many times, or duplicating data collection efforts and submerging data in silos?
– Is the software compatible with new database formats for raw, unstructured, and semi-structured big data?
– 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 would be needed to support collaboration on data sharing across economic sectors?
– Is senior management in your organization involved in big data-related projects?
– Are there any best practices or standards for the use of Big Data solutions?
– What new Security and Privacy challenge arise from new Big Data solutions?
– Does your organization have the necessary skills to handle big data?
– Is data-driven decision-making part of the organizations culture?
– Which Oracle Data Integration products are used in your solution?
– With more data to analyze, can Big Data improve decision-making?
– What is/are the corollaries for non-algorithmic analytics?
– Find traffic bottlenecks ?
– Are we Using Data To Win?
– What is in Scope?
Business analytics Critical Criteria:
See the value of Business analytics projects and drive action.
– Does Advanced Analytics create potential expectations in other areas that need to be recognized and considered?
– what is the most effective tool for Statistical Analysis Business Analytics and Business Intelligence?
– What role does communication play in the success or failure of a Advanced Analytics project?
– 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 business benefits will Advanced Analytics goals deliver if achieved?
– What are the trends shaping the future of business analytics?
Business intelligence Critical Criteria:
Guard Business intelligence decisions and know what your objective is.
– 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?
– Does the software let users work with the existing data infrastructure already in place, freeing your IT team from creating more cubes, universes, and standalone marts?
– Does the software allow users to bring in data from outside the company on-the-flylike demographics and market research to augment corporate data?
– Does a BI business intelligence CoE center of excellence approach to support and enhancements benefit our organization and save cost?
– What tools are there for publishing sharing and visualizing data online?
– What are the best UI frameworks for Business Intelligence Applications?
– What are the key skills a Business Intelligence Analyst should have?
– Which other Oracle Business Intelligence products are used in your solution?
– What are the pros and cons of outsourcing Business Intelligence?
– What type and complexity of system administration roles?
– What is the purpose of data warehouses and data marts?
– What are alternatives to building a data warehouse?
– To create parallel systems or custom workflows?
– Is the product accessible from the internet?
– Will your product work from a mobile device?
– Can your product map ad-hoc query results?
– What are our tools for big data analytics?
– How can we maximize our BI investments?
– Is your BI software easy to understand?
Cloud analytics Critical Criteria:
Have a session on Cloud analytics governance and point out improvements in Cloud analytics.
– Which Advanced Analytics goals are the most important?
Complex event processing Critical Criteria:
Adapt Complex event processing goals and be persistent.
– What are the barriers to increased Advanced Analytics production?
– Does our organization need more Advanced Analytics education?
– Are there recognized Advanced Analytics problems?
Computer programming Critical Criteria:
Huddle over Computer programming decisions and probe using an integrated framework to make sure Computer programming is getting what it needs.
– Is there a Advanced Analytics Communication plan covering who needs to get what information when?
– Does Advanced Analytics analysis isolate the fundamental causes of problems?
Continuous analytics Critical Criteria:
Systematize Continuous analytics quality and look in other fields.
– What are the long-term Advanced Analytics goals?
Cultural analytics Critical Criteria:
Test Cultural analytics decisions and balance specific methods for improving Cultural analytics results.
– Are there any easy-to-implement alternatives to Advanced Analytics? Sometimes other solutions are available that do not require the cost implications of a full-blown project?
– How does the organization define, manage, and improve its Advanced Analytics processes?
Customer analytics Critical Criteria:
Coach on Customer analytics leadership and drive action.
– Meeting the challenge: are missed Advanced Analytics opportunities costing us money?
– What are the record-keeping requirements of Advanced Analytics activities?
– Is Supporting Advanced Analytics documentation required?
Data mining Critical Criteria:
Troubleshoot Data mining quality and change contexts.
– What types of transactional activities and data mining are being used and where do we see the greatest potential benefits?
– What is the difference between Data Analytics Data Analysis Data Mining and Data Science?
– Is business intelligence set to play a key role in the future of Human Resources?
– Think of your Advanced Analytics project. what are the main functions?
– What are the business goals Advanced Analytics is aiming to achieve?
– What programs do we have to teach data mining?
– How can we improve Advanced Analytics?
