What is involved in Big Data

Find out what the related areas are that Big Data 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 Big Data thinking-frame.

How far is your company on its Big Data Information Management journey?

Take this short survey to gauge your organization’s progress toward Big Data Information Management 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 Big Data related domains to cover and 227 essential critical questions to check off in that domain.

The following domains are covered:

Big Data, Ulf-Dietrich Reips, The Globe and Mail, DBC 1012, International Data Corporation, Dirty data, Data acquisition, Data visualization, Data quality, Horizon 2020, The Independent, Anand Rajaraman, Google Translate, Descriptive statistics, Extract, transform, load, The Data Incubator, Digital camera, Predictive analytics, Mobile device, Data set, Computer data storage, Data defined storage, Human Genome Project, Radio-frequency identification, Data fusion, Indian general election, 2014, with mixed results, Data transmission, Information and communication technologies for development, Distributed file system, Apache Hadoop, Presidency of Barack Obama, Seventh Framework Program, National Diet Library, Cyber-physical system, Nonlinear system identification, Data philanthropy, MIT Computer Science and Artificial Intelligence Laboratory, Agent-based model, Business Intelligence, User behavior analytics, Government of India, Consumer privacy, Bloomberg Businessweek, Machine learning, Cluster analysis, Oracle NoSQL Database, Natural disaster, Data lineage, Data sharing, Data journalism, Topological Data Analysis, Systems management, Viktor Mayer-Schönberger, Relational database management system, Surveillance capitalism, Oracle Corporation, Google Flu Trends, Massive parallel processing, Economic productivity, EMC Corporation, Complex Systems:

Big Data Critical Criteria:

Read up on Big Data decisions and get out your magnifying glass.

– Looking at hadoop big data in the rearview mirror what would you have done differently after implementing a Data Lake?

– Are we collecting data once and using it many times, or duplicating data collection efforts and submerging data in silos?

– To what extent does data-driven innovation add to the competitive advantage (CA) of your company?

– Do we understand the mechanisms and patterns that underlie transportation in our jurisdiction?

– Technology Drivers – What were the primary technical challenges your organization faced?

– Quality vs. Quantity: What data are required to satisfy the given value proposition?

– How are the new Big Data developments captured in new Reference Architectures?

– Which other Oracle Business Intelligence products are used in your solution?

– How will systems and methods evolve to remove Big Data solution weaknesses?

– What are the new developments that are included in Big Data solutions?

– Does your organization have a strategy on big data or data analytics?

– What are the new applications that are enabled by Big Data solutions?

– Big Data: what is different from large databases?

– Are our Big Data investment programs results driven?

– Overall cost (matrix, weighting, SVD, sims)?

– So how are managers using big data?

– How do I get to there from here?

– What about Volunteered data?

– What s limiting the task?

– Who is collecting what?

Ulf-Dietrich Reips Critical Criteria:

Understand Ulf-Dietrich Reips adoptions and explain and analyze the challenges of Ulf-Dietrich Reips.

– How do mission and objectives affect the Big Data processes of our organization?

– How do we maintain Big Datas Integrity?

– How to Secure Big Data?

The Globe and Mail Critical Criteria:

Huddle over The Globe and Mail results and secure The Globe and Mail creativity.

– What prevents me from making the changes I know will make me a more effective Big Data leader?

– What is Effective Big Data?

DBC 1012 Critical Criteria:

Consider DBC 1012 decisions and forecast involvement of future DBC 1012 projects in development.

– Are there any easy-to-implement alternatives to Big Data? Sometimes other solutions are available that do not require the cost implications of a full-blown project?

– Think about the functions involved in your Big Data project. what processes flow from these functions?

– What threat is Big Data addressing?

International Data Corporation Critical Criteria:

Conceptualize International Data Corporation planning and intervene in International Data Corporation processes and leadership.

– Do those selected for the Big Data team have a good general understanding of what Big Data is all about?

– Among the Big Data product and service cost to be estimated, which is considered hardest to estimate?

– How do we know that any Big Data analysis is complete and comprehensive?

Dirty data Critical Criteria:

Powwow over Dirty data goals and interpret which customers can’t participate in Dirty data because they lack skills.

– Consider your own Big Data project. what types of organizational problems do you think might be causing or affecting your problem, based on the work done so far?

