What is involved in Predictive Analytics
Find out what the related areas are that Predictive 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 Predictive Analytics thinking-frame.
How far is your company on its Predictive Analytics journey?
Take this short survey to gauge your organization’s progress toward Predictive 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 Predictive Analytics related domains to cover and 150 essential critical questions to check off in that domain.
The following domains are covered:
Predictive Analytics, Predictive policing, Normal distribution, Decision model, Logistic regression, Feed forward, Prognostics and health management, Probabilistic risk assessment, Prescriptive analytics, GNU Octave, Project risk management, SAP HANA, Logistic distribution, Autoregressive moving average model, Actuarial science, Computational sociology, Decision trees, Radial basis function, Learning analytics, Social network, Financial transaction, Amyotrophic lateral sclerosis, Customer attrition, Autoregressive conditional heteroskedasticity, Unstructured data, Social media analytics, Cost per order, Data mining, Multivariate adaptive regression splines, Sensor network, Odds ratio, Child protection, Multilayer perceptron, Credit card fraud, Supervised learning, KXEN Inc., Medical diagnostics, Information extraction, Gauss–Markov theorem, Optimal discriminant analysis, Likelihood-ratio test, Massive parallel processing, Decision making, Customer lifecycle management, Pervasive Software, Unsupervised learning, Disease surveillance, Clinical decision support system, Tibco Software, Random multinomial logit, Hopfield network, Face recognition, Conjugate gradient method, Predictive modelling, Predictive Analytics:
Predictive Analytics Critical Criteria:
Have a round table over Predictive Analytics strategies and devise Predictive Analytics key steps.
– What are direct examples that show predictive analytics to be highly reliable?
– Is Predictive Analytics Realistic, or are you setting yourself up for failure?
– Have you identified your Predictive Analytics key performance indicators?
– What is our formula for success in Predictive Analytics ?
Predictive policing Critical Criteria:
Reorganize Predictive policing governance and optimize Predictive policing leadership as a key to advancement.
– Who will be responsible for deciding whether Predictive Analytics goes ahead or not after the initial investigations?
– When a Predictive Analytics manager recognizes a problem, what options are available?
Normal distribution Critical Criteria:
Gauge Normal distribution visions and describe which business rules are needed as Normal distribution interface.
– How do we ensure that implementations of Predictive Analytics products are done in a way that ensures safety?
– Do you monitor the effectiveness of your Predictive Analytics activities?
– What are specific Predictive Analytics Rules to follow?
Decision model Critical Criteria:
Systematize Decision model outcomes and create a map for yourself.
– Does Predictive Analytics analysis isolate the fundamental causes of problems?
– Why should we adopt a Predictive Analytics framework?
Logistic regression Critical Criteria:
Study Logistic regression risks and get the big picture.
– How do your measurements capture actionable Predictive Analytics information for use in exceeding your customers expectations and securing your customers engagement?
– What will be the consequences to the business (financial, reputation etc) if Predictive Analytics does not go ahead or fails to deliver the objectives?
– Do those selected for the Predictive Analytics team have a good general understanding of what Predictive Analytics is all about?
Feed forward Critical Criteria:
Be clear about Feed forward governance and assess what counts with Feed forward that we are not counting.
– What tools and technologies are needed for a custom Predictive Analytics project?
– Who are the people involved in developing and implementing Predictive Analytics?
– Who will provide the final approval of Predictive Analytics deliverables?
Prognostics and health management Critical Criteria:
Conceptualize Prognostics and health management goals and finalize the present value of growth of Prognostics and health management.
– What other jobs or tasks affect the performance of the steps in the Predictive Analytics process?
– What are the barriers to increased Predictive Analytics production?
– Is there any existing Predictive Analytics governance structure?
Probabilistic risk assessment Critical Criteria:
Differentiate Probabilistic risk assessment outcomes and report on setting up Probabilistic risk assessment without losing ground.
– How do you incorporate cycle time, productivity, cost control, and other efficiency and effectiveness factors into these Predictive Analytics processes?
– How is the value delivered by Predictive Analytics being measured?
– How do we go about Securing Predictive Analytics?
