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:
Match Advanced Analytics issues and improve Advanced Analytics service perception.
– Do those selected for the Advanced Analytics team have a good general understanding of what Advanced Analytics is all about?
– Is there a Advanced Analytics Communication plan covering who needs to get what information when?
– What is the source of the strategies for Advanced Analytics strengthening and reform?
– What is Advanced Analytics?
Academic discipline Critical Criteria:
Mine Academic discipline leadership and finalize specific methods for Academic discipline acceptance.
– How do mission and objectives affect the Advanced Analytics processes of our organization?
– Why is it important to have senior management support for a Advanced Analytics project?
– What are the barriers to increased Advanced Analytics production?
Analytic applications Critical Criteria:
Face Analytic applications strategies and display thorough understanding of the Analytic applications process.
– How can you negotiate Advanced Analytics successfully with a stubborn boss, an irate client, or a deceitful coworker?
– Is Advanced Analytics dependent on the successful delivery of a current project?
– What business benefits will Advanced Analytics goals deliver if achieved?
– How do you handle Big Data in Analytic Applications?
– Analytic Applications: Build or Buy?
Architectural analytics Critical Criteria:
Have a session on Architectural analytics visions and oversee Architectural analytics requirements.
– How will we insure seamless interoperability of Advanced Analytics moving forward?
– Which individuals, teams or departments will be involved in Advanced Analytics?
Behavioral analytics Critical Criteria:
Participate in Behavioral analytics goals and reinforce and communicate particularly sensitive Behavioral analytics decisions.
– What are the disruptive Advanced Analytics technologies that enable our organization to radically change our business processes?
– What vendors make products that address the Advanced Analytics needs?
– Are we Assessing Advanced Analytics and Risk?
Big data Critical Criteria:
Closely inspect Big data visions and know what your objective is.
– Have we let algorithms and large centralized data centres not only control the remembering but also the meaning and interpretation of the data?
– What are the main obstacles that prevent you from having access to all the datasets that are relevant for your organization?
– Do you see regulatory restrictions on data/servers localisation requirements as obstacles for data-driven innovation?
– What is (or would be) the added value of collaborating with other entities regarding data sharing in your sector?
– 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 is the quantifiable ROI for this solution (cost / time savings / data error minimization / etc)?
– Does big data threaten the traditional data warehouse business intelligence model stack?
– Are our business activities mainly conducted in one country?
– Is the need persistent enough to justify development costs?
– How do we measure the efficiency of these algorithms?
– More efficient all-to-all operations (similarities)?
– How fast can we adapt to changes in the data stream?
– How to model context in a computational environment?
– What is tacit permission and approval, anyway?
– What metrics do we use to assess the results?
– Are all our algorithms covered by templates?
– How much data might be lost to pruning?
– So how are managers using big data?
– How much data so far?
Business analytics Critical Criteria:
Reorganize Business analytics issues and explore and align the progress in Business analytics.
– Marketing budgets are tighter, consumers are more skeptical, and social media has changed forever the way we talk about Advanced Analytics. How do we gain traction?
– 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 are the trends shaping the future of business analytics?
Business intelligence Critical Criteria:
Accommodate Business intelligence governance and correct better engagement with Business intelligence results.
– 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?
– As we develop increasing numbers of predictive models, then we have to figure out how do you pick the targets, how do you optimize the models?
– What is the difference between Key Performance Indicators KPI and Critical Success Factors CSF in a Business Strategic decision?
– Can you easily add users and features to quickly scale and customize to your organizations specific needs?
– Which OpenSource ETL tool is easier to use more agile Pentaho Kettle Jitterbit Talend Clover Jasper Rhino?
– Does your bi solution require weeks of training before new users can analyze data and publish dashboards?
– Are business intelligence solutions starting to include social media data and analytics features?
– Is business intelligence set to play a key role in the future of Human Resources?
– Does your client support bi-directional functionality with mapping?
– How is Business Intelligence and Information Management related?
– What else does the data tell us that we never thought to ask?
– What are the best use cases for Mobile Business Intelligence?
– Can users easily create these thresholds and alerts?
– What business intelligence systems are available?
– To create parallel systems or custom workflows?
– How is Business Intelligence related to CRM?
– Can your product map ad-hoc query results?
– Types of data sources supported?
– Why BI?
Cloud analytics Critical Criteria:
Experiment with Cloud analytics goals and diversify disclosure of information – dealing with confidential Cloud analytics information.
