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| azure synapse analytics interview questions: C# Interview Guide Konstantin Semenenko, 2024-03-08 Catapult your C# journey with this guide to crafting standout resumes, mastering advanced concepts, and navigating job offers with real-world insights for unparalleled success in programming and interviews Key Features Acquire a strong foundation in syntax, data types, and object-oriented programming to code confidently Develop strategies for addressing behavioral questions, tackle technical challenges, and showcase your coding skills Augment your C# programming skills with valuable insights from industry experts Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIf you're gearing up for technical interviews by enhancing your programming skills and aiming for a successful career in C# programming and software development, the C# Interview Guide is your key to interview success. Designed to equip you with essential skills for excelling in technical interviews, this guide spans a broad spectrum, covering fundamental C# programming concepts to intricate technical details. As you progress, you'll develop proficiency in crafting compelling resumes, adeptly answering behavioral questions, and navigating the complexities of salary negotiations and job evaluations. What sets this book apart is its coverage, extending beyond technical know-how and incorporating real-world experiences and expert insights from industry professionals. This comprehensive approach, coupled with guidance on overcoming challenges, ranging from interview preparation to post-interview strategies, makes this guide an invaluable resource for those aspiring to advance in their C# programming careers. By the end of this guide, you’ll emerge with a solid understanding of C# programming, advanced technical interview skills, and the ability to apply industry best practices.What you will learn Craft compelling resumes and cover letters for impactful job applications Demonstrate proficiency in fundamental C# programming concepts and syntax Master advanced C# topics, including LINQ, asynchronous programming, and design patterns Implement best practices for writing clean, maintainable C# code Use popular C# development tools and frameworks, such as .NET and .NET Core Negotiate salary, evaluate job offers, and build a strong C# portfolio Apply soft skills for successful interactions in C# development roles Who this book is for This book is for individuals aspiring to pursue a career in C# programming or software development. Whether you are a beginner or experienced professional, this guide will enhance your technical interview skills and C# programming knowledge. |
| azure synapse analytics interview questions: Administering Relational Databases on Microsoft Azure Rajendra Gupta, Prashanth Jayaram, Ahmad Yaseen, 2021-03-10 This book is ideal for IT professionals who have some experience with SQL Server or Database but are looking for a rich hands-on resource with guidance to explore each of the Azure SQL administrator concepts and the solutions the cloud provider offers.The book is primarily designed for Cloud DBAs (with ample knowledge of SQL server) who are new to Azure and want to have a solid start and get an in-depth glimpse on advanced topics that will help them to solve day-to-day issues plus effectively support the Azure databases. Administering Relational Databases on Microsoft Azure takes readers through a complete tour of understanding fundamental Azure concepts, Azure SQL administration, Azure Management tools, and techniques. This book will give an edge over to clear DP 300 exam. Increasingly, we continue to flood with information about the importance of the cloud. Cloud computing is everywhere, but not everyone knows exactly what it is and where to get started.We try to focus more on Azure SQL and give you the foundational understanding of what the cloud really is and tell you how some of these cloud technologies can work for you, and direct you to improve your knowledge and get certified with hassle-free learning. If you find it is for you, you will pick up useful tricks and tips for making a move to the cloud as seamless as possible.It is never too late to turn the corner from On-premise DBA to Cloud DBA specialist. In most technical discussions, we see a vast gap in cloud adoption and the reality of absorption. There is always a need to learn the Next-Gen technology. In this book, you explore the importance of understanding and managing cloud databases and the skills you must build around the Cloud to face the cloud DBA certification. In addition, along the way, you will pick up great interesting insights, real-time scenarios and fundamentals, concepts of Cloud, cloud management tools, test cases, and several practice solutions. |
| azure synapse analytics interview questions: Azure Data Factory by Example Richard Swinbank, |