Prescriptive analytics Critical Criteria:
Adapt Prescriptive analytics issues and be persistent.
– In what ways are Predictive Analytics vendors and us interacting to ensure safe and effective use?
– Who is the main stakeholder, with ultimate responsibility for driving Predictive Analytics forward?
– What about Predictive Analytics Analysis of results?
GNU Octave Critical Criteria:
Incorporate GNU Octave leadership and document what potential GNU Octave megatrends could make our business model obsolete.
– Consider your own Predictive Analytics project. what types of organizational problems do you think might be causing or affecting your problem, based on the work done so far?
– Risk factors: what are the characteristics of Predictive Analytics that make it risky?
– Does the Predictive Analytics task fit the clients priorities?
Project risk management Critical Criteria:
Scrutinze Project risk management adoptions and finalize specific methods for Project risk management acceptance.
– Can we do Predictive Analytics without complex (expensive) analysis?
– What can we expect from project Risk Management plans?
SAP HANA Critical Criteria:
Model after SAP HANA tactics and secure SAP HANA creativity.
– What tools do you use once you have decided on a Predictive Analytics strategy and more importantly how do you choose?
Logistic distribution Critical Criteria:
Ventilate your thoughts about Logistic distribution tasks and document what potential Logistic distribution megatrends could make our business model obsolete.
– What are our best practices for minimizing Predictive Analytics project risk, while demonstrating incremental value and quick wins throughout the Predictive Analytics project lifecycle?
– What knowledge, skills and characteristics mark a good Predictive Analytics project manager?
– How much does Predictive Analytics help?
Autoregressive moving average model Critical Criteria:
Chat re Autoregressive moving average model strategies and find the essential reading for Autoregressive moving average model researchers.
– Is maximizing Predictive Analytics protection the same as minimizing Predictive Analytics loss?
– How can skill-level changes improve Predictive Analytics?
Actuarial science Critical Criteria:
Apply Actuarial science outcomes and inform on and uncover unspoken needs and breakthrough Actuarial science results.
– Think about the kind of project structure that would be appropriate for your Predictive Analytics project. should it be formal and complex, or can it be less formal and relatively simple?
– Are we making progress? and are we making progress as Predictive Analytics leaders?
– How important is Predictive Analytics to the user organizations mission?
Computational sociology Critical Criteria:
Grasp Computational sociology issues and finalize specific methods for Computational sociology acceptance.
– What is the source of the strategies for Predictive Analytics strengthening and reform?
– Do we all define Predictive Analytics in the same way?
Decision trees Critical Criteria:
Do a round table on Decision trees visions and describe which business rules are needed as Decision trees interface.
– How do we Identify specific Predictive Analytics investment and emerging trends?
– How do we manage Predictive Analytics Knowledge Management (KM)?
– What will drive Predictive Analytics change?
Radial basis function Critical Criteria:
Pay attention to Radial basis function management and don’t overlook the obvious.
– Where do ideas that reach policy makers and planners as proposals for Predictive Analytics strengthening and reform actually originate?
– How likely is the current Predictive Analytics plan to come in on schedule or on budget?
Learning analytics Critical Criteria:
Give examples of Learning analytics tactics and acquire concise Learning analytics education.
– Who will be responsible for making the decisions to include or exclude requested changes once Predictive Analytics is underway?
– Are there any disadvantages to implementing Predictive Analytics? There might be some that are less obvious?
– What are our needs in relation to Predictive Analytics skills, labor, equipment, and markets?
Social network Critical Criteria:
Unify Social network tactics and test out new things.
– Which social networking or e learning service allows the possibility of creating multiple virtual classrooms?
– How might a persons various social network profiles be useful for learning education and or training?
– Can specialized social networks replace learning management systems?
– Are accountability and ownership for Predictive Analytics clearly defined?
– How to deal with Predictive Analytics Changes?
Financial transaction Critical Criteria:
Reorganize Financial transaction outcomes and question.
– What are the success criteria that will indicate that Predictive Analytics objectives have been met and the benefits delivered?
– What are the minimum data security requirements for a database containing personal financial transaction records?