Data presentation architecture Critical Criteria:
Tête-à-tête about Data presentation architecture decisions and drive action.
– Will new equipment/products be required to facilitate Advanced Analytics delivery for example is new software needed?
– What is our Advanced Analytics Strategy?
Embedded analytics Critical Criteria:
Meet over Embedded analytics adoptions and diversify by understanding risks and leveraging Embedded analytics.
– Who are the people involved in developing and implementing Advanced Analytics?
– Who will provide the final approval of Advanced Analytics deliverables?
Enterprise decision management Critical Criteria:
Shape Enterprise decision management engagements and raise human resource and employment practices for Enterprise decision management.
– Think about the functions involved in your Advanced Analytics project. what processes flow from these functions?
– Who will be responsible for deciding whether Advanced Analytics goes ahead or not after the initial investigations?
Fraud detection Critical Criteria:
Demonstrate Fraud detection failures and be persistent.
– Do the Advanced Analytics decisions we make today help people and the planet tomorrow?
– What are the short and long-term Advanced Analytics goals?
Google Analytics Critical Criteria:
Value Google Analytics engagements and probe the present value of growth of Google Analytics.
– What are our best practices for minimizing Advanced Analytics project risk, while demonstrating incremental value and quick wins throughout the Advanced Analytics project lifecycle?
– How can the value of Advanced Analytics be defined?
Human resources Critical Criteria:
Gauge Human resources governance and tour deciding if Human resources progress is made.
– A dramatic step toward becoming a learning organization is to appoint a chief training officer (CTO) or a chief learning officer (CLO). Many organizations claim to value Human Resources, but how many have a Human Resources representative involved in discussions about research and development commercialization, new product development, the strategic vision of the company, or increasing shareholder value?
– 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)?
– 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?
– Where can an employee go for further information about the dispute resolution program?
– Is the crisis management team comprised of members from Human Resources?
– How is The staffs ability and response to handle questions or requests?
– How do financial reports support the various aspects of accountability?
– Can you think of other ways to reduce the costs of managing employees?
– What steps are taken to promote compliance with the hr principles?
– How should any risks to privacy and civil liberties be managed?
– How can we more efficiently on-board and off-board employees?
– What internal dispute resolution mechanisms are available?
– How is Staffs knowledge of procedures and regulations?
– Are we complying with existing security policies?
– Why study Human Resources management (hrm)?
– What additional approaches already exist?
– Why is transparency important?
Learning analytics Critical Criteria:
Detail Learning analytics quality and get answers.
– Who is responsible for ensuring appropriate resources (time, people and money) are allocated to Advanced Analytics?
– What are the Essentials of Internal Advanced Analytics Management?
Machine learning Critical Criteria:
Huddle over Machine learning leadership and find out what it really means.
– What are your results for key measures or indicators of the accomplishment of your Advanced Analytics strategy and action plans, including building and strengthening core competencies?
– What are the long-term implications of other disruptive technologies (e.g., machine learning, robotics, data analytics) converging with blockchain development?
– What are internal and external Advanced Analytics relations?
Marketing mix modeling Critical Criteria:
Pay attention to Marketing mix modeling visions and suggest using storytelling to create more compelling Marketing mix modeling projects.
– Do we cover the five essential competencies-Communication, Collaboration,Innovation, Adaptability, and Leadership that improve an organizations ability to leverage the new Advanced Analytics in a volatile global economy?
– Do we all define Advanced Analytics in the same way?
Mobile Location Analytics Critical Criteria:
Bootstrap Mobile Location Analytics projects and assess what counts with Mobile Location Analytics that we are not counting.
– What are your current levels and trends in key measures or indicators of Advanced 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?
– Do Advanced Analytics rules make a reasonable demand on a users capabilities?
– How do we maintain Advanced Analyticss Integrity?
Neural networks Critical Criteria:
Map Neural networks issues and gather Neural networks models .
– Does Advanced Analytics analysis show the relationships among important Advanced Analytics factors?
– To what extent does management recognize Advanced Analytics as a tool to increase the results?
News analytics Critical Criteria:
Give examples of News analytics projects and integrate design thinking in News analytics innovation.
– How likely is the current Advanced Analytics plan to come in on schedule or on budget?
