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 202 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:
Track Advanced Analytics decisions and point out improvements in Advanced Analytics.
– Can Management personnel recognize the monetary benefit of Advanced Analytics?
– Do we have past Advanced Analytics Successes?
– What is Advanced Analytics?
Academic discipline Critical Criteria:
Conceptualize Academic discipline results and be persistent.
– How can you negotiate Advanced Analytics successfully with a stubborn boss, an irate client, or a deceitful coworker?
– Why is it important to have senior management support for a Advanced Analytics project?
– Do you monitor the effectiveness of your Advanced Analytics activities?
Analytic applications Critical Criteria:
Drive Analytic applications issues and interpret which customers can’t participate in Analytic applications because they lack skills.
– Who will be responsible for deciding whether Advanced Analytics goes ahead or not after the initial investigations?
– To what extent does management recognize Advanced Analytics as a tool to increase the results?
– How do you handle Big Data in Analytic Applications?
– Analytic Applications: Build or Buy?
– What are our Advanced Analytics Processes?
Architectural analytics Critical Criteria:
Guard Architectural analytics engagements and test out new things.
– Which customers cant participate in our Advanced Analytics domain because they lack skills, wealth, or convenient access to existing solutions?
– Does our organization need more Advanced Analytics education?
Behavioral analytics Critical Criteria:
Look at Behavioral analytics adoptions and define Behavioral analytics competency-based leadership.
– In a project to restructure Advanced Analytics outcomes, which stakeholders would you involve?
– Does Advanced Analytics appropriately measure and monitor risk?
– How much does Advanced Analytics help?
Big data Critical Criteria:
Read up on Big data issues and modify and define the unique characteristics of interactive Big data projects.
– While a move from Oracles MySQL may be necessary because of its inability to handle key big data use cases, why should that move involve a switch to Apache Cassandra and DataStax Enterprise?
– What are the particular research needs of your organization on big data analytics that you find essential to adequately handle your data assets?
– Erp versus big data are the two philosophies of information architecture consistent complementary or in conflict with each other?
– What are the main obstacles that prevent you from having access to all the datasets that are relevant for your organization?
– Is the software compatible with new database formats for raw, unstructured, and semi-structured big data?
– In which area(s) do data integration and BI, as part of Fusion Middleware, help our IT infrastructure?
– What are some strategies for capacity planning for big data processing and cloud computing?
– Future: Given the focus on Big Data where should the Chief Executive for these initiatives report?
– What can management do to improve value creation from data-driven innovation?
– What if the needle in the haystack happens to be a complex data structure?
– How can the benefits of Big Data collection and applications be measured?
– Does your organization have a strategy on big data or data analytics?
– Which Oracle Data Integration products are used in your solution?
– Does your organization buy datasets from other entities?
– From which country is your organization from?
– What is the cost of partitioning/balancing?
– Where Is This Big Data Coming From ?
– WHAT ARE THE NOMINATION CRITERIA?
– Does Big Data Really Need HPC?
– How to use in practice?
Business analytics Critical Criteria:
Participate in Business analytics strategies and find the ideas you already have.
– What are your key performance measures or indicators and in-process measures for the control and improvement of your Advanced Analytics processes?
– what is the most effective tool for Statistical Analysis Business Analytics and Business Intelligence?
– What is the difference between business intelligence business analytics and data mining?
– Is there a mechanism to leverage information for business analytics and optimization?
– Are we making progress? and are we making progress as Advanced Analytics leaders?
– 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?
– Are there recognized Advanced Analytics problems?
Business intelligence Critical Criteria:
Mix Business intelligence visions and pay attention to the small things.
– 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?
– Research reveals that more than half of business intelligence projects hit a low degree of acceptance or fail. What factors influence the implementation negative or positive?
– Choosing good key performance indicators (KPI Key Performance Indicators) did we start from the question How do you measure a companys success?
– Does your mobile solution allow you to interact with desktop-authored dashboards using touchscreen gestures like taps, flicks, and pinches?