– Are there Big Data Models?

Data acquisition Critical Criteria:

Steer Data acquisition results and do something to it.

– Think about the kind of project structure that would be appropriate for your Big Data project. should it be formal and complex, or can it be less formal and relatively simple?

– Is there a Big Data Communication plan covering who needs to get what information when?

– Do Big Data rules make a reasonable demand on a users capabilities?

Data visualization Critical Criteria:

Match Data visualization failures and display thorough understanding of the Data visualization process.

– Which customers cant participate in our Big Data domain because they lack skills, wealth, or convenient access to existing solutions?

– What are the best places schools to study data visualization information design or information architecture?

– How do we make it meaningful in connecting Big Data with what users do day-to-day?

Data quality Critical Criteria:

Tête-à-tête about Data quality planning and catalog what business benefits will Data quality goals deliver if achieved.

– Does the design of the program/projects overall data collection and reporting system ensure that, if implemented as planned, it will collect and report quality data?

– Which audit findings of the Data Management and reporting system warrant recommendation notes and changes to the design in order to improve Data Quality?

– Has the program/project clearly documented (in writing) what is reported to who, and how and when reporting is required?

– Can a decision (or estimate) be made with the desired level of certainty, given the quality of the data?

– Can you be reasonably sure that the same set of data will be available to you next year?

– Is data recorded with sufficient precision/detail to measure relevant indicators?

– Have the majority of key data-management staff received the required training?

– Has management performed regular Data Quality assessments?

– What features do you need most in Data Quality software?

– What is the proportion of missing values for each field?

– Do you clearly document your data collection methods?

– Timeliness: is data available when needed?

– How do you determine the quality of data?

– Data Quality: how good is your data?

– Are the attributes independent?

– How good does data have to be?

– Is the review date identified?

– Can Data Quality be improved?

– Is the system flexible?

– Are records complete?

Horizon 2020 Critical Criteria:

Illustrate Horizon 2020 risks and mentor Horizon 2020 customer orientation.

– What will be the consequences to the business (financial, reputation etc) if Big Data does not go ahead or fails to deliver the objectives?

– Will Big Data have an impact on current business continuity, disaster recovery processes and/or infrastructure?

– Who will be responsible for documenting the Big Data requirements in detail?

The Independent Critical Criteria:

Align The Independent governance and find answers.

– What are our best practices for minimizing Big Data project risk, while demonstrating incremental value and quick wins throughout the Big Data project lifecycle?

– How can you negotiate Big Data successfully with a stubborn boss, an irate client, or a deceitful coworker?

Anand Rajaraman Critical Criteria:

Tête-à-tête about Anand Rajaraman quality and prioritize challenges of Anand Rajaraman.

– How do your measurements capture actionable Big Data information for use in exceeding your customers expectations and securing your customers engagement?

Google Translate Critical Criteria:

Revitalize Google Translate goals and shift your focus.

– How likely is the current Big Data plan to come in on schedule or on budget?

– Have all basic functions of Big Data been defined?

– How can skill-level changes improve Big Data?

Descriptive statistics Critical Criteria:

Read up on Descriptive statistics engagements and differentiate in coordinating Descriptive statistics.

– Why is it important to have senior management support for a Big Data project?

– How important is Big Data to the user organizations mission?

– How do we go about Comparing Big Data approaches/solutions?

Extract, transform, load Critical Criteria:

Value Extract, transform, load results and look for lots of ideas.

– Who will be responsible for making the decisions to include or exclude requested changes once Big Data is underway?

– What are the business goals Big Data is aiming to achieve?

The Data Incubator Critical Criteria:

Gauge The Data Incubator planning and modify and define the unique characteristics of interactive The Data Incubator projects.

– What is the purpose of Big Data in relation to the mission?

– How will you measure your Big Data effectiveness?

Digital camera Critical Criteria:

Guard Digital camera management and know what your objective is.

– Is the Big Data organization completing tasks effectively and efficiently?

– Does our organization need more Big Data education?

Predictive analytics Critical Criteria:

Debate over Predictive analytics adoptions and use obstacles to break out of ruts.

– What are direct examples that show predictive analytics to be highly reliable?

– Is there any existing Big Data governance structure?

– Are there recognized Big Data problems?

