Data and Knowledge Engineering The Ultimate Step-By-Step Guide PDF Download

Author: Gerardus Blokdyk
Publisher:
ISBN: 9780655136460
Category :
Languages : en
Pages : 0

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Author: Gerardus Blokdyk
Publisher: 5starcooks
ISBN: 9780655186465
Category :
Languages : en
Pages : 128

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Book Description
Is Data & Knowledge Engineering Required? Risk factors: what are the characteristics of Data & Knowledge Engineering that make it risky? How do we measure improved Data & Knowledge Engineering service perception, and satisfaction? What will drive Data & Knowledge Engineering change? Is the Data & Knowledge Engineering scope manageable? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Data & Knowledge Engineering investments work better. This Data & Knowledge Engineering All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Data & Knowledge Engineering Self-Assessment. Featuring 702 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Data & Knowledge Engineering improvements can be made. In using the questions you will be better able to: - diagnose Data & Knowledge Engineering projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Data & Knowledge Engineering and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Data & Knowledge Engineering Scorecard, you will develop a clear picture of which Data & Knowledge Engineering areas need attention. Your purchase includes access details to the Data & Knowledge Engineering self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. Your exclusive instant access details can be found in your book.

Author: Gerardus Blokdyk
Publisher: 5starcooks
ISBN: 9781867301882
Category :
Languages : en
Pages : 308

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Book Description
What internal processes need improvement? Why do you expend time and effort to implement measurement, for whom? Do you monitor the Data and Knowledge Engineering decisions made and fine tune them as they evolve? Are there regulatory / compliance issues? Do you monitor the effectiveness of your Data and Knowledge Engineering activities? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Data And Knowledge Engineering investments work better. This Data And Knowledge Engineering All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Data And Knowledge Engineering Self-Assessment. Featuring 949 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Data And Knowledge Engineering improvements can be made. In using the questions you will be better able to: - diagnose Data And Knowledge Engineering projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Data And Knowledge Engineering and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Data And Knowledge Engineering Scorecard, you will develop a clear picture of which Data And Knowledge Engineering areas need attention. Your purchase includes access details to the Data And Knowledge Engineering self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Data And Knowledge Engineering Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Author: Gerard Blokdyk
Publisher: Createspace Independent Publishing Platform
ISBN: 9781720475231
Category :
Languages : en
Pages : 140

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Book Description
What will drive Data & Knowledge Engineering change? What are the long-term Data & Knowledge Engineering goals? Who is the Data & Knowledge Engineering process owner? Will Data & Knowledge Engineering deliverables need to be tested and, if so, by whom? What are the expected benefits of Data & Knowledge Engineering to the business? Defining, designing, creating, and implementing a process to solve a challenge or meet an objective is the most valuable role... In EVERY group, company, organization and department. Unless you are talking a one-time, single-use project, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' This Self-Assessment empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Data & Knowledge Engineering investments work better. This Data & Knowledge Engineering All-Inclusive Self-Assessment enables You to be that person. All the tools you need to an in-depth Data & Knowledge Engineering Self-Assessment. Featuring new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Data & Knowledge Engineering improvements can be made. In using the questions you will be better able to: - diagnose Data & Knowledge Engineering projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Data & Knowledge Engineering and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Data & Knowledge Engineering Scorecard, you will develop a clear picture of which Data & Knowledge Engineering areas need attention. Your purchase includes access details to the Data & Knowledge Engineering self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. Your exclusive instant access details can be found in your book.

Author: IEEE Computer Society
Publisher:
ISBN: 9780769551661
Category : Computer software
Languages : en
Pages : 348

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Book Description
In the Guide to the Software Engineering Body of Knowledge (SWEBOK(R) Guide), the IEEE Computer Society establishes a baseline for the body of knowledge for the field of software engineering, and the work supports the Society's responsibility to promote the advancement of both theory and practice in this field. It should be noted that the Guide does not purport to define the body of knowledge but rather to serve as a compendium and guide to the knowledge that has been developing and evolving over the past four decades. Now in Version 3.0, the Guide's 15 knowledge areas summarize generally accepted topics and list references for detailed information. The editors for Version 3.0 of the SWEBOK(R) Guide are Pierre Bourque (Ecole de technologie superieure (ETS), Universite du Quebec) and Richard E. (Dick) Fairley (Software and Systems Engineering Associates (S2EA)).