| azure synapse analytics interview questions: Azure Data Engineer Associate Certification Guide Newton Alex, 2022-02-28 Become well-versed with data engineering concepts and exam objectives to achieve Azure Data Engineer Associate certification Key Features Understand and apply data engineering concepts to real-world problems and prepare for the DP-203 certification exam Explore the various Azure services for building end-to-end data solutions Gain a solid understanding of building secure and sustainable data solutions using Azure services Book DescriptionAzure is one of the leading cloud providers in the world, providing numerous services for data hosting and data processing. Most of the companies today are either cloud-native or are migrating to the cloud much faster than ever. This has led to an explosion of data engineering jobs, with aspiring and experienced data engineers trying to outshine each other. Gaining the DP-203: Azure Data Engineer Associate certification is a sure-fire way of showing future employers that you have what it takes to become an Azure Data Engineer. This book will help you prepare for the DP-203 examination in a structured way, covering all the topics specified in the syllabus with detailed explanations and exam tips. The book starts by covering the fundamentals of Azure, and then takes the example of a hypothetical company and walks you through the various stages of building data engineering solutions. Throughout the chapters, you'll learn about the various Azure components involved in building the data systems and will explore them using a wide range of real-world use cases. Finally, you’ll work on sample questions and answers to familiarize yourself with the pattern of the exam. By the end of this Azure book, you'll have gained the confidence you need to pass the DP-203 exam with ease and land your dream job in data engineering.What you will learn Gain intermediate-level knowledge of Azure the data infrastructure Design and implement data lake solutions with batch and stream pipelines Identify the partition strategies available in Azure storage technologies Implement different table geometries in Azure Synapse Analytics Use the transformations available in T-SQL, Spark, and Azure Data Factory Use Azure Databricks or Synapse Spark to process data using Notebooks Design security using RBAC, ACL, encryption, data masking, and more Monitor and optimize data pipelines with debugging tips Who this book is for This book is for data engineers who want to take the DP-203: Azure Data Engineer Associate exam and are looking to gain in-depth knowledge of the Azure cloud stack. The book will also help engineers and product managers who are new to Azure or interviewing with companies working on Azure technologies, to get hands-on experience of Azure data technologies. A basic understanding of cloud technologies, extract, transform, and load (ETL), and databases will help you get the most out of this book. |
| azure synapse analytics interview questions: Microsoft Azure Security Center Yuri Diogenes, Tom Shinder, 2018-06-04 Discover high-value Azure security insights, tips, and operational optimizations This book presents comprehensive Azure Security Center techniques for safeguarding cloud and hybrid environments. Leading Microsoft security and cloud experts Yuri Diogenes and Dr. Thomas Shinder show how to apply Azure Security Center’s full spectrum of features and capabilities to address protection, detection, and response in key operational scenarios. You’ll learn how to secure any Azure workload, and optimize virtually all facets of modern security, from policies and identity to incident response and risk management. Whatever your role in Azure security, you’ll learn how to save hours, days, or even weeks by solving problems in most efficient, reliable ways possible. Two of Microsoft’s leading cloud security experts show how to: • Assess the impact of cloud and hybrid environments on security, compliance, operations, data protection, and risk management • Master a new security paradigm for a world without traditional perimeters • Gain visibility and control to secure compute, network, storage, and application workloads • Incorporate Azure Security Center into your security operations center • Integrate Azure Security Center with Azure AD Identity Protection Center and third-party solutions • Adapt Azure Security Center’s built-in policies and definitions for your organization • Perform security assessments and implement Azure Security Center recommendations • Use incident response features to detect, investigate, and address threats • Create high-fidelity fusion alerts to focus attention on your most urgent security issues • Implement application whitelisting and just-in-time VM access • Monitor user behavior and access, and investigate compromised or misused credentials • Customize and perform operating system security baseline assessments • Leverage integrated threat intelligence to identify known bad actors |
| azure synapse analytics interview questions: The Data Warehouse Toolkit Ralph Kimball, Margy Ross, 2011-08-08 This old edition was published in 2002. The current and final edition of this book is The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling, 3rd Edition which was published in 2013 under ISBN: 9781118530801. The authors begin with fundamental design recommendations and gradually progress step-by-step through increasingly complex scenarios. Clear-cut guidelines for designing dimensional models are illustrated using real-world data warehouse case studies drawn from a variety of business application areas and industries, including: Retail sales and e-commerce Inventory management Procurement Order management Customer relationship management (CRM) Human resources management Accounting Financial services Telecommunications and utilities Education Transportation Health care and insurance By the end of the book, you will have mastered the full range of powerful techniques for designing dimensional databases that are easy to understand and provide fast query response. You will also learn how to create an architected framework that integrates the distributed data warehouse using standardized dimensions and facts. |
