Название: Data Engineering patterns on the cloud : How to solve common data engineering problems with cloud services?
Автор: Bartosz Konieczny
Издательство: Leanpub
Год: 2022-12-19
Страниц: 303
Язык: английский
Формат: pdf (true), epub
Размер: 28.3 MB

Doing data engineering without the cloud is hard to imagine nowadays. Does it mean, each cloud provider is different? Well, yes, each of them has its own specificities but it doesn't mean they're completely different. They all support several common data engineering patterns that you will find in the book classified in 7 categories: data processing, data storage, data security, data warehouse, data management, data orchestration and data transfer. This organization and the explanation of each pattern will help you understand a new cloud provider easier, whenever you come from AWS, Azure, or GCP environment.

Название: Hardening Your Macs: Keeping Apple Computers Safe at the Hardware and Software Level
Автор: Jesus Vigo, Jr.
Издательство: Apress
Год: 2023
Страниц: 228
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.2 MB

Learn the skills and solutions required to secure your Mac's operating system, the underlying hardware, and allow users to get work done safely. This book will show you how to create a Mac that’s made of steel and won’t buckle when attacked! Ok, there’s no such thing as unhackable. No magic tool or silver bullet will eliminate risk in all forms. Security is an ongoing journey – not a simple action or software application. And that is exactly what you’ll learn to master―the foundational knowledge, skills, and mindset to holistically protect Macs. Regardless of whether it’s your personal iMac or a fleet of MacBook Pro’s assigned to the remote employees within your organization, you’ll be able to limit access while identifying and mitigating risk unique to your environment.

Название: Privacy in Practice: Establish and Operationalize a Holistic Data Privacy Program
Автор: Alan Tang
Издательство: CRC Press
Год: 2023
Страниц: 474
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Privacy is not just the right to be left alone, but also the right to autonomy, control, and access to your personal data. The employment of new technologies over the last three decades drives personal data to play an increasingly important role in our economies, societies, and everyday lives. Personal information has become an increasingly valuable commodity in the digital age. At the same time, the abundance and persistence of personal data have elevated the risks to individuals’ privacy. In the age of Big Data, the Internet of Things, Biometrics, and Artificial Intelligence, it is becoming increasingly difficult for individuals to fully comprehend, let alone control, how and for what purposes organizations collect, use, and disclose their personal information. Consumers are growing increasingly concerned about their privacy, making the need for strong privacy champions ever more acute.

Название: Top 10 Challenges of Big Data Analytics
Автор: Maria Jose Sousa, Manuel Au-yong Oliveira
Издательство: Nova Science Publishers, Inc.
Год: 2021
Страниц: 217
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

The application of Big Data analytics in all fields of research is a critical driver for the competitiveness of all countries in the modern world. Currently, governments and industry generate large amounts of data driven by record keeping, compliance, regulations, data privacy, and dynamic requirements, and thus there is a need to create better mechanisms to analyse data, and hence support organizational development, as well as providing aid to policymakers' decision-making processes. In this context, there are emerging disruptive opportunities because of Big dаta: new business models, and vertical industry segments will emerge through shared relationships with all the stakeholders, and Big Data analytics is a major asset to support these dynamic relationships. This book was developed with the objective of analysing some of those challenges while at the same time providing a perspective of the potential of Big Data analytics, and the importance that analytics have for managers and for policymakers, to help define new strategies and new public policies, respectively.

Название: Tools and toolsets for enterprise architecture: Support for design, discipline and decision-making
Автор: Tom Graves
Издательство: Leanpub
Год: 2022-12-19
Страниц: 466
Язык: английский
Формат: pdf (true), epub
Размер: 10.2 MB

This anthology from the Tetradian weblog explores a range of topics about the kind of toolsets that we need to support the work in enterprise-architectures and the like. Which is where we come back to the need for those core elements that I’ve been ranting about through all of these posts: - a common file-format, or common content-structure, to share information between tools; - a database-structure that can hold that content within some kind of database-technology, such that editors can work on it; - a common way to describe ‘editors’ (tools) that can act on that content, in whatever way we need; - software apps that can support the content, the editors and the underlying data-structures, across the whole of the device-ecosystem from hand-helds to virtual-reality ‘war-rooms’.