– Do we aggressively reward and promote the people who have the biggest impact on creating excellent Advanced Analytics services/products?
– Is there any existing Advanced Analytics governance structure?
– Which Advanced Analytics goals are the most important?
Complex event processing Critical Criteria:
Rank Complex event processing engagements and probe Complex event processing strategic alliances.
– 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?
– Why is Advanced Analytics important for you now?
Computer programming Critical Criteria:
Adapt Computer programming planning and work towards be a leading Computer programming expert.
– What management system can we use to leverage the Advanced Analytics experience, ideas, and concerns of the people closest to the work to be done?
– Are there recognized Advanced Analytics problems?
Continuous analytics Critical Criteria:
Model after Continuous analytics quality and probe the present value of growth of Continuous analytics.
– What tools do you use once you have decided on a Advanced Analytics strategy and more importantly how do you choose?
– Does Advanced Analytics systematically track and analyze outcomes for accountability and quality improvement?
– What are the long-term Advanced Analytics goals?
Cultural analytics Critical Criteria:
Reconstruct Cultural analytics planning and correct better engagement with Cultural analytics results.
– What tools and technologies are needed for a custom Advanced Analytics project?
– What are our Advanced Analytics Processes?
Customer analytics Critical Criteria:
Incorporate Customer analytics results and raise human resource and employment practices for Customer analytics.
– 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?
– Who is responsible for ensuring appropriate resources (time, people and money) are allocated to Advanced Analytics?
Data mining Critical Criteria:
Read up on Data mining planning and get out your magnifying glass.
– 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?
– Does Advanced Analytics create potential expectations in other areas that need to be recognized and considered?
– What is the difference between Data Analytics Data Analysis Data Mining and Data Science?
– What are all of our Advanced Analytics domains and what do they do?
– What programs do we have to teach data mining?
Data presentation architecture Critical Criteria:
Have a round table over Data presentation architecture management and triple focus on important concepts of Data presentation architecture relationship management.
– How do we ensure that implementations of Advanced Analytics products are done in a way that ensures safety?
Embedded analytics Critical Criteria:
Match Embedded analytics goals and simulate teachings and consultations on quality process improvement of Embedded analytics.
– Is Supporting Advanced Analytics documentation required?
– How is the value delivered by Advanced Analytics being measured?
Enterprise decision management Critical Criteria:
Reconstruct Enterprise decision management tasks and create a map for yourself.
– How does the organization define, manage, and improve its Advanced Analytics processes?
– Will Advanced Analytics deliverables need to be tested and, if so, by whom?
Fraud detection Critical Criteria:
Grade Fraud detection results and work towards be a leading Fraud detection expert.
– Can we add value to the current Advanced Analytics decision-making process (largely qualitative) by incorporating uncertainty modeling (more quantitative)?
– How do we keep improving Advanced Analytics?
Google Analytics Critical Criteria:
Design Google Analytics tasks and maintain Google Analytics for success.
– Will Advanced Analytics have an impact on current business continuity, disaster recovery processes and/or infrastructure?
Human resources Critical Criteria:
Guide Human resources leadership and display thorough understanding of the Human resources process.
– How do we engage divisions, operating units, operations, internal audit, risk management, compliance, finance, technology, and human resources in adopting the updated framework?
– Should pay levels and differences reflect the earnings of colleagues in the country of the facility, or earnings at the company headquarters?
– May an employee be retaliated against for making a complaint or reporting potential violations of these principles?
– Do we identify desired outcomes and key indicators (if not already existing) such as what metrics?
– What are the procedures for filing an internal complaint about the handling of personal data?
– Does the cloud service provider have necessary security controls on their human resources?
– Can you think of other ways to reduce the costs of managing employees?
– What decisions can you envision making with this type of information?
– Can we do Advanced Analytics without complex (expensive) analysis?
– How does the company provide notice of its information practices?
– Do you have Human Resources available to support your policies?
– How can we promote retention of high performing employees?
– Do you need to develop a Human Resources manual?
– Is our company developing its Human Resources?
– Will an algorithm shield us from liability?
– Why study Human Resources management (hrm)?
– In what areas do you feel we can improve?
– How do we engage the stakeholders?
Learning analytics Critical Criteria:
Talk about Learning analytics risks and learn.
– Does Advanced Analytics analysis show the relationships among important Advanced Analytics factors?
– Is Advanced Analytics Required?
Machine learning Critical Criteria:
Trace Machine learning management and inform on and uncover unspoken needs and breakthrough Machine learning results.