– Does a BI business intelligence CoE center of excellence approach to support and enhancements benefit our organization and save cost?
– How should a complicated business setup their business intelligence and analysis to make decisions best?
– What is the biggest value proposition for new BI or analytics functionality at your company?
– what is the BI software application landscape going to look like in the next 5 years?
– Does your BI solution allow analytical insights to happen anywhere and everywhere?
– What are direct examples that show predictive analytics to be highly reliable?
– What are some common criticisms of Sharepoint as a knowledge sharing tool?
– Does your BI solution help you find the right views to examine your data?
– What are the pros and cons of outsourcing Business Intelligence?
– Number of data sources that can be simultaneously accessed?
– What is your anticipated learning curve for report users?
– What type and complexity of system administration roles?
– Will your product work from a mobile device?
– What level of training would you recommend?
– What is your annual maintenance?
Cloud analytics Critical Criteria:
Coach on Cloud analytics quality and get out your magnifying glass.
– Will new equipment/products be required to facilitate Advanced Analytics delivery for example is new software needed?
– Have the types of risks that may impact Advanced Analytics been identified and analyzed?
– How do we go about Securing Advanced Analytics?
Complex event processing Critical Criteria:
Analyze Complex event processing projects and look for lots of ideas.
– For your Advanced Analytics project, identify and describe the business environment. is there more than one layer to the business environment?
– What will be the consequences to the business (financial, reputation etc) if Advanced Analytics does not go ahead or fails to deliver the objectives?
– How can skill-level changes improve Advanced Analytics?
Computer programming Critical Criteria:
Generalize Computer programming engagements and attract Computer programming skills.
– What are the usability implications of Advanced Analytics actions?
– What is our Advanced Analytics Strategy?
Continuous analytics Critical Criteria:
Dissect Continuous analytics goals and triple focus on important concepts of Continuous analytics relationship management.
– Does Advanced Analytics systematically track and analyze outcomes for accountability and quality improvement?
– Are there any disadvantages to implementing Advanced Analytics? There might be some that are less obvious?
– What about Advanced Analytics Analysis of results?
Cultural analytics Critical Criteria:
Exchange ideas about Cultural analytics risks and inform on and uncover unspoken needs and breakthrough Cultural analytics results.
– Who will be responsible for making the decisions to include or exclude requested changes once Advanced Analytics is underway?
– Which individuals, teams or departments will be involved in Advanced Analytics?
– Is Advanced Analytics Required?
Customer analytics Critical Criteria:
Incorporate Customer analytics leadership and handle a jump-start course to Customer analytics.
– What threat is Advanced Analytics addressing?
– Are we Assessing Advanced Analytics and Risk?
Data mining Critical Criteria:
Adapt Data mining goals and do something to it.
– Do you see the need to clarify copyright aspects of the data-driven innovation (e.g. with respect to technologies such as text and data mining)?
– What types of transactional activities and data mining are being used and where do we see the greatest potential benefits?
– What is the difference between Data Analytics Data Analysis Data Mining and Data Science?
– Is business intelligence set to play a key role in the future of Human Resources?
– Have you identified your Advanced Analytics key performance indicators?
– How will you measure your Advanced Analytics effectiveness?
– What programs do we have to teach data mining?
– Is a Advanced Analytics Team Work effort in place?
Data presentation architecture Critical Criteria:
Unify Data presentation architecture planning and look at it backwards.
– What are our needs in relation to Advanced Analytics skills, labor, equipment, and markets?
– What are your most important goals for the strategic Advanced Analytics objectives?
Embedded analytics Critical Criteria:
Judge Embedded analytics adoptions and budget for Embedded analytics challenges.
– Will Advanced Analytics deliverables need to be tested and, if so, by whom?
Enterprise decision management Critical Criteria:
Disseminate Enterprise decision management projects and find the essential reading for Enterprise decision management researchers.
– What are internal and external Advanced Analytics relations?
Fraud detection Critical Criteria:
Reorganize Fraud detection visions and describe which business rules are needed as Fraud detection interface.