Mobile device Critical Criteria:

Co-operate on Mobile device projects and define what our big hairy audacious Mobile device goal is.

– 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?

– Can we add value to the current Big Data decision-making process (largely qualitative) by incorporating uncertainty modeling (more quantitative)?

– If mobile technologies are supported, how is the software optimized for use on smartphone, tables, and other mobile devices?

– Does the tool we use provide the ability for mobile devices to access critical portions of the management interface?

– Can your bi solution quickly locate dashboard on your mobile device?

– Will your product work from a mobile device?

Data set Critical Criteria:

Systematize Data set goals and achieve a single Data set view and bringing data together.

– How do you incorporate cycle time, productivity, cost control, and other efficiency and effectiveness factors into these Big Data processes?

– For hosted solutions, are we permitted to download the entire data set in order to maintain local backups?

– How was it created; what algorithms, algorithm versions, ancillary and calibration data sets were used?

– How do we ensure that implementations of Big Data products are done in a way that ensures safety?

– How do senior leaders actions reflect a commitment to the organizations Big Data values?

– Is data that is transcribed or copied checked for errors against the original data set?

– What needs to be in the plan related to the data capture for the various data sets?

– Is someone responsible for migrating data sets that are in old/outdated formats?

– You get a data set. what do you do with it?

Computer data storage Critical Criteria:

Win new insights about Computer data storage management and inform on and uncover unspoken needs and breakthrough Computer data storage results.

– What are your current levels and trends in key measures or indicators of Big Data 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 management system can we use to leverage the Big Data experience, ideas, and concerns of the people closest to the work to be done?

Data defined storage Critical Criteria:

Scan Data defined storage leadership and get the big picture.

– Do we aggressively reward and promote the people who have the biggest impact on creating excellent Big Data services/products?

– In what ways are Big Data vendors and us interacting to ensure safe and effective use?

– What are current Big Data Paradigms?

Human Genome Project Critical Criteria:

Collaborate on Human Genome Project quality and point out improvements in Human Genome Project.

– What sources do you use to gather information for a Big Data study?

– Why is Big Data important for you now?

Radio-frequency identification Critical Criteria:

Co-operate on Radio-frequency identification leadership and oversee implementation of Radio-frequency identification.

– Think about the people you identified for your Big Data 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?

– Are assumptions made in Big Data stated explicitly?

Data fusion Critical Criteria:

Weigh in on Data fusion governance and get out your magnifying glass.

– What new requirements emerge in terms of information processing/management to make physical and virtual world data fusion possible?

– Which individuals, teams or departments will be involved in Big Data?

– What business benefits will Big Data goals deliver if achieved?

– What are the short and long-term Big Data goals?

Indian general election, 2014, with mixed results Critical Criteria:

Gauge Indian general election, 2014, with mixed results tasks and oversee Indian general election, 2014, with mixed results requirements.

– What are the top 3 things at the forefront of our Big Data agendas for the next 3 years?

– Who needs to know about Big Data ?

Data transmission Critical Criteria:

Deduce Data transmission issues and mentor Data transmission customer orientation.

– How do you determine the key elements that affect Big Data workforce satisfaction? how are these elements determined for different workforce groups and segments?

– Are there any disadvantages to implementing Big Data? There might be some that are less obvious?

– Does the Big Data task fit the clients priorities?

Information and communication technologies for development Critical Criteria:

Familiarize yourself with Information and communication technologies for development governance and develop and take control of the Information and communication technologies for development initiative.

– Record-keeping requirements flow from the records needed as inputs, outputs, controls and for transformation of a Big Data process. ask yourself: are the records needed as inputs to the Big Data process available?

– Who will provide the final approval of Big Data deliverables?

– How do we go about Securing Big Data?

Distributed file system Critical Criteria:

Deduce Distributed file system governance and define what our big hairy audacious Distributed file system goal is.

– what is the best design framework for Big Data organization now that, in a post industrial-age if the top-down, command and control model is no longer relevant?

– What is the total cost related to deploying Big Data, including any consulting or professional services?

Apache Hadoop Critical Criteria:

Sort Apache Hadoop risks and find answers.

– Are we Assessing Big Data and Risk?

