• Skip to main content
  • Skip to secondary menu
  • Skip to primary sidebar
  • Skip to footer
  • Articles
  • News
  • Events
  • Advertize
  • Jobs
  • Courses
  • Contact
  • (0)
  • LoginRegister
    • Facebook
    • LinkedIn
    • RSS
      Articles
      News
      Events
      Job Posts
    • Twitter
Datafloq

Datafloq

Data and Technology Insights

  • Categories
    • Big Data
    • Blockchain
    • Cloud
    • Internet Of Things
    • Metaverse
    • Robotics
    • Cybersecurity
    • Startups
    • Strategy
    • Technical
  • Big Data
  • Blockchain
  • Cloud
  • Metaverse
  • Internet Of Things
  • Robotics
  • Cybersecurity
  • Startups
  • Strategy
  • Technical

Free Business Analytics Content Part 4

Martyn Jones / 9 min read.
March 12, 2016
Datafloq AI Score
×

Datafloq AI Score: 69.67

Datafloq enables anyone to contribute articles, but we value high-quality content. This means that we do not accept SEO link building content, spammy articles, clickbait, articles written by bots and especially not misinformation. Therefore, we have developed an AI, built using multiple built open-source and proprietary tools to instantly define whether an article is written by a human or a bot and determine the level of bias, objectivity, whether it is fact-based or not, sentiment and overall quality.

Articles published on Datafloq need to have a minimum AI score of 60% and we provide this graph to give more detailed information on how we rate this article. Please note that this is a work in progress and if you have any suggestions, feel free to contact us.

floq.to/98jNL

Why buy when you can get it for free?

Back at you! Here is the fourth fantastic delivery of an amazing and fabulous selection of free and widely available business analytics learning content, which has been prepared just for you.

  • Data Mining Data mining is an interdisciplinary subfield of computer science. It is the computational process of discovering patterns in large data sets (big data) involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. Aside from the raw analysis step, it involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating. Data mining is the analysis step of the knowledge discovery in databases process, or KDD. https://en.wikipedia.org/wiki/Data_mining
    Another interesting article on the subject is Raymond Lis piece titled Top 10 Data Mining Algorithms, Explained which is available on Gregory Piatetsky-Shapiros great KDNuggets site: https://www.kdnuggets.com/2015/05/top-10-data-mining-algorithms-explained.html