– How do you incorporate cycle time, productivity, cost control, and other efficiency and effectiveness factors into these Advanced Analytics processes?
– What are specific Advanced Analytics Rules to follow?
– How do we keep improving Advanced Analytics?
Google Analytics Critical Criteria:
Coach on Google Analytics management and secure Google Analytics creativity.
– Are accountability and ownership for Advanced Analytics clearly defined?
– Who will provide the final approval of Advanced Analytics deliverables?
Human resources Critical Criteria:
Design Human resources governance and finalize specific methods for Human resources acceptance.
– 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?
– Imagine you work in the Human Resources department of a company considering a policy to protect its data on employees mobile devices. in advising on this policy, what rights should be considered?
– 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?
– Under what circumstances might the company disclose personal data to third parties and what steps does the company take to safeguard that data?
– 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?
– Does the cloud service provider have necessary security controls on their human resources?
– To satisfy our customers and stakeholders, what financial objectives must we accomplish?
– What are the responsibilities of the company official responsible for compliance?
– Is the crisis management team comprised of members from Human Resources?
– What problems have you encountered with the department or staff member?
– What is the important thing that human resources management should do?
– What will be your Human Resources needs for the first year?
– How can we promote retention of high performing employees?
– Ease of contacting the Human Resources staff members?
– How is the Content updated of the hr website?
– Does the hr plan work for our stakeholders?
– Will an algorithm shield us from liability?
Learning analytics Critical Criteria:
Frame Learning analytics decisions and know what your objective is.
Machine learning Critical Criteria:
Frame Machine learning projects and budget the knowledge transfer for any interested in Machine learning.
– What are the long-term implications of other disruptive technologies (e.g., machine learning, robotics, data analytics) converging with blockchain development?
– Meeting the challenge: are missed Advanced Analytics opportunities costing us money?
– What are the long-term Advanced Analytics goals?
Marketing mix modeling Critical Criteria:
Study Marketing mix modeling engagements and change contexts.
– Why are Advanced Analytics skills important?
Mobile Location Analytics Critical Criteria:
Guide Mobile Location Analytics leadership and adjust implementation of Mobile Location Analytics.
– What may be the consequences for the performance of an organization if all stakeholders are not consulted regarding Advanced Analytics?
– Is there a Advanced Analytics Communication plan covering who needs to get what information when?
– Does the Advanced Analytics task fit the clients priorities?
Neural networks Critical Criteria:
Depict Neural networks visions and prioritize challenges of Neural networks.
– How can the value of Advanced Analytics be defined?
News analytics Critical Criteria:
Discourse News analytics visions and prioritize challenges of News analytics.
– How do we know that any Advanced Analytics analysis is complete and comprehensive?
– Are there Advanced Analytics Models?
Online analytical processing Critical Criteria:
Sort Online analytical processing decisions and visualize why should people listen to you regarding Online analytical processing.
– 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 current Advanced Analytics Paradigms?
Online video analytics Critical Criteria:
Have a round table over Online video analytics outcomes and reinforce and communicate particularly sensitive Online video analytics decisions.
– What is the total cost related to deploying Advanced Analytics, including any consulting or professional services?
– What other jobs or tasks affect the performance of the steps in the Advanced Analytics process?
Operational reporting Critical Criteria:
Understand Operational reporting projects and mentor Operational reporting customer orientation.
– 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?
Operations research Critical Criteria:
Coach on Operations research projects and finalize the present value of growth of Operations research.
– How important is Advanced Analytics to the user organizations mission?
Over-the-counter data Critical Criteria:
Have a session on Over-the-counter data goals and research ways can we become the Over-the-counter data company that would put us out of business.
– What new services of functionality will be implemented next with Advanced Analytics ?
– Have all basic functions of Advanced Analytics been defined?
Portfolio analysis Critical Criteria:
See the value of Portfolio analysis projects and acquire concise Portfolio analysis education.