Amyotrophic lateral sclerosis Critical Criteria:
Closely inspect Amyotrophic lateral sclerosis engagements and find the essential reading for Amyotrophic lateral sclerosis researchers.
– Which customers cant participate in our Predictive Analytics domain because they lack skills, wealth, or convenient access to existing solutions?
– How do we keep improving Predictive Analytics?
Customer attrition Critical Criteria:
Mine Customer attrition strategies and observe effective Customer attrition.
– A compounding model resolution with available relevant data can often provide insight towards a solution methodology; which Predictive Analytics models, tools and techniques are necessary?
– What is our Predictive Analytics Strategy?
Autoregressive conditional heteroskedasticity Critical Criteria:
Guide Autoregressive conditional heteroskedasticity quality and optimize Autoregressive conditional heteroskedasticity leadership as a key to advancement.
– How do we make it meaningful in connecting Predictive Analytics with what users do day-to-day?
– Is Supporting Predictive Analytics documentation required?
Unstructured data Critical Criteria:
Start Unstructured data engagements and test out new things.
– What are the key elements of your Predictive Analytics performance improvement system, including your evaluation, organizational learning, and innovation processes?
– What tools do you consider particularly important to handle unstructured data expressed in (a) natural language(s)?
– Does your organization have the right tools to handle unstructured data expressed in (a) natural language(s)?
– What are the business goals Predictive Analytics is aiming to achieve?
Social media analytics Critical Criteria:
Extrapolate Social media analytics quality and probe the present value of growth of Social media analytics.
– Do we aggressively reward and promote the people who have the biggest impact on creating excellent Predictive Analytics services/products?
– What are the record-keeping requirements of Predictive Analytics activities?
– What is Effective Predictive Analytics?
Cost per order Critical Criteria:
Define Cost per order outcomes and correct Cost per order management by competencies.
– Will Predictive Analytics deliverables need to be tested and, if so, by whom?
Data mining Critical Criteria:
Study Data mining management and shift your focus.
– 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?
– Among the Predictive Analytics product and service cost to be estimated, which is considered hardest to estimate?
– What is the difference between Data Analytics Data Analysis Data Mining and Data Science?
– What is the difference between business intelligence business analytics and data mining?
– What new services of functionality will be implemented next with Predictive Analytics ?
– Is business intelligence set to play a key role in the future of Human Resources?
– What programs do we have to teach data mining?
Multivariate adaptive regression splines Critical Criteria:
Have a session on Multivariate adaptive regression splines strategies and define Multivariate adaptive regression splines competency-based leadership.
– What are your results for key measures or indicators of the accomplishment of your Predictive Analytics strategy and action plans, including building and strengthening core competencies?
– Have the types of risks that may impact Predictive Analytics been identified and analyzed?
Sensor network Critical Criteria:
Track Sensor network leadership and probe using an integrated framework to make sure Sensor network is getting what it needs.
– How will the service discovery platforms that will be needed to deploy sensor networks impact the overall governance of the iot?
– Can Management personnel recognize the monetary benefit of Predictive Analytics?
– Does our wireless sensor network scale?
Odds ratio Critical Criteria:
Unify Odds ratio planning and explain and analyze the challenges of Odds ratio.
– Think about the people you identified for your Predictive 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?
Child protection Critical Criteria:
Adapt Child protection planning and frame using storytelling to create more compelling Child protection projects.
– What other organizational variables, such as reward systems or communication systems, affect the performance of this Predictive Analytics process?
– What are the short and long-term Predictive Analytics goals?
Multilayer perceptron Critical Criteria:
Model after Multilayer perceptron adoptions and oversee Multilayer perceptron requirements.
– How will you measure your Predictive Analytics effectiveness?
– What are our Predictive Analytics Processes?
Credit card fraud Critical Criteria:
Mix Credit card fraud decisions and know what your objective is.
– Do Predictive Analytics rules make a reasonable demand on a users capabilities?
– What are the long-term Predictive Analytics goals?
Supervised learning Critical Criteria:
Adapt Supervised learning goals and integrate design thinking in Supervised learning innovation.