Название: More on practice for Enterprise Architecture: Roles, skills, engagement and problem-issues
Автор: Tom Graves
Издательство: Leanpub
Год: 2022-12-12
Страниц: 229
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB

This anthology from the Tetradian weblog explores more about real-world practice for enterprise-architecture and its related disciplines. In short, in most cases it seems that ‘architect’ means pretty much exactly the same as the old term ‘analyst/programmer’, except that these days said analyst/programmer is expected to know something about more than just the one application, and to have some idea of how to get the infernal things to actually communicate, in some fashion that doesn’t result in the outright demolition of all the data (the latter being a more frequent occurrence than the IT trade is generally willing to admit…).

Название: Computing from the Command Line: Linux command line tools and Shell Scripting for beginner to intermediate level users
Автор: Sundeep Agarwal
Издательство: Leanpub
Год: 2022-11-01
Страниц: 203
Язык: английский
Формат: pdf (true), mobi, epub
Размер: 10.2 MB

This ebook aims to teach Linux command line tools and Shell Scripting for beginner to intermediate level users. The main focus is towards managing your files and performing text processing tasks. Plenty of examples and exercises are provided to make it easier to understand a particular tool and its various features. This ebook aims to teach Linux command line tools and Shell Scripting for beginner to intermediate level users. The main focus is towards managing your files and performing text processing tasks. Plenty of examples are provided to make it easier to understand a particular tool and its various features. Exercises at the end of chapters will help you practice what you've learned and solutions are provided for reference.

Название: Data Cleaning: The Ultimate Practical Guide - From Dirty Data to Clean Data
Автор: Lee Baker
Издательство: Leanpub
Год: 2022-11-08
Язык: английский
Формат: pdf, mobi, epub + Extras
Размер: 10.2 MB

Data Cleaning: The Ultimate Practical Guide is a guide to understanding what dirty data is, and how it gets into your dataset. Data cleaning is the process of transforming dirty data into clean data. That is, identifying inaccurate, incomplete and inconsistent data to improve the quality of your dataset until it is clean enough to be stored (in a database) or to be analysed (in a spreadsheet or a stats program). The term ‘clean data’ refers to the correctness and validity of the data themselves, but not to how useful the data are to your study. This book will help you prevent most types of dirty data getting into your dataset, and clean out quickly and efficiently the remaining errors, so you can have clean, fit-for-purpose and analysis-ready data.

Название: Building an Azure DevOps Pipeline for Infrastructure
Автор: Adam Bertram
Издательство: Leanpub
Год: 2022-11-12
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

If you ever wanted to see what building an entire Azure DevOps pipeline is like, here’s your chance. This Project will start from scratch building an Azure VM via an Azure Resource Manager (ARM) template stored in a GitHub repository and upon any change, will deploy a new Azure VM, run all required tests and tear down any test infrastructure built. When you search online, you will find various blog posts, documentation, and tutorials on Azure DevOps. These items are valuable resources but rarely does one walk you through a real-world scenario. Many skim over the security aspect leaving passwords in clear text for simplicity or an end product that essentially does nothing. Let's change that. In this project, you'll learn from soup to nuts how to build a real Azure DevOps release pipeline that automates infrastructure. You'll learn to use Azure DevOps to build a continuous deployment pipeline to provision Azure virtual machines. By the end of this project, you will have a fully-functioning Azure pipeline.

Название: Big Data for Big Decisions: Building a Data-Driven Organization
Автор: Krishna Pera
Издательство: CRC Press
Год: 2023
Страниц: 266
Язык: английский
Формат: pdf (true)
Размер: 13.2 MB

Building a data-driven organization (DDO) is an enterprise-wide initiative that may consume and lock up resources for the long term. Understandably, any organization considering such an initiative would insist on a roadmap and business case to be prepared and evaluated prior to approval. This book presents a step-by-step methodology in order to create a roadmap and business case, and provides a narration of the constraints and experiences of managers who have attempted the setting up of DDOs. The emphasis is on the big decisions – the key decisions that influence 90% of business outcomes – starting from decision first and reengineering the data to the decisions process-chain and data governance, so as to ensure the right data are available at the right time, every time.