– What are the long-term implications of other disruptive technologies (e.g., machine learning, robotics, data analytics) converging with blockchain development?
– At what point will vulnerability assessments be performed once Advanced Analytics is put into production (e.g., ongoing Risk Management after implementation)?
Marketing mix modeling Critical Criteria:
Reorganize Marketing mix modeling engagements and attract Marketing mix modeling skills.
– What may be the consequences for the performance of an organization if all stakeholders are not consulted regarding Advanced Analytics?
– How much does Advanced Analytics help?
Mobile Location Analytics Critical Criteria:
Probe Mobile Location Analytics decisions and overcome Mobile Location Analytics skills and management ineffectiveness.
Neural networks Critical Criteria:
Map Neural networks visions and budget the knowledge transfer for any interested in Neural networks.
– Who will provide the final approval of Advanced Analytics deliverables?
News analytics Critical Criteria:
Probe News analytics visions and finalize specific methods for News analytics acceptance.
– How will you know that the Advanced Analytics project has been successful?
– Does the Advanced Analytics task fit the clients priorities?
– What are the business goals Advanced Analytics is aiming to achieve?
Online analytical processing Critical Criteria:
Unify Online analytical processing results and attract Online analytical processing skills.
– How do you determine the key elements that affect Advanced Analytics workforce satisfaction? how are these elements determined for different workforce groups and segments?
– In what ways are Advanced Analytics vendors and us interacting to ensure safe and effective use?
– Are accountability and ownership for Advanced Analytics clearly defined?
Online video analytics Critical Criteria:
Face Online video analytics tasks and plan concise Online video analytics education.
– Does Advanced Analytics appropriately measure and monitor risk?
Operational reporting Critical Criteria:
Grade Operational reporting results and clarify ways to gain access to competitive Operational reporting services.
– 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?
Operations research Critical Criteria:
Recall Operations research outcomes and acquire concise Operations research education.
– Think about the functions involved in your Advanced Analytics project. what processes flow from these functions?
– What other jobs or tasks affect the performance of the steps in the Advanced Analytics process?
Over-the-counter data Critical Criteria:
Confer re Over-the-counter data management and correct Over-the-counter data management by competencies.
– How can we incorporate support to ensure safe and effective use of Advanced Analytics into the services that we provide?
– Is Advanced Analytics Realistic, or are you setting yourself up for failure?
Portfolio analysis Critical Criteria:
Accumulate Portfolio analysis risks and observe effective Portfolio analysis.
– 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?
– What are our needs in relation to Advanced Analytics skills, labor, equipment, and markets?
Predictive analytics Critical Criteria:
Adapt Predictive analytics tactics and diversify disclosure of information – dealing with confidential Predictive analytics information.
– What are direct examples that show predictive analytics to be highly reliable?
– Think of your Advanced Analytics project. what are the main functions?
Predictive engineering analytics Critical Criteria:
Deliberate over Predictive engineering analytics risks and raise human resource and employment practices for Predictive engineering analytics.
– How do you incorporate cycle time, productivity, cost control, and other efficiency and effectiveness factors into these Advanced Analytics processes?
– What are the success criteria that will indicate that Advanced Analytics objectives have been met and the benefits delivered?
– How will you measure your Advanced Analytics effectiveness?
Predictive modeling Critical Criteria:
Gauge Predictive modeling leadership and find the essential reading for Predictive modeling researchers.
– Who will be responsible for making the decisions to include or exclude requested changes once Advanced Analytics is underway?
– Are you currently using predictive modeling to drive results?
Prescriptive analytics Critical Criteria:
Do a round table on Prescriptive analytics quality and get answers.
– How do senior leaders actions reflect a commitment to the organizations Advanced Analytics values?
– What is Effective Advanced Analytics?
– How to Secure Advanced Analytics?
Price discrimination Critical Criteria:
Coach on Price discrimination risks and track iterative Price discrimination results.
– What are the top 3 things at the forefront of our Advanced Analytics agendas for the next 3 years?
– Are assumptions made in Advanced Analytics stated explicitly?
– How do we go about Comparing Advanced Analytics approaches/solutions?
Risk analysis Critical Criteria:
Analyze Risk analysis leadership and display thorough understanding of the Risk analysis process.
– 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 are our best practices for minimizing Advanced Analytics project risk, while demonstrating incremental value and quick wins throughout the Advanced Analytics project lifecycle?
– 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?