  • Decision analysis (DA) is the discipline comprising the philosophy, theory, methodology, and professional practice necessary to address important decisions in a formal manner. Decision analysis includes many procedures, methods, and tools for identifying, clearly representing, and formally assessing important aspects of a decision, for prescribing a recommended course of action by applying the maximum expected utility action axiom to a well-formed representation of the decision, and for translating the formal representation of a decision and its corresponding recommendation into insight for the decision maker and other stakeholders. https://en.wikipedia.org/wiki/Decision_analysis
    You may also be interested in this old yet timely piece featured on the Harvard Business Review site Decision Analysis Comes of Age by Jacob W. Ulvila and Rex V. Brown https://hbr.org/1982/09/decision-analysis-comes-of-age
  • Engineering analytics. Engineering is the application of mathematics, empirical evidence and scientific, economic, social, and practical knowledge in order to invent, innovate, design, build, maintain, research, and improve structures, machines, tools, systems, components, materials, and processes. https://en.wikipedia.org/wiki/Engineering
    The usually wonderful Google also provide a free download Introduction to Lean Analytics (in Ebook, PDF and EPUB formats) https://www.google.com/fusiontables/DataSource?docid=1NqTVajvpiSktRK328XiFvUWSLnjT2RkpCpKyzJIE#rows:id=1
  • Forecasting analytics. Forecasting is the process of making predictions of the future based on past and present data and analysis of trends. A commonplace example might be estimation of some variable of interest at some specified future date. Prediction is a similar, but more general term. Both might refer to formal statistical methods employing time series, cross-sectional or longitudinal data, or alternatively to less formal judgmental methods. Usage can differ between areas of application: for example, in hydrology, the terms forecast and forecasting are sometimes reserved for estimates of values at certain specific future times, while the term prediction is used for more general estimates, such as the number of times floods will occur over a long period. https://en.wikipedia.org/wiki/Forecasting
    Heres another great piece from HBR, How to Choose the Right Forecasting Technique by John C. ChambersSatinder, K. MullickDonald and D. Smith. Its from 1971, but it rocks the numbers. https://hbr.org/1971/07/how-to-choose-the-right-forecasting-technique
  • Game analytics. Game theory is the study of mathematical models of conflict and cooperation between intelligent rational decision-makers. Game theory is mainly used in economics, political science, and psychology, as well as logic, computer science, biology and poker. Originally, it addressed zero-sum games, in which one persons gains result in losses for the other participants. Today, game theory applies to a wide range of behavioral relations, and is now an umbrella term for the science of logical decision making in humans, animals, and computers. https://en.wikipedia.org/wiki/Game_theory
    You may also be interested in a very well written research report available from the LSE, titled Game Theory. Thanks to Theodore L. Turocy of Texas A&M and Berhard von Stengel of the London School of Economics (at the time of publishing). https://www.cdam.lse.ac.uk/Reports/Files/cdam-2001-09.pdf
  • Industrial analytics. Industrial engineering is a branch of engineering which deals with the optimization of complex processes or systems. Industrial engineers work to eliminate waste of time, money, materials, man-hours, machine time, energy and other resources that do not generate value. According to the Institute of Industrial Engineers, they figure out how to do things better. They engineer processes and systems that improve quality and productivity. https://en.wikipedia.org/wiki/Industrial_engineering
    Datawatch Corporation have also produced a great little paper entitled Industrial analytics powered by the internet of things. You might like to check it out: https://www.datawatch.com/wp-content/uploads/2014/10/Gartner-Industrial-Analytics-Newsletter.pdf
  • Logistics analytics. Logistics is generally the detailed organization and implementation of a complex operation. In a general business sense, logistics is the management of the flow of things between the point of origin and the point of consumption in order to meet requirements of customers or corporations. The resources managed in logistics can include physical items, such as food, materials, animals, equipment and liquids, as well as abstract items, such as time and information. The logistics of physical items usually involves the integration of information flow, material handling, production, packaging, inventory, transportation, warehousing, and often security. https://en.wikipedia.org/wiki/Logistics
    Cap Gemini have also produced a great little paper on Logistics Analysis, which may be found here: https://www.capgemini.com/resource-file-access/resource/pdf/logistics_0.pdf
  • Modelling analytics. A mathematical model is a description of a system using mathematical concepts and language. The process of developing a mathematical model is termed mathematical modeling. Mathematical models are used in the natural sciences (such as physics, biology, earth science, meteorology) and engineering disciplines (such as computer science, artificial intelligence), as well as in the social sciences (such as economics, psychology, sociology, political science). Physicists, engineers, statisticians, operations research analysts, and economists use mathematical models most extensively. A model may help to explain a system and to study the effects of different components, and to make predictions about behaviour. https://en.wikipedia.org/wiki/Mathematical_model
  • Optimisation analytics. Mathematical optimisation. In mathematics, computer science and operations research, mathematical optimization (alternatively, optimization or mathematical programming) is the selection of a best element (with regard to some criteria) from some set of available alternatives. https://en.wikipedia.org/wiki/Mathematical_optimization
  • Probability analytics. Probability is the measure of the likelihood that an event will occur. Probability is quantified as a number between 0 and 1 (where 0 indicates impossibility and 1 indicates certainty). The higher the probability of an event, the more certain we are that the event will occur. A simple example is the tossing of a fair (unbiased) coin. Since the coin is unbiased, the two outcomes (head and tail) are equally probable; the probability of head equals the probability of tail. Since no other outcome is possible, the probability is 1/2 (or 50%) of either head or tail. In other words, the probability of head is 1 out of 2 outcomes and the probability of tail is also, 1 out of 2 outcomes. https://en.wikipedia.org/wiki/Probability
    Heres a real book on probability from the Harvard web site. Probability Theory and Stochastic Processes with Applications, by Oliver Knill Well worth a perusal https://www.math.harvard.edu/~knill/books/KnillProbability.pdf
  • Project analytics. Project management is the discipline of initiating, planning, executing, controlling, and closing the work of a team to achieve specific goals and meet specific success criteria. A project is a temporary endeavor designed to produce a unique product, service or result with a defined beginning and end (usually time-constrained, and often constrained by funding or deliverables) undertaken to meet unique goals and objectives, typically to bring about beneficial change or added value. https://en.wikipedia.org/wiki/Project_management
    You might also like to check out this snazzy paper from Deloitte, entitled Predictive project analytics Will your project be successful? https://www2.deloitte.com/content/dam/Deloitte/ca/Documents/risk/ca-en-ers-predictive-project-analytics.pdf
  • Simulation analytics. Simulation is the imitation of the operation of a real-world process or system over time. The act of simulating something first requires that a model be developed; this model represents the key characteristics or behaviors/functions of the selected physical or abstract system or process. The model represents the system itself, whereas the simulation represents the operation of the system over time. https://en.wikipedia.org/wiki/Simulation
    RAND put together this comprehensive paper on Modeling, Simulation, and Operations Analysis in Afghanistan and Iraq https://www.rand.org/content/dam/rand/pubs/research_reports/RR300/RR382/RAND_RR382.pdf
  • Social analysis. Social networks. A social network is a social structure made up of a set of social actors (such as individuals or organizations), sets of dyadic ties, and other social interactions between actors. The social network perspective provides a set of methods for analyzing the structure of whole social entities as well as a variety of theories explaining the patterns observed in these structures. The study of these structures uses social network analysis to identify local and global patterns, locate influential entities, and examine network dynamics. https://en.wikipedia.org/wiki/Social_network
    Engage more with insights and predictive tools. Here is a link to some great social analytics content from Adobe: https://www.adobe.com/la/solutions/social-marketing/social-analytics.html
  • Supply chain analytics. Supply chain management (SCM) is the management of the flow of goods and services. It includes the movement and storage of raw materials, work-in-process inventory, and finished goods from point of origin to point of consumption. Interconnected or interlinked networks, channels and node businesses are involved in the provision of products and services required by end customers in a supply chain. Supply chain management has been defined as the design, planning, execution, control, and monitoring of supply chain activities with the objective of creating net value, building a competitive infrastructure, leveraging worldwide logistics, synchronizing supply with demand and measuring performance globally. https://en.wikipedia.org/wiki/Supply_chain_management
    This is something else that might also take your interest to the next level. Supply Chain Analytics: What is it and Why is it so Important? by Paul Myerson in The Lean Supply Chain: https://www.industryweek.com/blog/supply-chain-analytics-what-it-and-why-it-so-important