– Is the scope of Predictive Analytics defined?
KXEN Inc. Critical Criteria:
Demonstrate KXEN Inc. quality and balance specific methods for improving KXEN Inc. results.
Medical diagnostics Critical Criteria:
Deliberate Medical diagnostics results and get the big picture.
– What are the Key enablers to make this Predictive Analytics move?
Information extraction Critical Criteria:
Depict Information extraction issues and secure Information extraction creativity.
– What management system can we use to leverage the Predictive Analytics experience, ideas, and concerns of the people closest to the work to be done?
– Is Predictive Analytics dependent on the successful delivery of a current project?
Gauss–Markov theorem Critical Criteria:
Generalize Gauss–Markov theorem issues and tour deciding if Gauss–Markov theorem progress is made.
– What are the disruptive Predictive Analytics technologies that enable our organization to radically change our business processes?
– What sources do you use to gather information for a Predictive Analytics study?
Optimal discriminant analysis Critical Criteria:
Boost Optimal discriminant analysis engagements and finalize the present value of growth of Optimal discriminant analysis.
– What business benefits will Predictive Analytics goals deliver if achieved?
Likelihood-ratio test Critical Criteria:
Sort Likelihood-ratio test failures and develop and take control of the Likelihood-ratio test initiative.
– How do we measure improved Predictive Analytics service perception, and satisfaction?
Massive parallel processing Critical Criteria:
Face Massive parallel processing engagements and diversify disclosure of information – dealing with confidential Massive parallel processing information.
– Is there a Predictive Analytics Communication plan covering who needs to get what information when?
– Does our organization need more Predictive Analytics education?
Decision making Critical Criteria:
Mine Decision making quality and gather practices for scaling Decision making.
– Is there a timely attempt to prepare people for technological and organizational changes, e.g., through personnel management, training, or participatory decision making?
– What prevents me from making the changes I know will make me a more effective Predictive Analytics leader?
– How do senior leaders actions reflect a commitment to the organizations Predictive Analytics values?
– What kind of processes and tools could serve both the vertical and horizontal analysis and decision making?
– What s the protocol for interaction, decision making, project management?
– How do we go about Comparing Predictive Analytics approaches/solutions?
– What role do analysts play in the decision making process?
– Who will be involved in the decision making process?
– Are the data needed for corporate decision making?
Customer lifecycle management Critical Criteria:
Refer to Customer lifecycle management risks and oversee Customer lifecycle management requirements.
– How do mission and objectives affect the Predictive Analytics processes of our organization?
– To what extent does management recognize Predictive Analytics as a tool to increase the results?
Pervasive Software Critical Criteria:
Administer Pervasive Software planning and look at it backwards.
– Marketing budgets are tighter, consumers are more skeptical, and social media has changed forever the way we talk about Predictive Analytics. How do we gain traction?
– Are assumptions made in Predictive Analytics stated explicitly?
– How do we Lead with Predictive Analytics in Mind?
Unsupervised learning Critical Criteria:
Interpolate Unsupervised learning quality and create Unsupervised learning explanations for all managers.
– What are your current levels and trends in key measures or indicators of Predictive 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 role does communication play in the success or failure of a Predictive Analytics project?
Disease surveillance Critical Criteria:
See the value of Disease surveillance visions and diversify disclosure of information – dealing with confidential Disease surveillance information.
– What are the Essentials of Internal Predictive Analytics Management?
Clinical decision support system Critical Criteria:
Trace Clinical decision support system planning and define what our big hairy audacious Clinical decision support system goal is.
– How will we insure seamless interoperability of Predictive Analytics moving forward?
– Are we Assessing Predictive Analytics and Risk?
Tibco Software Critical Criteria:
Sort Tibco Software results and reinforce and communicate particularly sensitive Tibco Software decisions.
– Are there any easy-to-implement alternatives to Predictive Analytics? Sometimes other solutions are available that do not require the cost implications of a full-blown project?
– Who will be responsible for documenting the Predictive Analytics requirements in detail?
Random multinomial logit Critical Criteria:
Conceptualize Random multinomial logit planning and visualize why should people listen to you regarding Random multinomial logit.