– Who will be responsible for deciding whether Advanced Analytics goes ahead or not after the initial investigations?
– 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:
Paraphrase Security information and event management governance and test out new things.
– 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?
– Is maximizing Advanced Analytics protection the same as minimizing Advanced Analytics loss?
Semantic analytics Critical Criteria:
Discuss Semantic analytics leadership and secure Semantic analytics creativity.
– Do we monitor the Advanced Analytics decisions made and fine tune them as they evolve?
Smart grid Critical Criteria:
Facilitate Smart grid tactics and secure Smart grid creativity.
– 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?
– To what extent does management recognize Advanced Analytics as a tool to increase the results?
– How can the value of Advanced Analytics be defined?
Social analytics Critical Criteria:
Map Social analytics engagements and triple focus on important concepts of Social analytics relationship management.
– What potential environmental factors impact the Advanced Analytics effort?
Software analytics Critical Criteria:
Troubleshoot Software analytics governance and explore and align the progress in Software analytics.
– How would one define Advanced Analytics leadership?
– Is a Advanced Analytics Team Work effort in place?
Speech analytics Critical Criteria:
Merge Speech analytics tasks and define Speech analytics competency-based leadership.
Statistical discrimination Critical Criteria:
Guard Statistical discrimination governance and diversify by understanding risks and leveraging Statistical discrimination.
– What new services of functionality will be implemented next with Advanced Analytics ?
Stock-keeping unit Critical Criteria:
Derive from Stock-keeping unit planning and don’t overlook the obvious.
– Who is the main stakeholder, with ultimate responsibility for driving Advanced Analytics forward?
Structured data Critical Criteria:
Transcribe Structured data results and look for lots of ideas.
– What is the total cost related to deploying Advanced Analytics, including any consulting or professional services?
– 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:
Add value to Telecommunications data retention governance and improve Telecommunications data retention service perception.
– How can we improve Advanced Analytics?
Text analytics Critical Criteria:
Guide Text analytics tasks and shift your focus.
– Have text analytics mechanisms like entity extraction been considered?
Text mining Critical Criteria:
Consolidate Text mining visions and stake your claim.
– 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?
– What are the key elements of your Advanced Analytics performance improvement system, including your evaluation, organizational learning, and innovation processes?
Time series Critical Criteria:
Participate in Time series goals and attract Time series skills.
– For your Advanced Analytics project, identify and describe the business environment. is there more than one layer to the business environment?
– When a Advanced Analytics manager recognizes a problem, what options are available?
Unstructured data Critical Criteria:
Unify Unstructured data decisions and remodel and develop an effective Unstructured data strategy.
User behavior analytics Critical Criteria:
Guide User behavior analytics strategies and check on ways to get started with User behavior analytics.
– How do we measure improved Advanced Analytics service perception, and satisfaction?
Visual analytics Critical Criteria:
Check Visual analytics planning and drive action.
Web analytics Critical Criteria:
Devise Web analytics outcomes and suggest using storytelling to create more compelling Web analytics projects.
– 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 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:
Scrutinze Win–loss analytics adoptions and get going.
– How likely is the current Advanced Analytics plan to come in on schedule or on budget?