| azure synapse analytics interview questions: Trustworthy Online Controlled Experiments Ron Kohavi, Diane Tang, Ya Xu, 2020-04-02 Getting numbers is easy; getting numbers you can trust is hard. This practical guide by experimentation leaders at Google, LinkedIn, and Microsoft will teach you how to accelerate innovation using trustworthy online controlled experiments, or A/B tests. Based on practical experiences at companies that each run more than 20,000 controlled experiments a year, the authors share examples, pitfalls, and advice for students and industry professionals getting started with experiments, plus deeper dives into advanced topics for practitioners who want to improve the way they make data-driven decisions. Learn how to • Use the scientific method to evaluate hypotheses using controlled experiments • Define key metrics and ideally an Overall Evaluation Criterion • Test for trustworthiness of the results and alert experimenters to violated assumptions • Build a scalable platform that lowers the marginal cost of experiments close to zero • Avoid pitfalls like carryover effects and Twyman's law • Understand how statistical issues play out in practice. |
| azure synapse analytics interview questions: Design Patterns and Best Practices in Java Kamalmeet Singh, Adrian Ianculescu, Lucian-Paul Torje, 2018-06-27 Create various design patterns to master the art of solving problems using Java Key Features This book demonstrates the shift from OOP to functional programming and covers reactive and functional patterns in a clear and step-by-step manner All the design patterns come with a practical use case as part of the explanation, which will improve your productivity Tackle all kinds of performance-related issues and streamline your development Book Description Having a knowledge of design patterns enables you, as a developer, to improve your code base, promote code reuse, and make the architecture more robust. As languages evolve, new features take time to fully understand before they are adopted en masse. The mission of this book is to ease the adoption of the latest trends and provide good practices for programmers. We focus on showing you the practical aspects of smarter coding in Java. We'll start off by going over object-oriented (OOP) and functional programming (FP) paradigms, moving on to describe the most frequently used design patterns in their classical format and explain how Java’s functional programming features are changing them. You will learn to enhance implementations by mixing OOP and FP, and finally get to know about the reactive programming model, where FP and OOP are used in conjunction with a view to writing better code. Gradually, the book will show you the latest trends in architecture, moving from MVC to microservices and serverless architecture. We will finish off by highlighting the new Java features and best practices. By the end of the book, you will be able to efficiently address common problems faced while developing applications and be comfortable working on scalable and maintainable projects of any size. What you will learn Understand the OOP and FP paradigms Explore the traditional Java design patterns Get to know the new functional features of Java See how design patterns are changed and affected by the new features Discover what reactive programming is and why is it the natural augmentation of FP Work with reactive design patterns and find the best ways to solve common problems using them See the latest trends in architecture and the shift from MVC to serverless applications Use best practices when working with the new features Who this book is for This book is for those who are familiar with Java development and want to be in the driver’s seat when it comes to modern development techniques. Basic OOP Java programming experience and elementary familiarity with Java is expected. |
| azure synapse analytics interview questions: MapReduce Design Patterns Donald Miner, Adam Shook, 2012-11-21 Until now, design patterns for the MapReduce framework have been scattered among various research papers, blogs, and books. This handy guide brings together a unique collection of valuable MapReduce patterns that will save you time and effort regardless of the domain, language, or development framework you’re using. Each pattern is explained in context, with pitfalls and caveats clearly identified to help you avoid common design mistakes when modeling your big data architecture. This book also provides a complete overview of MapReduce that explains its origins and implementations, and why design patterns are so important. All code examples are written for Hadoop. Summarization patterns: get a top-level view by summarizing and grouping data Filtering patterns: view data subsets such as records generated from one user Data organization patterns: reorganize data to work with other systems, or to make MapReduce analysis easier Join patterns: analyze different datasets together to discover interesting relationships Metapatterns: piece together several patterns to solve multi-stage problems, or to perform several analytics in the same job Input and output patterns: customize the way you use Hadoop to load or store data A clear exposition of MapReduce programs for common data processing patterns—this book is indespensible for anyone using Hadoop. --Tom White, author of Hadoop: The Definitive Guide |