I hope you find the content useful. Of course, all thanks should really go to Wikipedia and their unpaid expert contributors, as well as additional references and content providers.

I will try to get the next part of Free Business Analytics Content onto Linked Pulse over the next week.


Interested in what the future will bring? Download our 2023 Technology Trends eBook for free.

Consent

Many thanks for reading.

You may be interested in other articles I have written:

Free Business Analytics Content Part 1

Free Business Analytics Content Part 2

Free Business Analytics Content Part 3

Categories: Big Data
Tags: analytics, Big Data, data mining, decisions, engineering, optimization, simulation, supply chain

About Martyn Jones

Martyn's range of knowledge, skills and experience span executive management, organisational strategy, strategic business performance and information management, leadership, business analysis, business and data architectures, data management, and executive and team coaching.

Martyn has worked with and advised many of the world's best-known organisations including Adidas, Banco Santander, Bank of China, BBVA, Boston Consulting Group, British Telecom, La Caixa, Central Statistical Office (UK), Central Statistical Office of Poland, Citco, Citigroup, Credit Suisse, E.On, Eroski, European Union, Fnac, France Telecom, Hewlett Packard, Iberdrola, IBM, Iberia, Infineon, T rkiye ' , Metropolitan Police, Movistar, NCR, National Health Service (UK), Office of the Governor - State of California, Oracle, The Home Office (UK), Rolls-Royce Marine Power Operations, the Royal Navy, Shell, Swiss Life, TSB, UBS, Unisys, the United Nations and Xerox, among many others.