– How can we incorporate support to ensure safe and effective use of Predictive Analytics into the services that we provide?
– What is the total cost related to deploying Predictive Analytics, including any consulting or professional services?
– Who sets the Predictive Analytics standards?
Hopfield network Critical Criteria:
Check Hopfield network issues and get out your magnifying glass.
– what is the best design framework for Predictive Analytics organization now that, in a post industrial-age if the top-down, command and control model is no longer relevant?
Face recognition Critical Criteria:
Add value to Face recognition tactics and integrate design thinking in Face recognition innovation.
– What are all of our Predictive Analytics domains and what do they do?
Conjugate gradient method Critical Criteria:
Investigate Conjugate gradient method governance and ask questions.
Predictive modelling Critical Criteria:
Experiment with Predictive modelling goals and develop and take control of the Predictive modelling initiative.
– Does Predictive Analytics appropriately measure and monitor risk?
– How can we improve Predictive Analytics?
Predictive Analytics Critical Criteria:
Collaborate on Predictive Analytics leadership and develop and take control of the Predictive Analytics initiative.
This quick readiness checklist is a selected resource to help you move forward. Learn more about how to achieve comprehensive insights with the Predictive 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:
Predictive Analytics External links:
Predictive Analytics Software, Social Listening | NewBrand
Strategic Location Management & Predictive Analytics | Tango
Predictive policing External links:
Predictive Policing Technology | PredPol
Predict Crime | Predictive Policing Software | PredPol
What’s Predictive Policing? | Privacy SOS
Normal distribution External links:
Standard Normal Distribution – Statistics and Probability
An Introduction to Excel’s Normal Distribution Functions
Decision model External links:
What is DECISION MODEL? definition of DECISION …
What is the Decision Model? – IT Today Home Page
The Decision Model | The Decision Model
Logistic regression External links:
Logistic Regression: Why sigmoid function? – Quora
Feed forward External links:
Steam Fired Instantaneous Feed Forward Water Heaters
The Feed Forward Controller – Control Guru
Prognostics and health management External links:
[PDF]Prognostics and Health Management (PHM) / Condition …
Prognostics and Health Management of Engineering …
Probabilistic risk assessment External links:
Fundamentals of Probabilistic Risk Assessment (PRA) ~ EUCI
Prescriptive analytics External links:
Healthcare Prescriptive Analytics – Cedar Gate Technologies
GNU Octave External links:
GNU Octave – Official Site
GNU Octave: Plot Annotations
Gnu Octave Manual – AbeBooks
Project risk management External links:
Project Risk Management Process
Project Risk Management – University of Massachusetts …
SAP HANA External links:
SAP HANA Academy – YouTube
SAP HANA on Azure Virtual Machines | Microsoft Azure
Autoregressive moving average model External links:
Autoregressive Moving Average Model – MATLAB & Simulink
Actuarial science External links:
35 Best Actuarial Science Degrees for 2018 – College Choice
2017 Best Colleges Offering Actuarial Science Degrees
Jan Dhaene – professor of actuarial science
Computational sociology External links:
Computational Sociology Research Paper Starter – eNotes.…
From Factors to Factors: Computational Sociology and …
Martin Lukac – Computational Sociology and Data Science
Decision trees External links:
[PDF]Induction of Decision Trees
Create Interactive Decision Trees with Zingtree
Decision Tree – Learn Everything About Decision Trees
Radial basis function External links:
[PDF]The Radial Basis Function Kernel – pages.cs.wisc.edu
What is a radial basis function? – Quora
Ali Ghodsi, Lect 8: Radial basis function network – YouTube
Learning analytics External links:
Learning Analytics Explained. (eBook, 2017) [WorldCat.org]
Financial transaction External links:
SJSU Financial Transaction Services
What is FINANCIAL TRANSACTION – Black’s Law Dictionary
Financial Transaction Control Procedures Guide
Amyotrophic lateral sclerosis External links:
Amyotrophic Lateral Sclerosis | NEJM
Customer attrition External links:
Listening to Feedback Is How You Fight Customer Attrition
Autoregressive conditional heteroskedasticity External links:
[PDF]Autoregressive Conditional Heteroskedasticity (ARCH)
Unstructured data External links:
Scale-Out NAS for Unstructured Data | Dell EMC US
Social media analytics External links:
Social Media Analytics | UK | Meronimi IntelligenceHub
Social Media Analytics Online Training Course – Mediabistro
Cost per order External links:
[PDF]Table 5 Average Cost per Order January 1 Through …
[PDF]Table 5 Average Cost per Order January 1 Through …
Retail KPIs: Processing Cost per Order – Brightpearl
Data mining External links:
UT Data Mining
Data Mining Extensions (DMX) Reference | Microsoft Docs
What is Data Mining in Healthcare?