Presidency of Barack Obama Critical Criteria:

Ventilate your thoughts about Presidency of Barack Obama planning and diversify disclosure of information – dealing with confidential Presidency of Barack Obama information.

– What role does communication play in the success or failure of a Big Data project?

– What vendors make products that address the Big Data needs?

Seventh Framework Program Critical Criteria:

Face Seventh Framework Program planning and correct Seventh Framework Program management by competencies.

– Are there Big Data problems defined?

National Diet Library Critical Criteria:

Audit National Diet Library tasks and look in other fields.

– What are your most important goals for the strategic Big Data objectives?

– Who are the people involved in developing and implementing Big Data?

Cyber-physical system Critical Criteria:

Check Cyber-physical system adoptions and frame using storytelling to create more compelling Cyber-physical system projects.

– Is Supporting Big Data documentation required?

Nonlinear system identification Critical Criteria:

Grasp Nonlinear system identification failures and attract Nonlinear system identification skills.

– Is Big Data Realistic, or are you setting yourself up for failure?

– What about Big Data Analysis of results?

Data philanthropy Critical Criteria:

Understand Data philanthropy adoptions and catalog Data philanthropy activities.

– What are the barriers to increased Big Data production?

MIT Computer Science and Artificial Intelligence Laboratory Critical Criteria:

Have a meeting on MIT Computer Science and Artificial Intelligence Laboratory projects and modify and define the unique characteristics of interactive MIT Computer Science and Artificial Intelligence Laboratory projects.

– In the case of a Big Data project, the criteria for the audit derive from implementation objectives. an audit of a Big Data project involves assessing whether the recommendations outlined for implementation have been met. in other words, can we track that any Big Data project is implemented as planned, and is it working?

Agent-based model Critical Criteria:

Test Agent-based model failures and change contexts.

– What are the Key enablers to make this Big Data move?

– Do we do Agent-Based Modeling and Simulation?

– What Is Agent-Based Modeling & Simulation?

– Agent-based modeling: A revolution?

Business Intelligence Critical Criteria:

Deliberate Business Intelligence adoptions and look for lots of ideas.

– Forget right-click and control+z. mobile interactions are fundamentally different from those on a desktop. does your mobile solution allow you to interact with desktop-authored dashboards using touchscreen gestures like taps, flicks, and pinches?

– Can your software connect to all forms of data, from text and Excel files to cloud and enterprise-grade databases, with a few clicks?

– How should a complicated business setup their business intelligence and analysis to make decisions best?

– Does your bi software work well with both centralized and decentralized data architectures and vendors?

– What does a typical data warehouse and business intelligence organizational structure look like?

– What are the approaches to handle RTB related data 100 GB aggregated for business intelligence?

– What is the difference between business intelligence business analytics and data mining?

– What specialized bi knowledge does your business have that can be leveraged?

– Describe the process of data transformation required by your system?

– What percentage of enterprise apps will be web based in 3 years?

– No single business unit responsible for enterprise data?

– Can Business Intelligence BI meet business expectations?

– What is the future of BI Score cards KPI etc?

– Is the product accessible from the internet?

– Why do we need business intelligence?

User behavior analytics Critical Criteria:

Audit User behavior analytics projects and forecast involvement of future User behavior analytics projects in development.

– Do we monitor the Big Data decisions made and fine tune them as they evolve?

– To what extent does management recognize Big Data as a tool to increase the results?

Government of India Critical Criteria:

Design Government of India tasks and point out Government of India tensions in leadership.

– What are specific Big Data Rules to follow?

– Do we all define Big Data in the same way?

Consumer privacy Critical Criteria:

Group Consumer privacy adoptions and document what potential Consumer privacy megatrends could make our business model obsolete.

– Think of your Big Data project. what are the main functions?

Bloomberg Businessweek Critical Criteria:

Face Bloomberg Businessweek planning and adopt an insight outlook.

– How do we measure improved Big Data service perception, and satisfaction?

– Is Big Data dependent on the successful delivery of a current project?

– How will you know that the Big Data project has been successful?

Machine learning Critical Criteria:

Audit Machine learning tactics and gather Machine learning models .

– What are the long-term implications of other disruptive technologies (e.g., machine learning, robotics, data analytics) converging with blockchain development?

– Will new equipment/products be required to facilitate Big Data delivery for example is new software needed?