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 | 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:
Advanced Analytics – Big Data Analytics Defined by Gartner
Big Data and Advanced Analytics Solutions | Microsoft Azure
Neural Designer | Advanced analytics software
Academic discipline External links:
Behavioral analytics External links:
Security and IT Risk Intelligence with Behavioral Analytics
Niara | No Compromise Behavioral Analytics
FraudMAP Behavioral Analytics Solutions Brochure | Fiserv
Big data External links:
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:
[PDF]Position Title: Business Intelligence Analyst – ttra
Cloud analytics External links:
Cloud Analytics – Datamation
Financial Services – Cloud Analytics City Tour
Cloud Analytics Academy | Hosted by Snowflake
Complex event processing External links:
Eclipse IoT Day ECE 2017 – Complex Event Processing of …
Complex Event Processing (CEP) for Big Data Streaming
Computer programming External links:
Computer Programming Degrees and Certificates – …
Coding for Kids | Computer Programming | AgentCubes online
Computer Programming – Augusta Technical College
Continuous analytics External links:
continuous analytics Archives – Iguazio
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 …
Careers – Customer Analytics Company – Buxton
Customer Analytics | Maverick
Data mining External links:
[PDF]Data Mining Mining Text Data – tutorialspoint.com
Job Titles in Data Mining – kdnuggets.com
Embedded analytics External links:
Embedded Analytics | Vertica
What is embedded analytics ? – Definition from WhatIs.com
Enterprise decision management External links:
enterprise decision management Archives – Insights
Fraud detection External links:
Big Data Fraud Detection | DataVisor
Google Analytics External links:
Google Analytics for Firebase Use Policy | Firebase
Google Analytics Opt-out Browser Add-on Download Page
Services Google Analytics Partner Services and …
Human resources External links:
myDHR | Maryland Department of Human Resources
UAB – Human Resources – Careers
Learning analytics External links:
Society for Learning Analytics Research – YouTube
Journal of Learning Analytics
[PDF]Download and Read Learning Analytics Learning …
Machine learning External links:
Machine Learning, Cognitive Search & Text Analytics | Attivio
Microsoft Azure Machine Learning Studio
DataRobot – Automated Machine Learning for Predictive …
Marketing mix modeling External links:
Marketing Mix Modeling | Marketing Management Analytics
Marketing Mix Modeling – Decision Analyst
Mobile Location Analytics External links:
How ‘Mobile Location Analytics’ Controls Your Mind – …
Online analytical processing External links:
Working with Online Analytical Processing (OLAP)
SAS Online Analytical Processing Server
Operations research External links:
[PDF]Course Syllabus Course Title: Operations Research
Operations Research Dual-Title Degree Graduate …
Operations Research Analysis Manager Salaries – Salary.com
Over-the-counter data External links:
Bio — Over-the-Counter Data
Standards — Over-the-Counter Data
Portfolio analysis External links:
Portfolio analysis. (Book, 1979) [WorldCat.org]
4. TITLE AND SUBTITLE Defense Portfolio Analysis – …
Portfolio Analysis | Economy Watch
Predictive analytics External links:
Predictive Analytics for Healthcare | Forecast Health
Predictive Analytics Workers Compensation
Best Predictive Analytics Software in 2017 | G2 Crowd
Predictive engineering analytics External links:
Predictive Engineering Analytics: Siemens PLM Software
Predictive modeling External links:
Fast, Scalable, Accurate Predictive Modeling for Big Data
Prescriptive analytics External links:
How to Get Started With Prescriptive Analytics
Prescriptive Analytics – Gartner IT Glossary
Price discrimination External links:
ERIC – Marketing Theory Applied to Price Discrimination …
Risk analysis External links:
JIFSAN: Risk Analysis Training
What is Risk Analysis? – Definition from Techopedia
Smart grid External links:
Smart Grid – AbeBooks
Smart Grid Massachusetts | National Grid
Honeywell Smart Grid
Social analytics External links:
Enterprise Social Analytics Platform | About
Social Analytics – Votigo
Social Analytics – Marchex
Software analytics External links:
Physician Dispensing Software Analytics | MDScripts
Speech analytics External links:
Speech Analytics ROI Calculator Inquiry – CallMiner
Impact 360 Speech Analytics
Speech Analytics & Speech Recognition – TranscribeMe
Statistical discrimination External links:
Statistical Discrimination in Health Care
Statistical discrimination is an economic theory of racial or gender inequality based on stereotypes. According to this theory, inequality may exist and persist between demographic groups even when economic agents (consumers, workers, employers, etc.) are rational and non-prejudiced.
Structured data External links:
[PDF]Efficient Population of Structured Data Forms for …
n4e Ltd Structured Data cabling | Electrical Installations
Introduction to Structured Data | Search | Google Developers
Telecommunications data retention External links:
Telecommunications data retention | German WOTD
Telecommunications Data Retention and Human …
[PDF]Telecommunications Data Retention and Human …
Text analytics External links:
Text Analytics — Blogs, Pictures, and more on WordPress
Text mining External links:
Text Mining in R: A Tutorial – Springboard Blog
Text Mining, Semantics & Data Intelligence | SciBite
Text Mining | Metadata | Portable Document Format
Time series External links:
[PDF]Time Series Analysis and Forecasting – Cengage
Initial State – Analytics for Time Series Data
Azure Time Series Insights API | Microsoft Docs
User behavior analytics External links:
Varonis User Behavior Analytics | Varonis Systems
What is User Behavior Analytics? – YouTube
IBM QRadar User Behavior Analytics – Overview – United …
Visual analytics External links:
Web analytics External links:
20 Best Title:(web Analytics Manager) jobs | Simply Hired
11 Best Web Analytics Tools | Inc.com
AFS Analytics – Web analytics