Author: Mayank Malhotra
Publisher: Orange Education Pvt Ltd
ISBN: 8196994788
Category : Computers
Languages : en
Pages : 280

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Book Description
Navigating Databricks with Ease for Unparalleled Data Engineering Insights. KEY FEATURES ● Navigate Databricks with a seamless progression from fundamental principles to advanced engineering techniques. ● Gain hands-on experience with real-world examples, ensuring immediate relevance and practicality. ● Discover expert insights and best practices for refining your data engineering skills and achieving superior results with Databricks. DESCRIPTION Ultimate Data Engineering with Databricks is a comprehensive handbook meticulously designed for professionals aiming to enhance their data engineering skills through Databricks. Bridging the gap between foundational and advanced knowledge, this book employs a step-by-step approach with detailed explanations suitable for beginners and experienced practitioners alike. Focused on practical applications, the book employs real-world examples and scenarios to teach how to construct, optimize, and maintain robust data pipelines. Emphasizing immediate applicability, it equips readers to address real data challenges using Databricks effectively. The goal is not just understanding Databricks but mastering it to offer tangible solutions. Beyond technical skills, the book imparts best practices and expert tips derived from industry experience, aiding readers in avoiding common pitfalls and adopting strategies for optimal data engineering solutions. This book will help you develop the skills needed to make impactful contributions to organizations, enhancing your value as data engineering professionals in today's competitive job market. WHAT WILL YOU LEARN ● Acquire proficiency in Databricks fundamentals, enabling the construction of efficient data pipelines. ● Design and implement high-performance data solutions for scalability. ● Apply essential best practices for ensuring data integrity in pipelines. ● Explore advanced Databricks features for tackling complex data tasks. ● Learn to optimize data pipelines for streamlined workflows. WHO IS THIS BOOK FOR? This book caters to a diverse audience, including data engineers, data architects, BI analysts, data scientists and technology enthusiasts. Suitable for both professionals and students, the book appeals to those eager to master Databricks and stay at the forefront of data engineering trends. A basic understanding of data engineering concepts and familiarity with cloud computing will enhance the learning experience. TABLE OF CONTENTS 1. Fundamentals of Data Engineering 2. Mastering Delta Tables in Databricks 3. Data Ingestion and Extraction 4. Data Transformation and ETL Processes 5. Data Quality and Validation 6. Data Modeling and Storage 7. Data Orchestration and Workflow Management 8. Performance Tuning and Optimization 9. Scalability and Deployment Considerations 10. Data Security and Governance Last Words Index

Author: Guus Schreiber
Publisher: MIT Press
ISBN: 9780262193009
Category : Business & Economics
Languages : en
Pages : 476

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Book Description
The disciplines of knowledge engineering and knowledge management are closely tied. Knowledge engineering deals with the development of information systems in which knowledge and reasoning play pivotal roles. Knowledge management, a newly developed field at the intersection of computer science and management, deals with knowledge as a key resource in modern organizations. Managing knowledge within an organization is inconceivable without the use of advanced information systems; the design and implementation of such systems pose great organization as well as technical challenges.

Author: Andrew Park
Publisher: Andrew Park
ISBN: 9781801779470
Category :
Languages : en
Pages : 100