Cluster analysis Critical Criteria:

Add value to Cluster analysis decisions and drive action.

– Meeting the challenge: are missed Big Data opportunities costing us money?

– Risk factors: what are the characteristics of Big Data that make it risky?

Oracle NoSQL Database Critical Criteria:

Participate in Oracle NoSQL Database quality and maintain Oracle NoSQL Database for success.

– Have you identified your Big Data key performance indicators?

– How can the value of Big Data be defined?

Natural disaster Critical Criteria:

Contribute to Natural disaster adoptions and budget for Natural disaster challenges.

– Does cloud storage get affected during a natural disaster how can we ensure a secure disaster recovery for that?

– How much safe is data from Natural disaster?

Data lineage Critical Criteria:

Recall Data lineage tactics and cater for concise Data lineage education.

– What new services of functionality will be implemented next with Big Data ?

Data sharing Critical Criteria:

Chart Data sharing quality and achieve a single Data sharing view and bringing data together.

– What will be the policies for data sharing and public access (including provisions for protection of privacy, confidentiality, security, intellectual property rights and other rights as appropriate)?

– What is (or would be) the added value of collaborating with other entities regarding data sharing across economic sectors?

– Does the project require agreements related to organizational data sharing that havent yet been created?

– What is (or would be) the added value of collaborating with other entities regarding data sharing in your sector?

– What transformations will be necessary to prepare data for preservation / data sharing?

– Do you regularly audit 3rd parties with whom you have data sharing agreements with?

– What would be needed to support collaboration on data sharing across economic sectors?

– Is maximizing Big Data protection the same as minimizing Big Data loss?

– What would be needed to support collaboration on data sharing in your sector?

– How can we improve data sharing methodologies between departments?

– Do you have any data sharing agreements with any 3rd parties?

Data journalism Critical Criteria:

Talk about Data journalism tactics and find the ideas you already have.

Topological Data Analysis Critical Criteria:

Categorize Topological Data Analysis leadership and get going.

– What other jobs or tasks affect the performance of the steps in the Big Data process?

– When a Big Data manager recognizes a problem, what options are available?

Systems management Critical Criteria:

Value Systems management visions and probe the present value of growth of Systems management.

– In a project to restructure Big Data outcomes, which stakeholders would you involve?

– How to deal with Big Data Changes?

Viktor Mayer-Schönberger Critical Criteria:

Win new insights about Viktor Mayer-Schönberger engagements and modify and define the unique characteristics of interactive Viktor Mayer-Schönberger projects.

– At what point will vulnerability assessments be performed once Big Data is put into production (e.g., ongoing Risk Management after implementation)?

– What are the disruptive Big Data technologies that enable our organization to radically change our business processes?

– Does Big Data analysis isolate the fundamental causes of problems?

Relational database management system Critical Criteria:

Reorganize Relational database management system governance and catalog what business benefits will Relational database management system goals deliver if achieved.

– How can you measure Big Data in a systematic way?

Surveillance capitalism Critical Criteria:

Reorganize Surveillance capitalism risks and diversify disclosure of information – dealing with confidential Surveillance capitalism information.

Oracle Corporation Critical Criteria:

Study Oracle Corporation visions and sort Oracle Corporation activities.

– Does Big Data systematically track and analyze outcomes for accountability and quality improvement?

– Will Big Data deliverables need to be tested and, if so, by whom?

Google Flu Trends Critical Criteria:

Give examples of Google Flu Trends leadership and shift your focus.

Massive parallel processing Critical Criteria:

Scan Massive parallel processing decisions and correct better engagement with Massive parallel processing results.

– How do we Lead with Big Data in Mind?

Economic productivity Critical Criteria:

Group Economic productivity strategies and grade techniques for implementing Economic productivity controls.

– What are all of our Big Data domains and what do they do?

EMC Corporation Critical Criteria:

Give examples of EMC Corporation planning and sort EMC Corporation activities.

– How do we keep improving Big Data?

– How much does Big Data help?

Complex Systems Critical Criteria:

Study Complex Systems results and pioneer acquisition of Complex Systems systems.

– How much testing is necessary in order to expose all the potential failure modes and situations of highly integrated complex systems?

– Who is responsible for ensuring appropriate resources (time, people and money) are allocated to Big Data?

