Guides: IT & Cyber Security: Big Data

eBooks - Big Data

Alteryx Designer: The Definitive Guide by Joshua Burkhow Analytics projects are frequently long, drawn-out affairs, requiring multiple teams and skills to clean, join, and eventually turn data into analysis for timely decision-making. Alteryx Designer changes all of that. With this low-code, self-service, drag-and-drop workflow platform, new and experienced data and business analysts can deliver results in hours instead of weeks.
Publication Date: 2023
The Big Data Agenda by Annika Richterich This book highlights that the capacity for gathering, analysing, and utilising vast amounts of digital (user) data raises significant ethical issues. Annika Richterich provides a systematic contemporary overview of the field of critical data studies that reflects on practices of digital data collection and analysis.
Publication Date: 2018
Big Data in Context by Thomas Hoeren, Barbara Kolany-Raiser This book sheds new light on a selection of big data scenarios from an interdisciplinary perspective. It features legal, sociological and economic approaches to fundamental big data topics such as privacy, data quality and the ECJ’s Safe Harbor decision on the one hand, and practical applications such as smart cars, wearables and web tracking on the other. Addressing the interests of researchers and practitioners alike, it provides a comprehensive overview of and introduction to the emerging challenges regarding big data.
Publication Date: 2018
Consumer Data Research by James Cheshire, Paul Longley, Alex Singleton Big Data collected by customer-facing organisations – such as smartphone logs, store loyalty card transactions, smart travel tickets, social media posts, or smart energy meter readings – account for most of the data collected about citizens today. As a result, they are transforming the practice of social science. Consumer Big Data are distinct from conventional social science data not only in their volume, variety and velocity, but also in terms of their provenance and fitness for ever more research purposes.
Publication Date: 2018
The Datafied Society by Mirko Tobias Schäfer (Editor); Karin van Es (Editor) As machine-readable data comes to play an increasingly important role in everyday life, researchers find themselves with rich resources for studying society. The novel methods and tools needed to work with such data require not only new knowledge and skills, but also a new way of thinking about best research practices.
Publication Date: 2017
Digital Objects, Digital Subjects by David Chandler (Editor); Christian Fuchs (Editor) This volume explores activism, research and critique in the age of digital subjects and objects and Big Data capitalism after a digital turn said to have radically transformed our political futures. Optimists assert that the 'digital' promises: new forms of community and ways of knowing and sensing, innovation, participatory culture, networked activism, and distributed democracy.
Publication Date: 2019
Essential Math for AI by Hala Nelson Companies are scrambling to integrate AI into their systems and operations. But to build truly successful solutions, you need a firm grasp of the underlying mathematics. This accessible guide walks you through the math necessary to thrive in the AI field such as focusing on real-world applications rather than dense academic theory.
Exam Ref SC-900 Microsoft Security, Compliance, and Identity Fundamentals by Yuri Diogenes; Nicholas DiCola; Mark Morowczynski; Kevin McKinnerney Prepare for Microsoft Exam SC-900 and demonstrate your real-world knowledge of the fundamentals of security, compliance, and identity (SCI) across cloud-based and related Microsoft services. Designed for business stakeholders, new and existing IT professionals, functional consultants, and students, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Security, Compliance, and Identity Fundamentals level.
Publication Date: 2024
Machine Learning for High-Risk Applications by Patrick Hall, James Curtis, Parul Pandey The past decade has witnessed the broad adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight in their widespread implementation has resulted in some incidents and harmful outcomes that could have been avoided with proper risk management. Before we can realize AI/ML's true benefit, practitioners must understand how to mitigate its risks.
Publication Date: 2023

O'Reilly eBook database

Metasearch

Data Commons The Data Commons provides services to manage, organize, preserve, publish, discover, and reuse data. You can browse Community Released Data and data curated by CyVerse.
Enigma Public Data The world's broadest collection of public data curated into a single searchable, explorable web portal and API.
European Commission - Global Human Settlement GHSL - Global Human Settlement Layer A new open and free tool for assessing the human presence on the planet.
GitHub Topic-centric Public datasets.
Google Dataset Search Google Dataset Search, launched in 2018, is a search engine from Google that helps researchers locate online data that is freely available for use.
Open Data Network Publish data and share. Find data and build. Answer questions.