He currently focuses on helping clients to:

-' Create relevant, understandable and actionable information
-' Plan, manage, design, develop and deliver information supply frameworks for the timely, appropriate and adequate supply of information
-' Design, develop and deliver beneficial, tangible and usable strategic performance and information frameworks
-' Design, develop and deliver relevant and coherent performance models, indicators and metrics
-' Plan, manage, design, develop and deliver information and data analytic strategies
-' Design, develop and deliver management informational insight and dynamic feedback solutions
-' Coach teams in measuring and managing performance
-' Align people, competencies, processes and practices with strategy
-' Prepare clients for the next big thing in Information Management and Analytics
-' Help IT suppliers to better align with the needs and nature of clients and prospects
-' Help clients capitalise on tangible benefits derived from advanced information architectures and management

Primary Sidebar

E-mail Newsletter

Sign up to receive email updates daily and to hear what's going on with us!

Publish
AN Article
Submit
a press release
List
AN Event
Create
A Job Post
Host your website with Managed WordPress for $1.00/mo with GoDaddy!

Related Articles

The Advantages of IT Staff Augmentation Over Traditional Hiring

May 4, 2023 By Mukesh Ram

The State of Digital Asset Management in 2023

May 3, 2023 By pimcoremkt

Test Data Management – Implementation Challenges and Tools Available

May 1, 2023 By yash.mehta262

Related Jobs

  • Software Engineer | South Yorkshire, GB - February 07, 2023
  • Software Engineer with C# .net Investment House | London, GB - February 07, 2023
  • Senior Java Developer | London, GB - February 07, 2023
  • Software Engineer – Growing Digital Media Company | London, GB - February 07, 2023
  • LBG Returners – Senior Data Analyst | Chester Moor, GB - February 07, 2023
More Jobs

Tags

AI Amazon analysis analytics app application Artificial Intelligence BI Big Data business China Cloud Companies company costs crypto customers Data design development digital environment experience future Google+ government information learning machine learning market mobile Musk news Other public research sales security share social social media software strategy technology twitter

Related Events

  • 6th Middle East Banking AI & Analytics Summit 2023 | Riyadh, Saudi Arabia - May 10, 2023
  • Data Science Salon NYC: AI & Machine Learning in Finance & Technology | The Theater Center - December 7, 2022
  • Big Data LDN 2023 | Olympia London - September 20, 2023
More events

Related Online Courses

  • Oracle Cloud Data Management Foundations Workshop
  • Data Science at Scale
  • Statistics with Python
More courses

Footer


Datafloq is the one-stop source for big data, blockchain and artificial intelligence. We offer information, insights and opportunities to drive innovation with emerging technologies.

  • Facebook
  • LinkedIn
  • RSS
  • Twitter

Recent

  • 5 Reasons Why Modern Data Integration Gives You a Competitive Advantage
  • 5 Most Common Database Structures for Small Businesses
  • 6 Ways to Reduce IT Costs Through Observability
  • How is Big Data Analytics Used in Business? These 5 Use Cases Share Valuable Insights
  • How Realistic Are Self-Driving Cars?

Search

Tags

AI Amazon analysis analytics app application Artificial Intelligence BI Big Data business China Cloud Companies company costs crypto customers Data design development digital environment experience future Google+ government information learning machine learning market mobile Musk news Other public research sales security share social social media software strategy technology twitter

Copyright © 2023 Datafloq
HTML Sitemap| Privacy| Terms| Cookies

  • Facebook
  • Twitter
  • LinkedIn
  • WhatsApp

In order to optimize the website and to continuously improve Datafloq, we use cookies. For more information click here.

Dear visitor,
Thank you for visiting Datafloq. If you find our content interesting, please subscribe to our weekly newsletter:

Did you know that you can publish job posts for free on Datafloq? You can start immediately and find the best candidates for free! Click here to get started.

Not Now Subscribe

Thanks for visiting Datafloq
If you enjoyed our content on emerging technologies, why not subscribe to our weekly newsletter to receive the latest news straight into your mailbox?

Subscribe

No thanks

Privacy Overview

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.

Necessary Cookies

Strictly Necessary Cookie should be enabled at all times so that we can save your preferences for cookie settings.

If you disable this cookie, we will not be able to save your preferences. This means that every time you visit this website you will need to enable or disable cookies again.

Marketing cookies

This website uses Google Analytics to collect anonymous information such as the number of visitors to the site, and the most popular pages.

Keeping this cookie enabled helps us to improve our website.

Please enable Strictly Necessary Cookies first so that we can save your preferences!