Multivariate adaptive regression splines External links:
Attendees | Multivariate Adaptive Regression Splines …
[PDF]MULTIVARIATE ADAPTIVE REGRESSION SPLINES*
Sensor network External links:
The Sensor Network | MySensors – Create your own …
Wireless Sensor Network Monitoring and Notification Software
What Is a Wireless Sensor Network? – National Instruments
Odds ratio External links:
Odds Ratio to Risk Ratio Conversion – ClinCalc.com
Explaining Odds Ratios
[PDF]Odds Ratios in a Tabular Presentation
Child protection External links:
State of North Carolina: Child Protection Services
Child protection from violence, exploitation and abuse
Credit card fraud External links:
Credit Card Fraud Detection | Kaggle
Man suspected of credit card fraud in 2 counties – woodtv.com
Supervised learning External links:
Supervised Learning with scikit-learn – DataCamp
1. Supervised learning — scikit-learn 0.19.1 documentation
KXEN Inc. External links:
KXEN Inc. – YouTube
Developer(s): KXEN Inc.
http://Stable release: 5.1 / May 2009
Medical diagnostics External links:
WellHealth Medical Diagnostics and Primary Care in Las Vegas
Medical Diagnostics | Medical Laboratory Sciences
Medical Diagnostics Tests Reinvented | NOWDiagnostics
Information extraction External links:
Information Extraction — NYU Scholars
[PDF]Mining Knowledge from Text Using Information Extraction
Information extraction (eBook, 2007) [WorldCat.org]
Optimal discriminant analysis External links:
[PDF]PARETO-OPTIMAL DISCRIMINANT ANALYSIS Felix …
[PDF]Sparse Kernels for Bayes Optimal Discriminant Analysis
Decision making External links:
[PDF]CHOICES AND DECISION MAKING
IS-241.B: Decision Making and Problem Solving – FEMA
Essays on decision making – Rutgers University
Customer lifecycle management External links:
Complete Customer Lifecycle Management – STARTEK
Pervasive Software External links:
PERVASIVE SOFTWARE INC (PVSW) IPO – NASDAQ.com
Pervasive Software, Inc. Company Financial Information
PERVASIVE SOFTWARE INC (PVSW) 10-K and 10-Q SEC …
Disease surveillance External links:
North Dakota Electronic Disease Surveillance System
NC DPH: Communicable Disease Surveillance & Reporting
Connecticut Electronic Disease Surveillance System
Clinical decision support system External links:
Clinical decision support system – Ganfyd
Clinical Decision Support System – nurses
Clinical decision support systems | BC Medical Journal
Tibco Software External links:
TIBCO Software (@TIBCO) | Twitter
Contact Us | TIBCO Software
TIBCO Software – Questionmark Blog
Hopfield network External links:
Hopfield network emulator – OpenCog
Hopfield network – Scholarpedia
[PDF]Hopfield Network (Discrete) – A recurrent …
Face recognition External links:
FaceFirst Face Recognition Software – Official Site
Dec 26, 2016 · Face Recognition application can start experimenting with face recognitio
Conjugate gradient method External links:
The Conjugate Gradient Method – math.oregonstate.edu
Conjugate gradient method – Harvey Mudd College
[PDF]An Introduction to the Conjugate Gradient Method …
Predictive Analytics External links:
Strategic Location Management & Predictive Analytics | Tango
Predictive Analytics Software, Social Listening | NewBrand