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Book Description
★ 55% OFF for Bookstores! NOW at $ 33,97 instead of $ 43.97! ★ Are you interested in knowing more about the fascinating world of Data Science? Your Customers Will Love This Amazing Step-By-Step Guide! This book offers you the fundamental knowledge you need to get started, but keep in mind that no book or even teacher can do everything for you. You need to work hard by putting each building block in its place as you advance. Data Science is a massive field of study that requires years of learning and practice before you can master it. This shouldn't discourage you, however! Embrace it as a challenge that you can undertake in order to broaden your horizons and improve your knowledge of all that is Data Science and machine learning. Data Science is a highly complex topic that has continuously been developed for decades. It is constantly evolving, and it can be challenging to keep up with all the past, present, and future concepts. With that being said, this isn't supposed to discourage you from pursuing this field. To start out this guidebook, we are going to take a look at what Data Science is all about, why it is important, and why we would want to work with this process in the first place as well. We will then take some time in order to learn the lifecycle of Data Science, and how we need to go through a series of steps like the finding the right data, preparing the data, coming up with the right model, and more. All of this and more will be discussed in this guidebook so that you can go from start to finish with your own Data Science project. This is just the start of some of the amazing things that we are able to do when it is time to start on Data Science. We are able to spend our time looking at what machine learning is all about, the different types of machine learning, and how we are able to put it all together to makes sure that we can create the right algorithms and models when it is time to sort through our data and find the right patterns and insights in the process. In "The Essential Guide on Data Science" you will discover: What is Data Science? Why is Data Science So Important? The Benefits of Python Data Science The Lifecycle of Data Science The Importance of Visuals with Data Science A Look at Data Mining The Real-Life Applications of Data Science There are a lot of benefits that we are able to see when it comes to working on Data Science, and many companies in a lot of different industries are going to work with this in order to ensure that we will be able to handle how to work with their customers, how to beat out the competition, and so much more. When you are ready to work with the idea of Data Science, and you want to work with all of the different parts that are found with it, then make sure to check out this guidebook to help you get started. You can position yourself to use your deep knowledge and understanding of all the cutting-edge technologies obtained from this book to contribute to the growth of any company and land yourself a new high paying and rewarding job! Buy It NOW and Let Your Customers Get Addicted to This Amazing Book!

Author: Tobias Macey
Publisher: "O'Reilly Media, Inc."
ISBN: 1492062383
Category : Computers
Languages : en
Pages : 263

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Book Description
Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Contributors from notable companies including Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges. Edited by Tobias Macey, host of the popular Data Engineering Podcast, this book presents 97 concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data. Data engineers, data architects, data team managers, data scientists, machine learning engineers, and software engineers will greatly benefit from the wisdom and experience of their peers. Topics include: The Importance of Data Lineage - Julien Le Dem Data Security for Data Engineers - Katharine Jarmul The Two Types of Data Engineering and Data Engineers - Jesse Anderson Six Dimensions for Picking an Analytical Data Warehouse - Gleb Mezhanskiy The End of ETL as We Know It - Paul Singman Building a Career as a Data Engineer - Vijay Kiran Modern Metadata for the Modern Data Stack - Prukalpa Sankar Your Data Tests Failed! Now What? - Sam Bail

Author: Shitalkumar R Sukhdeve
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 304

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Book Description
Review: "I would recommend this book to all prospective data scientists - as well as those software professionals who choose to transfer or migrate to the domain of data science. It is a useful addition to the body of work already available to guide project managers of data science projects." Lt Col (Dr) Rajesh Kapur (Retd), AI Investor, Asst. Prof. TIMSCDR, Hyderabad, India "It's a masterpiece of work for the aspiring leaders of data science and AI. It's also a guide for executives and investors to get maximum value from their investment in AI. Beginners in data science can also get the most out of this book.", Jay Ojha, Business intelligence and analytics manager, HCL Infosystem LtdWhy should you read this book? 87% of data science project fails to make to production in enterprises. Only 50% is the data leadership success rate. Is it not surprising to know when data science and AI are in the top trend? If you are looking for a career in data science or looking for leadership, these insights may disturb you. Don't worry, "Step up for Leadership in Enterprise Data Science & Artificial Intelligence with Big Data." will -Burst the myths around data science, AI & big data-Presents the real business scenarios -Take you on the journey of data science, AI & big data even if you are an ultimate beginner.-Introduce you to the essential skills of success in this field -Develop a leadership mindset by cutting edge methodologies & strategies-Make you aware of technical trends around it-Develop technical skills with R, Python, Machine learning with big data as well as business skills-Reduce failure possibility and increase the chance of success by covering the 360 degrees view of the field. Each day counts. So as your steps. Step up immediately and begin your journey to your dreams of data science and AI.