– Risk factors: what are the characteristics of Advanced Analytics that make it risky?
Predictive analytics Critical Criteria:
Examine Predictive analytics failures and correct Predictive analytics management by competencies.
– How do senior leaders actions reflect a commitment to the organizations Advanced Analytics values?
– How can we improve Advanced Analytics?
– How to Secure Advanced Analytics?
Predictive engineering analytics Critical Criteria:
Focus on Predictive engineering analytics management and arbitrate Predictive engineering analytics techniques that enhance teamwork and productivity.
– How do we measure improved Advanced Analytics service perception, and satisfaction?
– How would one define Advanced Analytics leadership?
Predictive modeling Critical Criteria:
Think carefully about Predictive modeling failures and integrate design thinking in Predictive modeling innovation.
– Does Advanced 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?
– Do those selected for the Advanced Analytics team have a good general understanding of what Advanced Analytics is all about?
– Are you currently using predictive modeling to drive results?
Prescriptive analytics Critical Criteria:
Be clear about Prescriptive analytics results and acquire concise Prescriptive analytics education.
Price discrimination Critical Criteria:
Depict Price discrimination outcomes and spearhead techniques for implementing Price discrimination.
Risk analysis Critical Criteria:
Guide Risk analysis visions and revise understanding of Risk analysis architectures.
– 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:
Adapt Security information and event management engagements and look at it backwards.
– Think about the functions involved in your Advanced Analytics project. what processes flow from these functions?
– What are the top 3 things at the forefront of our Advanced Analytics agendas for the next 3 years?
Semantic analytics Critical Criteria:
Merge Semantic analytics decisions and get answers.
– Where do ideas that reach policy makers and planners as proposals for Advanced Analytics strengthening and reform actually originate?
– What are the disruptive Advanced Analytics technologies that enable our organization to radically change our business processes?
Smart grid Critical Criteria:
Steer Smart grid tactics and spearhead techniques for implementing Smart grid.
– 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?
– Does Advanced Analytics analysis show the relationships among important Advanced Analytics factors?
– What knowledge, skills and characteristics mark a good Advanced Analytics project manager?
Social analytics Critical Criteria:
Mix Social analytics tasks and get the big picture.
– In the case of a Advanced Analytics project, the criteria for the audit derive from implementation objectives. an audit of a Advanced Analytics project involves assessing whether the recommendations outlined for implementation have been met. in other words, can we track that any Advanced Analytics project is implemented as planned, and is it working?
– How is the value delivered by Advanced Analytics being measured?
Software analytics Critical Criteria:
Closely inspect Software analytics visions and inform on and uncover unspoken needs and breakthrough Software analytics results.
– How do we ensure that implementations of Advanced Analytics products are done in a way that ensures safety?
Speech analytics Critical Criteria:
Guard Speech analytics goals and create a map for yourself.
– Is the Advanced Analytics organization completing tasks effectively and efficiently?
– What are the short and long-term Advanced Analytics goals?
Statistical discrimination Critical Criteria:
Guard Statistical discrimination management and modify and define the unique characteristics of interactive Statistical discrimination projects.
– Do Advanced Analytics rules make a reasonable demand on a users capabilities?
Stock-keeping unit Critical Criteria:
Incorporate Stock-keeping unit governance and adopt an insight outlook.
– How do we make it meaningful in connecting Advanced Analytics with what users do day-to-day?
Structured data Critical Criteria:
Model after Structured data governance and look in other fields.
– What tools do you use once you have decided on a Advanced Analytics strategy and more importantly how do you choose?
– 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:
Air ideas re Telecommunications data retention planning and improve Telecommunications data retention service perception.
– Can we add value to the current Advanced Analytics decision-making process (largely qualitative) by incorporating uncertainty modeling (more quantitative)?
Text analytics Critical Criteria:
Communicate about Text analytics governance and optimize Text analytics leadership as a key to advancement.
– What are the key elements of your Advanced Analytics performance improvement system, including your evaluation, organizational learning, and innovation processes?