| azure synapse analytics interview questions: Azure Serverless Computing Cookbook Praveen Kumar Sreeram, 2020-06-19 Discover recipes for implementing solutions to real-world business problems through serverless applications Key FeaturesTest, troubleshoot, and monitor Azure functions to deliver high-quality and reliable cloud-centric applicationsUnderstand Visual Studio's integrated developer experience for Azure functionsExplore best practices for organizing and refactoring code within the Azure functionsBook Description This third edition of Azure Serverless Computing Cookbook guides you through the development of a basic back-end web API that performs simple operations, helping you understand how to persist data in Azure Storage services. You'll cover the integration of Azure Functions with other cloud services, such as notifications (SendGrid and Twilio), Cognitive Services (computer vision), and Logic Apps, to build simple workflow-based applications. With the help of this book, you'll be able to leverage Visual Studio tools to develop, build, test, and deploy Azure functions quickly. It also covers a variety of tools and methods for testing the functionality of Azure functions locally in the developer's workstation and in the cloud environment. Once you're familiar with the core features, you'll explore advanced concepts such as durable functions, starting with a hello world example, and learn about the scalable bulk upload use case, which uses durable function patterns, function chaining, and fan-out/fan-in. By the end of this Azure book, you'll have gained the knowledge and practical experience needed to be able to create and deploy Azure applications on serverless architectures efficiently. What you will learnImplement continuous integration and continuous deployment (CI/CD) of Azure functionsDevelop different event-based handlers in a serverless architectureIntegrate Azure functions with different Azure services to develop enterprise-level applicationsAccelerate your cloud application development using Azure function triggers and bindingsAutomate mundane tasks at various levels, from development to deployment and maintenanceDevelop stateful serverless applications and self-healing jobs using durable functions Who this book is for If you are a cloud developer or architect who wants to build cloud-native systems and deploy serverless applications with Azure functions, this book is for you. Prior experience with Microsoft Azure core services will help you to make the most out of this book. |
| azure synapse analytics interview questions: Mastering Cloud Computing Rajkumar Buyya, Christian Vecchiola, S.Thamarai Selvi, 2013-04-05 Mastering Cloud Computing is designed for undergraduate students learning to develop cloud computing applications. Tomorrow's applications won't live on a single computer but will be deployed from and reside on a virtual server, accessible anywhere, any time. Tomorrow's application developers need to understand the requirements of building apps for these virtual systems, including concurrent programming, high-performance computing, and data-intensive systems. The book introduces the principles of distributed and parallel computing underlying cloud architectures and specifically focuses on virtualization, thread programming, task programming, and map-reduce programming. There are examples demonstrating all of these and more, with exercises and labs throughout. - Explains how to make design choices and tradeoffs to consider when building applications to run in a virtual cloud environment - Real-world case studies include scientific, business, and energy-efficiency considerations |
| azure synapse analytics interview questions: Professional Azure SQL Managed Database Administration Ahmad Osama, Shashikant Shakya, 2021-03-08 Master data management by effectively utilizing the features of Azure SQL database. Key FeaturesLearn to automate common management tasks with PowerShell.Understand different methods to generate elastic pools and shards to scale Azure SQL databases.Learn to develop a scalable cloud solution through over 40 practical activities and exercises.Book Description Despite being the cloud version of SQL Server, Azure SQL Database and Azure SQL Managed Instance stands out in various aspects when it comes to management, maintenance, and administration. Updated with the latest Azure features, Professional Azure SQL Managed Database Administration continues to be a comprehensive guide for becoming proficient in data management. The book begins by introducing you to the Azure SQL managed databases (Azure SQL Database and Azure SQL Managed Instance), explaining their architecture, and how they differ from an on-premises SQL server. You will then learn how to perform common tasks, such as migrating, backing up, and restoring a SQL Server database to an Azure database. As you progress, you will study how you can save costs and manage and scale multiple SQL databases using elastic pools. You will also implement a disaster recovery solution using standard and active geo-replication. Finally, you will explore the monitoring and tuning of databases, the key features of databases, and the phenomenon of app modernization. By the end of this book, you will have mastered the key aspects of an Azure SQL database and Azure SQL managed instance, including migration, backup restorations, performance optimization, high availability, and disaster