– Complex interventions or complex systems?


This quick readiness checklist is a selected resource to help you move forward. Learn more about how to achieve comprehensive insights with the Big Data Information Management Self Assessment:


Author: Gerard Blokdijk

CEO at The Art of Service | theartofservice.com

[email protected]


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.

External links:

To address the criteria in this checklist, these selected resources are provided for sources of further research and information:

Ulf-Dietrich Reips External links:

Ulf-Dietrich Reips – Google Scholar Citations

Ulf-Dietrich Reips | Colorado PROFILES

Ulf-Dietrich Reips

The Globe and Mail External links:

The Globe and Mail French River Cruise – Official Site

The Globe and Mail Centre – Official Site

The Globe and Mail – Subscription

Dirty data External links:

Knock out dirty data | Infographic | Experian Data Quality

Dirty Data in your CRM? What’s the real cost?

What is dirty data? – Definition from WhatIs.com

Data acquisition External links:

Data Acquisition Databook – AbeBooks

Hi-Techniques Inc. – High Performance Data Acquisition …

Manager, Data Acquisition – Columbus, OH – Quantum …

Data visualization External links:

What is data visualization? – Definition from WhatIs.com

Data Visualization | FEMA.gov

Data Visualization & Business Intelligence Tool | datapine

Data quality External links:

Data quality (Book, 2001) [WorldCat.org]

Horizon 2020 External links:

Horizon 2020 Energy Info Days

Horizon 2020: What to Expect and Where to Apply in 2018- …

EFMC: Horizon 2020 Experts

The Independent External links:

AICC, The Independent Packaging Association

SFA | Empowering the Independent Financial Advisor – SFA

Anand Rajaraman External links:

Anand Rajaraman Profiles | Facebook

Anand Rajaraman – The Mathematics Genealogy Project

Anand Rajaraman YourStory.com

Google Translate External links:

Google Translate

Google Translate

Google Translate on the App Store – iTunes – Apple

Descriptive statistics External links:

[DOC]Descriptive statistics for measurements of a single …

Descriptive Statistics Essays – ManyEssays.com

Descriptive Statistics

Extract, transform, load External links:

What is ETL (Extract, Transform, Load)? Webopedia Definition

The Data Incubator External links:

The Data Incubator Reviews | Course Report

Hire Data Scientists | The Data Incubator

The Data Incubator – Google+

Digital camera External links:

www.amazon.com › … › Digital Cameras › Point & Shoot Digital Cameras

Best Digital Camera Reviews – Consumer Reports

Predictive analytics External links:

Customer Analytics & Predictive Analytics Tools for Business

Best Predictive Analytics Software in 2017 | G2 Crowd

Predictive Analytics for Healthcare | Forecast Health

Mobile device External links:

Mobile Tracker – a mobile device IP address tracking

Duke Health Mobile Device Manager

Restart the Apple Mobile Device Service (AMDS) on Windows

Data set External links:

Finding the Mean of a Data Set as a “Balance Point” – YouTube

OpenFEMA Dataset: OpenFEMA Data Sets – V1 | FEMA.gov

Limited Data Set | HHS.gov

Computer data storage External links:

Computer Data Storage Options – Ferris State University

Lecture 16 | Computer Data Storage | Computer Programming

Find great deals on eBay for computer data storage. Shop with confidence.

Human Genome Project External links:

ERIC – The Human Genome Project: Biology, Computers, …

NIH Fact Sheets – Human Genome Project

The Human Genome Project | Discover Nursing

Data fusion External links:

Data Fusion Solutions

Data fusion : concepts and ideas (eBook, 2012) …

Algorithms and Data Fusion – Quora

Data transmission External links:

Data transmission (Book, 1965) [WorldCat.org]

Data transmission (Book, 1989) [WorldCat.org]

[PDF]Data Transmission – Washington University in St. Louis

Distributed file system External links:

Setting Up a DFS (Distributed File System) Server – YouTube

Download Distributed File System Namespace Solution …

Apache Hadoop External links:

Apache Hadoop open source ecosystem | Cloudera

Apache Hadoop training from Cloudera University

Services and Support for Apache Hadoop | Cloudera

Seventh Framework Program External links:

Seventh Framework Program | Fortnightly

National Diet Library External links:

National Diet Library | library, Tokyo, Japan | Britannica.com

National Diet Library law. (Book, 1961) [WorldCat.org]

Online Gallery | National Diet Library

Cyber-physical system External links:

EuroCPS | Cyber-Physical Systems

Cyber-Physical Systems | NSF – National Science Foundation

Nonlinear system identification External links:



MIT Computer Science and Artificial Intelligence Laboratory External links:

MIT Computer Science and Artificial Intelligence Laboratory …

MIT Computer Science and Artificial Intelligence Laboratory

Agent-based model External links:

What is Agent-Based Modeling | IGI Global

[PDF]Tutorial on agent-based modelling and simulation – …

Business Intelligence External links:

List of Business Intelligence Skills – The Balance

[PDF]Position Title: Business Intelligence Analyst – ttra

User behavior analytics External links:

User Behavior Analytics (UBA) Tools and Solutions | Rapid7

IBM QRadar User Behavior Analytics – Overview – United …

User Behavior Analytics | FairWarning.com

Government of India External links:

eProcurement System Government of India

Consumer privacy External links:

Consumer Privacy Pledge | Privacy Policies | U.S. Bank

U.S. Consumer Privacy Notice from Bank of America

Consumer Privacy Policy | Safeco Insurance

Bloomberg Businessweek External links:

Bloomberg Businessweek – October 9, 2017 Issue – Bloomberg

Bloomberg Businessweek Middle East – Home | Facebook

Bloomberg Businessweek – Home | Facebook

Machine learning External links:

DataRobot – Automated Machine Learning for Predictive …

Microsoft Azure Machine Learning Studio

Cluster analysis External links:

Cluster Analysis With JMP – YouTube

What Us Businesses Utilize Cluster Analysis? – Quora

Cluster Analysis Software | NCSS Statistical Software | NCSS

Oracle NoSQL Database External links:

The Oracle NoSQL Database – CERN Document Server

Oracle Blogs | Oracle NoSQL Database Blog

Natural disaster External links:

Natural Disaster Survival – Roblox

Natural Disaster Claims | Safeco Insurance

Natural disaster – Customer Assistance – Chase

Data lineage External links:

Metadata Lineage Holy Grail | InfoLibrarian Corporation

Simplifying Data Lineage – Solidatus

Data Lineage Helps to Drive Business Value | Trifacta

Data sharing External links:

[DOC]Data Sharing MOU – Draft v3.docx – Office of the CISO

Data Sharing Platform from Salesforce – Salesforce.com

LETTR | Proven Data Sharing. Any RMS.

Data journalism External links:

Data journalism | Media | The Guardian

The data journalism handbook (eBook, 2012) …

People’s Pundit Daily | Independent Data Journalism

Topological Data Analysis External links:

Topological Data Analysis – Graduate Center, CUNY

[1703.04385] Topological Data Analysis of Financial …

CiteSeerX — Topological Data Analysis

Systems management External links:

Welcome to the Mail Systems Management Association

HSMN – Health Systems Management Network

M.S. Information Systems Management – American …

Viktor Mayer-Schönberger External links:

Viktor Mayer-Schönberger, Delete: The Virtue of …

Viktor Mayer-Schönberger | Facebook

Relational database management system External links:

RDB: a Relational Database Management System

Relational Database Management System (RDBMS) – Techopedia.com

NoSQL Relational Database Management System: …
www.strozzi.it/cgi-bin/CSA/tw7/I/en_US/NoSQL/Home Page

Oracle Corporation External links:

Oracle Corporation – The New York Times

Oracle Corporation: NYSE:ORCL quotes & news – Google …

Oracle Corporation – ORCL – Stock Price Today – Zacks

Google Flu Trends External links:

Google Flu Trends Is Under The Weather, Study Says

Google Flu Trends

Google Flu Trends – Track Influenza Faster Than the CDC

Economic productivity External links:

Economic productivity has declined in some countries as …

[PDF]FMSIB: Moving Freight for Economic Productivity

EMC Corporation External links:

EMC Corporation

EMC Corporation

EMC Corporation Careers & Job Opportunities – Monster

Complex Systems External links:

About Complex Systems | NECSI

ICTT-Systems Engineering for Complex Systems

Model-Based Design of Complex Systems

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