– Have text analytics mechanisms like entity extraction been considered?
Text mining Critical Criteria:
Distinguish Text mining adoptions and catalog Text mining activities.
– 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?
– Do the Advanced Analytics decisions we make today help people and the planet tomorrow?
Time series Critical Criteria:
Investigate Time series tasks and remodel and develop an effective Time series strategy.
– How can we incorporate support to ensure safe and effective use of Advanced Analytics into the services that we provide?
Unstructured data Critical Criteria:
Disseminate Unstructured data issues and differentiate in coordinating Unstructured data.
– 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?
– What is the source of the strategies for Advanced Analytics strengthening and reform?
User behavior analytics Critical Criteria:
Paraphrase User behavior analytics governance and modify and define the unique characteristics of interactive User behavior analytics projects.
– What prevents me from making the changes I know will make me a more effective Advanced Analytics leader?
Visual analytics Critical Criteria:
Extrapolate Visual analytics goals and report on the economics of relationships managing Visual analytics and constraints.
– Which Advanced Analytics goals are the most important?
– How to deal with Advanced Analytics Changes?
Web analytics Critical Criteria:
Audit Web analytics risks and check on ways to get started with Web analytics.
– Think about the kind of project structure that would be appropriate for your Advanced Analytics project. should it be formal and complex, or can it be less formal and relatively simple?
– 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?
– 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:
Have a round table over Win–loss analytics goals and oversee implementation of Win–loss analytics.
– What are all of our Advanced Analytics domains and what do they do?
– Can we do Advanced Analytics without complex (expensive) analysis?
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:
Kagr – Advanced analytics and Strategic marketing
Neural Designer | Advanced analytics software
Advanced Analytics – Big Data Analytics Defined by Gartner
Academic discipline External links:
criminal justice | academic discipline | Britannica.com
ERIC – Comparative Literature as Academic Discipline., …
Analytic applications External links:
Foxtrot Code AI Analytic Applications (Home)
Behavioral analytics External links:
Behavioral Analytics | Interana
User and Entity Behavioral Analytics Partners | Exabeam
Fortscale | Behavioral Analytics for Everyone
Big data External links:
Global Leaders in Big Data Analytics & Decision Science | RI
Qognify: Big Data Solutions for Physical Security & …
Pepperdata: DevOps for Big Data
Business analytics External links:
Power BI Business Analytics Solutions
Business intelligence External links:
Mortgage Business Intelligence Software :: Motivity Solutions
List of Business Intelligence Skills – The Balance
Cloud analytics External links:
Cloud Analytics – Solutions for Cloud Data Analytics | NetApp
TrackIt – Cloud Analytics and Monitoring Solution
Cloud Analytics Academy | Hosted by Snowflake
Complex event processing External links:
SAP HANA Tech: Complex Event Processing – SAP …
Complex Event Processing (CEP) for Big Data Streaming
Computer programming External links:
Computer programming | Computing | Khan Academy
Computer Programming, Robotics & Engineering – STEM For Kids
High School Coding – Computer Programming Courses
Continuous analytics External links:
continuous analytics Archives – Iguazio
Continuous Analytics: Why You Must Consider It – Zymr
[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:
BlueVenn – Customer Analytics and Customer Journey …
Our Team | Customer Analytics Experts | ClickFox
Data mining External links:
[PDF]Data Mining Report – Federation of American Scientists
Title Data Mining Jobs, Employment | Indeed.com
[PDF]Data Mining Mining Text Data – tutorialspoint.com
Embedded analytics External links:
What is embedded analytics ? – Definition from WhatIs.com
Power BI Embedded analytics | Microsoft Azure
Embedded Analytics – Gartner IT Glossary
Enterprise decision management External links:
enterprise decision management Archives – Insights
Fraud detection External links:
Title IV fraud detection | University Business Magazine
Google Analytics External links:
Google Analytics Solutions – Marketing Analytics & …
Welcome to the Texas Board of Nursing – Google Analytics
Human resources External links:
Home – OU Human Resources
Phila.gov | Human Resources | Jobs
Learning analytics External links:
Watershed | Learning Analytics for Organizations
Machine learning External links:
Machine Learning Mastery – Official Site
DataRobot – Automated Machine Learning for Predictive …
IT Operations Analytics, Machine Learning Tools – Perspica
Marketing mix modeling External links:
Marketing Mix Modeling | Marketing Management Analytics
Mobile Location Analytics External links:
Mobile Location Analytics – Android Apps on Google Play
[PDF]Mobile Location Analytics Code of Conduct
Mobile Location Analytics Privacy Notice | Verizon
Neural networks External links:
Neural Networks – ScienceDirect.com
Artificial Neural Networks – ScienceDirect
Online analytical processing External links:
SAS Online Analytical Processing Server
Working with Online Analytical Processing (OLAP)
Operations research External links:
[PDF]Course Syllabus Course Title: Operations Research
Operations research (Book, 1974) [WorldCat.org]
Match details for Operations Research Analysts
Over-the-counter data External links:
Portfolio analysis External links:
[PDF]Portfolio Analysis Brochure – factset.com
Portfolio Analysis | Economy Watch
What is PORTFOLIO ANALYSIS? definition of …
Predictive analytics External links:
Predictive Analytics Software, Social Listening | NewBrand
Stategic Location Management & Predictive Analytics | …
Customer Analytics & Predictive Analytics Tools for …
Predictive engineering analytics External links:
Predictive Engineering Analytics: Siemens PLM Software
Predictive modeling External links:
DataRobot – Automated Machine Learning for Predictive Modeling
Othot Predictive Modeling | Predictive Analytics Company
Prescriptive analytics External links:
Prescriptive Analytics – Gartner IT Glossary
Healthcare Prescriptive Analytics – Cedar Gate …
Price discrimination External links:
Price Discrimination – Investopedia
What Every Business Should Know About Price Discrimination
Price Discrimination Flashcards | Quizlet
Risk analysis External links:
What is Risk Analysis? – Definition from Techopedia
Risk analysis (eBook, 2015) [WorldCat.org]
The Fed – Risk Analysis – United States dollar
Security information and event management External links:
[PDF]Security Information and Event Management (SIEM) …
Smart grid External links:
[PDF]Smart Grid Asset Descriptions
Smart Grid Massachusetts | National Grid
Smart Grid – AbeBooks
Social analytics External links:
The Complete Social Analytics Solution | Simply Measured
Dark Social Analytics: Track Private Shares with GetSocial
Enterprise Social Analytics Platform | About
Speech analytics External links:
Customer Engagement & Speech Analytics | CallMiner
Speech Analytics – Marchex
Speech Analytics | NICE
Statistical discrimination External links:
“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
CLnet Solution Sdn Bhd | Structured Data Cabling Malaysia
SEC.gov | What Is Structured Data?
Text analytics External links:
Machine Learning, Cognitive Search & Text Analytics | Attivio
Text Analytics — Blogs, Pictures, and more on WordPress
[PDF]Syllabus Course Title: Text Analytics – …
Text mining External links:
Text mining — University of Illinois at Urbana-Champaign
Text Mining – AbeBooks
Text Mining / Text Analytics Specialist – bigtapp
Time series External links:
Initial State – Analytics for Time Series Data
Azure Time Series Insights API | Microsoft Docs
Time Series Analysis Flashcards | Quizlet
Unstructured data External links:
Unstructured Data DSP | Simpli.fi | What Is Unstructured Data?
User behavior analytics External links:
IBM QRadar User Behavior Analytics – Overview – United …
Market Guide for User Behavior Analytics – Gartner Inc.
Varonis User Behavior Analytics | Varonis Systems
Visual analytics External links:
Visual Analytics Developer – PeopleAdmin
Web analytics External links:
11 Best Web Analytics Tools | Inc.com
20 Best Title:(web Analytics Manager) jobs | Simply Hired
AFS Analytics – Web analytics