recovery. What you will learnUnderstanding Azure SQL database configuration and pricing optionsProvisioning a new SQL database or migrating an existing on-premises SQL Server database to an Azure SQL databaseBacking up and restoring an Azure SQL databaseSecuring and scaling an Azure SQL databaseMonitoring and tuning an Azure SQL databaseImplementing high availability and disaster recovery with an Azure SQL databaseManaging, maintaining, and securing managed instancesWho this book is for This book is designed to benefit database administrators, database developers, or application developers who are interested in developing new applications or migrating existing ones with Azure SQL database. Prior experience of working with an on-premise SQL Server or Azure SQL database along with a basic understanding of PowerShell scripts and C# code is necessary to grasp the concepts covered in this book. |
| azure synapse analytics interview questions: Probability for Statistics and Machine Learning Anirban DasGupta, 2011-05-17 This book provides a versatile and lucid treatment of classic as well as modern probability theory, while integrating them with core topics in statistical theory and also some key tools in machine learning. It is written in an extremely accessible style, with elaborate motivating discussions and numerous worked out examples and exercises. The book has 20 chapters on a wide range of topics, 423 worked out examples, and 808 exercises. It is unique in its unification of probability and statistics, its coverage and its superb exercise sets, detailed bibliography, and in its substantive treatment of many topics of current importance. This book can be used as a text for a year long graduate course in statistics, computer science, or mathematics, for self-study, and as an invaluable research reference on probabiliity and its applications. Particularly worth mentioning are the treatments of distribution theory, asymptotics, simulation and Markov Chain Monte Carlo, Markov chains and martingales, Gaussian processes, VC theory, probability metrics, large deviations, bootstrap, the EM algorithm, confidence intervals, maximum likelihood and Bayes estimates, exponential families, kernels, and Hilbert spaces, and a self contained complete review of univariate probability. |
| azure synapse analytics interview questions: Exam Ref 70-761 Querying Data with Transact-SQL Itzik Ben-Gan, 2017-04-04 Prepare for Microsoft Exam 70-761–and help demonstrate your real-world mastery of SQL Server 2016 Transact-SQL data management, queries, and database programming. Designed for experienced IT professionals ready to advance their status, Exam Ref focuses on the critical-thinking and decision-making acumen needed for success at the MCSA level. Focus on the expertise measured by these objectives: • Filter, sort, join, aggregate, and modify data • Use subqueries, table expressions, grouping sets, and pivoting • Query temporal and non-relational data, and output XML or JSON • Create views, user-defined functions, and stored procedures • Implement error handling, transactions, data types, and nulls This Microsoft Exam Ref: • Organizes its coverage by exam objectives • Features strategic, what-if scenarios to challenge you • Assumes you have experience working with SQL Server as a database administrator, system engineer, or developer • Includes downloadable sample database and code for SQL Server 2016 SP1 (or later) and Azure SQL Database Querying Data with Transact-SQL About the Exam Exam 70-761 focuses on the skills and knowledge necessary to manage and query data and to program databases with Transact-SQL in SQL Server 2016. About Microsoft Certification Passing this exam earns you credit toward a Microsoft Certified Solutions Associate (MCSA) certification that demonstrates your mastery of essential skills for building and implementing on-premises and cloud-based databases across organizations. Exam 70-762 (Developing SQL Databases) is also required for MCSA: SQL 2016 Database Development certification. See full details at: microsoft.com/learning |
| azure synapse analytics interview questions: The Future of Finance Henri Arslanian, Fabrice Fischer, 2019-07-15 This book, written jointly by an engineer and artificial intelligence expert along with a lawyer and banker, is a glimpse on what the future of the financial services will look like and the impact it will have on society. The first half of the book provides a detailed yet easy to understand educational and technical overview of FinTech, artificial intelligence and cryptocurrencies including the existing industry pain points and the new technological enablers. The second half provides a practical, concise and engaging overview of their latest trends and their impact on the future of the financial services industry including numerous use cases and practical examples. The book is a must read for any professional currently working in finance, any student studying the topic or anyone curious on how the future of finance will look like. |