Online analytical processing Critical Criteria:
Discuss Online analytical processing adoptions and develop and take control of the Online analytical processing initiative.
– Do we monitor the Advanced Analytics decisions made and fine tune them as they evolve?
Online video analytics Critical Criteria:
Merge Online video analytics goals and create Online video analytics explanations for all managers.
– Are there Advanced Analytics problems defined?
Operational reporting Critical Criteria:
Refer to Operational reporting strategies and budget for Operational reporting challenges.
– Who sets the Advanced Analytics standards?
Operations research Critical Criteria:
Think carefully about Operations research decisions and point out Operations research tensions in leadership.
– Among the Advanced Analytics product and service cost to be estimated, which is considered hardest to estimate?
– Are assumptions made in Advanced Analytics stated explicitly?
Over-the-counter data Critical Criteria:
Be clear about Over-the-counter data decisions and work towards be a leading Over-the-counter data expert.
Portfolio analysis Critical Criteria:
Survey Portfolio analysis results and overcome Portfolio analysis skills and management ineffectiveness.
– Which customers cant participate in our Advanced Analytics domain because they lack skills, wealth, or convenient access to existing solutions?
– What is the source of the strategies for Advanced Analytics strengthening and reform?
Predictive analytics Critical Criteria:
Collaborate on Predictive analytics projects and prioritize challenges of Predictive analytics.
– What are direct examples that show predictive analytics to be highly reliable?
– How is the value delivered by Advanced Analytics being measured?
Predictive engineering analytics Critical Criteria:
Face Predictive engineering analytics goals and secure Predictive engineering analytics creativity.
– How do we measure improved Advanced Analytics service perception, and satisfaction?
– Why is Advanced Analytics important for you now?
– What are our Advanced Analytics Processes?
Predictive modeling Critical Criteria:
Discuss Predictive modeling decisions and handle a jump-start course to Predictive modeling.
– Who is the main stakeholder, with ultimate responsibility for driving Advanced Analytics forward?
– Are you currently using predictive modeling to drive results?
Prescriptive analytics Critical Criteria:
Unify Prescriptive analytics engagements and create a map for yourself.
– What are all of our Advanced Analytics domains and what do they do?
Price discrimination Critical Criteria:
Map Price discrimination leadership and raise human resource and employment practices for Price discrimination.
– How do we go about Securing Advanced Analytics?
– How do we keep improving Advanced Analytics?
Risk analysis Critical Criteria:
Use past Risk analysis governance and spearhead techniques for implementing Risk analysis.
– 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?
– Who needs to know about Advanced Analytics ?
Security information and event management Critical Criteria:
Chart Security information and event management tasks and arbitrate Security information and event management techniques that enhance teamwork and productivity.
– Is the Advanced Analytics organization completing tasks effectively and efficiently?
Semantic analytics Critical Criteria:
Conceptualize Semantic analytics tactics and probe using an integrated framework to make sure Semantic analytics is getting what it needs.
– What is the total cost related to deploying Advanced Analytics, including any consulting or professional services?
Smart grid Critical Criteria:
Analyze Smart grid projects and develop and take control of the Smart grid initiative.
– Does your organization perform vulnerability assessment activities as part of the acquisition cycle for products in each of the following areas: Cybersecurity, SCADA, smart grid, internet connectivity, and website hosting?
Social analytics Critical Criteria:
Do a round table on Social analytics leadership and develop and take control of the Social analytics initiative.
– Consider your own Advanced Analytics project. what types of organizational problems do you think might be causing or affecting your problem, based on the work done so far?
Software analytics Critical Criteria:
Pilot Software analytics tasks and do something to it.
– Have you identified your Advanced Analytics key performance indicators?
– What are the Key enablers to make this Advanced Analytics move?
Speech analytics Critical Criteria:
Gauge Speech analytics quality and transcribe Speech analytics as tomorrows backbone for success.
– How do senior leaders actions reflect a commitment to the organizations Advanced Analytics values?
– What are your most important goals for the strategic Advanced Analytics objectives?
– What potential environmental factors impact the Advanced Analytics effort?
Statistical discrimination Critical Criteria:
Weigh in on Statistical discrimination projects and point out Statistical discrimination tensions in leadership.