Free Tutorials

Coursera - Top Big Data Free Courses Take courses from the world's best instructors and universities. Courses include recorded auto-graded and peer-reviewed assignments, video lectures, and community discussion forums. When you complete a course, you’ll be eligible to receive a shareable electronic Course Certificate for a small fee.
Lynda.com from LinkedIn - Big Data Training and Tutorials (1 month free) What is big data? It's a phrase used to quantify data sets that are so large and complex that they become difficult to exchange, secure, and analyze with typical tools. These courses on big data show you how to solve these problems, and many more, with leading IT tools and techniques.
Python - For Beginners Are you completely new to programming? If not then we presume you will be looking for information about why and how to get started with Python. Fortunately an experienced programmer in any programming language (whatever it may be) can pick up Python very quickly. It's also easy for beginners to use and learn, so jump in!
Tutorialspoint - Big Data Analytics Tutorial In this tutorial, we will discuss the most fundamental concepts and methods of Big Data Analytics. This tutorial has been prepared for software professionals aspiring to learn the basics of Big Data Analytics. Professionals who are into analytics in general may as well use this tutorial to good effect. Before you start proceeding with this tutorial, we assume that you have prior exposure to handling huge volumes of unprocessed data at an organizational level. Through this tutorial, we will develop a mini project to provide exposure to a real-world problem and how to solve it using Big Data Analytics. You can download the necessary files of this project from this link: http://www.tools.tutorialspoint.com/bda/
Udemy - Big Data and Hadoop Essentilas This course builds a essential fundamental understanding of Big Data problems and Hadoop as a solution. This course takes you through: 1. Understanding of Big Data problems with easy to understand examples. 2. History and advent of Hadoop right from when Hadoop wasn’t even named Hadoop. 3. What is Hadoop Magic which makes it so unique and powerful. 4. Understanding the difference between Data science and data engineering, which is one of the big confusions in selecting a carrier or understanding a job role. 5. And most importantly, demystifying Hadoop vendors like Cloudera, MapR and Hortonworks by understanding about them.
Udemy - R Basics - R Programming Language Introduction You will learn how to navigate in the RStudio interface, make basic graphs, about the basic structure of R including packages, how to perform basic commands in the R programming language, how to handle add on packages, how to use the R help tools and generally how to find your way in the R world.

Online videos

Adam Hirsch Discusses Big Data And Personalization (2015) Extending on that. I mean, it's about personalization, right? And the hardest part about personalization on an individual level is how much data is actually out there. So I, you know, knowing some of the process, you obviously have to test manually some of these theories of personalization.
Big Data (c. 2014) 3:13 We produce nearly 2.5 million terabytes of data per day. Directors Pina and Jakob want to find out if our entire lives have become computable. They will allow computer experts from the Fraunhofer Institute full access to their smartphone data to see if they can predict their future behavior.
The Crowd & The Cloud: Episode 1—Even Big Data Starts Small (2017) Citizen Science. 20,000 volunteers across the U.S. measure precipitation: when extreme weather hits, emergency managers turn their data into life-saving alerts. Armchair mappers worldwide update information used by first responders after the Nepal earthquake. A new project, EyesOnALZ, enlists the crowd to speed up research on Alzheimer’s disease. DIY enthusiasts from Public Lab map the BP oil spill with kites, balloons and cameras and continue to watchdog pollution.
Linda Benowitz Discusses big Data Concerns (c. 2015) 2:50 Banks have models that really look at your payment transactions and can see when a transaction deviates from your normal pattern. So that's something we've always done. This is Big Data

Online Journal Articles

Automated data-driven profiling: threats for group privacy (2020) User profiling with big data raises significant issues regarding privacy. Privacy studies typically focus on individual privacy; however, in the era of big data analytics, users are also targeted as members of specific groups, thus challenging their collective privacy with unidentified implications. Overall, this paper aims to argue that in the age of big data, there is a need to consider the collective aspects of privacy as well and to develop new ways of calculating privacy risks and identify privacy threats that emerge.
Governance in practice: Big data, privacy and information governance - incorporating an ethical-based assessment (2019) As the law lags behind in rapid technology innovations, particularly in big data, artificial intelligence (AI), machine-learning and the Internet of Things (IoT), there is increasing awareness and discussion about the need for an ethical-based approach to data analytics.
Mitigating risk in the age of big data (2019) Over 87 per cent of company value today is now in intangible assets. - Less than 0.5 per cent of data is actually ever analysed and used. In unlocking the value of big data there are some significant technical, legal and reputational risks and challenges to navigate.

Websites

Big Data Analytics Leverage the most effective big data technology to analyze the growing volume, velocity and variety of data for the greatest insights.
SAS - Big Data & IoT Insights Expert insights into big data, Internet of Things, and beyond.