– How do your measurements capture actionable Advanced Analytics information for use in exceeding your customers expectations and securing your customers engagement?
– What is the purpose of Advanced Analytics in relation to the mission?
– How can you measure Advanced Analytics in a systematic way?
Stock-keeping unit Critical Criteria:
Cut a stake in Stock-keeping unit strategies and report on the economics of relationships managing Stock-keeping unit and constraints.
– Why should we adopt a Advanced Analytics framework?
Structured data Critical Criteria:
Set goals for Structured data projects and budget for Structured data challenges.
– 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)?
– Is Advanced Analytics dependent on the successful delivery of a current project?
– Should you use a hierarchy or would a more structured database-model work best?
Telecommunications data retention Critical Criteria:
Weigh in on Telecommunications data retention leadership and ask what if.
– A compounding model resolution with available relevant data can often provide insight towards a solution methodology; which Advanced Analytics models, tools and techniques are necessary?
– In a project to restructure Advanced Analytics outcomes, which stakeholders would you involve?
Text analytics Critical Criteria:
Steer Text analytics tasks and report on the economics of relationships managing Text analytics and constraints.
– Have text analytics mechanisms like entity extraction been considered?
– What is Effective Advanced Analytics?
Text mining Critical Criteria:
Accommodate Text mining tasks and drive action.
– What are the disruptive Advanced Analytics technologies that enable our organization to radically change our business processes?
– How do we Improve Advanced Analytics service perception, and satisfaction?
Time series Critical Criteria:
Experiment with Time series failures and look at it backwards.
– What are current Advanced Analytics Paradigms?
Unstructured data Critical Criteria:
Talk about Unstructured data planning and perfect Unstructured data conflict management.
– How can skill-level changes improve Advanced Analytics?
– Why are Advanced Analytics skills important?
User behavior analytics Critical Criteria:
Debate over User behavior analytics adoptions and visualize why should people listen to you regarding User behavior analytics.
– What sources do you use to gather information for a Advanced Analytics study?
Visual analytics Critical Criteria:
Model after Visual analytics management and ask what if.
Web analytics Critical Criteria:
Concentrate on Web analytics visions and be persistent.
– What are your key performance measures or indicators and in-process measures for the control and improvement of your Advanced Analytics processes?
– Do we aggressively reward and promote the people who have the biggest impact on creating excellent Advanced Analytics services/products?
– What statistics should one be familiar with for business intelligence and web analytics?
– How is cloud computing related to web analytics?
Win–loss analytics Critical Criteria:
Tête-à-tête about Win–loss analytics planning and look for lots of ideas.
– How to Secure Advanced Analytics?
This quick readiness checklist is a selected resource to help you move forward. Learn more about how to achieve comprehensive insights with the Advancing Business With Advanced 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:
Advanced Analytics External links:
Neural Designer | Advanced analytics software
Advanced Analytics Report
http://Ad · www.sas.com/analytics-white-paper
Advanced Analytics – Big Data Analytics Defined by Gartner
Academic discipline External links:
criminal justice | academic discipline | Britannica.com
Academic Discipline Events – Northwest Nazarene …
Analytic applications External links:
Hype Cycle for Back-Office Analytic Applications, 2017
Architectural analytics External links:
Architectural Analytics – Home | Facebook
Behavioral analytics External links:
Security and IT Risk Intelligence with Behavioral Analytics
Fortscale | Behavioral Analytics for Everyone
Behavioral Analytics | Interana
Big data External links:
Pepperdata: DevOps for Big Data
Take 5 Media Group – Build an audience using big data
Business Intelligence and Big Data Analytics Software
Business analytics External links:
Business Analytics. Data Science. Data Management. – …
Business intelligence External links:
List of Business Intelligence Skills – The Balance
Cloud analytics External links:
Cloud Analytics Data Catalog
Cloud Analytics | Big Data Analytics | HPE Vertica
Computer programming External links:
Computer programming | Computing | Khan Academy
Computer Programming Degrees and Certificates – …
Coding for Kids | Computer Programming | AgentCubes online
Continuous analytics External links:
[PDF]Continuous Analytics: Stream Query Processing in …
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:
Our Team | Customer Analytics Experts | ClickFox
BlueVenn – Customer Analytics and Customer Journey …
Customer Analytics & Predictive Analytics for City Government
Data mining External links:
data aggregation in data mining ppt
Title Data Mining Jobs, Employment | Indeed.com
Job Titles in Data Mining – kdnuggets.com
Embedded analytics External links:
Embedded Analytics – Gartner IT Glossary
What is embedded analytics ? – Definition from WhatIs.com
Power BI Embedded analytics | Microsoft Azure
Enterprise decision management External links:
enterprise decision management Archives – Insights
Enterprise Decision Management (EDM) – Techopedia.com
Fraud detection External links:
Title IV fraud detection | University Business Magazine
Google Analytics External links:
Welcome to the Texas Board of Nursing – Google Analytics
Human resources External links:
UAB – Human Resources – Careers
Department of Human Resources Home – TN.Gov
Phila.gov | Human Resources | Jobs
Learning analytics External links:
Chapter 1 | Society for Learning Analytics Research (SoLAR)
Learning analytics – MoodleDocs
Journal of Learning Analytics
Machine learning External links:
Microsoft Azure Machine Learning Studio
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
Mobile Location Analytics – Android Apps on Google Play
Mobile location analytics | Federal Trade Commission
Neural networks External links:
Neural Networks – Home
Online analytical processing External links:
Oracle Online Analytical Processing (OLAP)
SAS Online Analytical Processing Server
Working with Online Analytical Processing (OLAP)
Operations research External links:
Operations research (Book, 2014) [WorldCat.org]
Operations Research Analysis Manager Salaries – Salary.com
Operations Research on JSTOR
Over-the-counter data External links:
Standards — Over-the-Counter Data
Portfolio analysis External links:
Essay on Portfolio Analysis – 1491 Words – StudyMode
Loan Portfolio Analysis | Visible Equity
Portfolio Analysis | Economy Watch
Predictive analytics External links:
Customer Analytics & Predictive Analytics Tools for Business
Store Lifecycle Management & Predictive Analytics | Tango
Predictive Analytics Software, Social Listening | NewBrand
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:
Healthcare Prescriptive Analytics – Cedar Gate …
How to Get Started With Prescriptive Analytics
Price discrimination External links:
What Every Business Should Know About Price Discrimination
Price Discrimination – Investopedia
Risk analysis External links:
What is risk analysis? – Definition from WhatIs.com
Risk analysis (eBook, 2015) [WorldCat.org]
Risk Analysis and Risk Management – Decision Making …
Smart grid External links:
[PDF]Smart Grid Asset Descriptions
SMART GRID SUMMITS
Honeywell Smart Grid
Social analytics External links:
Enterprise Social Analytics Platform | About
The Complete Social Analytics Solution | Simply Measured
Social Analytics – Marchex
Speech analytics External links:
Market Guide for Contact Center Speech Analytics
Speech Analytics – Marchex
Impact 360 Speech Analytics
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:
Introduction to Structured Data | Search | Google Developers
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:
Text Analytics | What is Text Analytics? – Clarabridge
Machine Learning, Cognitive Search & Text Analytics | Attivio
Text analytics software| NICE LTD | NICE
Text mining External links:
Text Mining in R: A Tutorial – Springboard Blog
Text Mining / Text Analytics Specialist – bigtapp
[PDF]Text Mining – UP – paginas.fe.up.pt
Time series External links:
Azure Time Series Insights Documentation – Tutorials, …
Initial State – Analytics for Time Series Data
Unstructured data External links:
Isilon Scale-Out NAS Storage-Unstructured Data | Dell …
Unstructured Data Management in the Cloud | Panzura
Data Governance of Unstructured Data and Active …
User behavior analytics External links:
User Behavior Analytics (UBA) Tools and Solutions | Rapid7
User Behavior Analytics | FairWarning.com
Visual analytics External links:
Visual Analytics Guide – Big Data with SAS Visual Analytics
http://Ad · www.sas.com/visual-analytics-guide
Visual Analytics Guide
http://Ad · www.sas.com/visual-analytics-guide
Web analytics External links:
11 Best Web Analytics Tools | Inc.com
20 Best Title:(web Analytics Manager) jobs | Simply Hired
Web Analytics in Real Time | Clicky