| azure synapse analytics interview questions: Cloud Computing Basics Simplilearn, 2020-12-14 In recent times, the popularity of cloud computing has increased for businesses due to several reasons, such as cost savings, increased productivity, the enhanced speed with better efficiency, performance, as well as security. Along with Amazon Web Services (AWS), Salesforce’s CRM system and Microsoft Azure are also popular public cloud offerings. And due to the cloud’s increasing popularity, companies all around the world are in search of more cloud computing experts, as more organizations are now switching from the classical server infrastructure to cloud solutions to implement critical applications. With three business models: Platform as a Service (PaaS), software as a Service (SaaS), and Infrastructure as a Service (IaaS), it is likely that in the future, the system and network administrator jobs will be replaced if you are not updated with your skills. Cloud computing is helping businesses automate and configure their systems, as many are now transforming their onsite data center to clouds. Hence, there will be a huge demand for experts configuring Cloud Computing Infrastructure and APIs into their applications and storage. This cloud computing guide aims to help readers understand everything about cloud computing, from basic concepts to terminologies, various cloud tools and services, and also ways to build and scale up your cloud career. |
| azure synapse analytics interview questions: Logistics 4.0 Turan Paksoy, Cigdem Gonul Kochan, Sadia Samar Ali, 2020-12-17 Industrial revolutions have impacted both, manufacturing and service. From the steam engine to digital automated production, the industrial revolutions have conduced significant changes in operations and supply chain management (SCM) processes. Swift changes in manufacturing and service systems have led to phenomenal improvements in productivity. The fast-paced environment brings new challenges and opportunities for the companies that are associated with the adaptation to the new concepts such as Internet of Things (IoT) and Cyber Physical Systems, artificial intelligence (AI), robotics, cyber security, data analytics, block chain and cloud technology. These emerging technologies facilitated and expedited the birth of Logistics 4.0. Industrial Revolution 4.0 initiatives in SCM has attracted stakeholders’ attentions due to it is ability to empower using a set of technologies together that helps to execute more efficient production and distribution systems. This initiative has been called Logistics 4.0 of the fourth Industrial Revolution in SCM due to its high potential. Connecting entities, machines, physical items and enterprise resources to each other by using sensors, devices and the internet along the supply chains are the main attributes of Logistics 4.0. IoT enables customers to make more suitable and valuable decisions due to the data-driven structure of the Industry 4.0 paradigm. Besides that, the system’s ability of gathering and analyzing information about the environment at any given time and adapting itself to the rapid changes add significant value to the SCM processes. In this peer-reviewed book, experts from all over the world, in the field present a conceptual framework for Logistics 4.0 and provide examples for usage of Industry 4.0 tools in SCM. This book is a work that will be beneficial for both practitioners and students and academicians, as it covers the theoretical framework, on the one hand, and includes examples of practice and real world. |
| azure synapse analytics interview questions: Learning SQL Alan Beaulieu, 2009-04-11 Updated for the latest database management systems -- including MySQL 6.0, Oracle 11g, and Microsoft's SQL Server 2008 -- this introductory guide will get you up and running with SQL quickly. Whether you need to write database applications, perform administrative tasks, or generate reports, Learning SQL, Second Edition, will help you easily master all the SQL fundamentals. Each chapter presents a self-contained lesson on a key SQL concept or technique, with numerous illustrations and annotated examples. Exercises at the end of each chapter let you practice the skills you learn. With this book, you will: Move quickly through SQL basics and learn several advanced features Use SQL data statements to generate, manipulate, and retrieve data Create database objects, such as tables, indexes, and constraints, using SQL schema statements Learn how data sets interact with queries, and understand the importance of subqueries Convert and manipulate data with SQL's built-in functions, and use conditional logic in data statements Knowledge of SQL is a must for interacting with data. With Learning SQL, you'll quickly learn how to put the power and flexibility of this language to work. |
| azure synapse analytics interview questions: Artificial Intelligence with Python Prateek Joshi, 2017-01-27 Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application. |
| azure synapse analytics interview questions: Building a Scalable Data Warehouse with Data Vault 2.0 Daniel Linstedt, Michael Olschimke, 2015-09-15 The Data Vault was invented by Dan Linstedt at the U.S. Department of Defense, and the standard has been successfully applied to data warehousing projects at organizations of different sizes, from small to large-size corporations. Due to its simplified design, which is adapted from nature, the Data Vault 2.0 standard helps prevent typical data warehousing failures. Building a Scalable Data Warehouse covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss: - How to load each layer using SQL Server Integration Services (SSIS), including automation of the Data Vault loading processes. - Important data warehouse technologies and practices. - Data Quality Services (DQS) and Master Data Services (MDS) in the context of the Data Vault architecture. - Provides a complete introduction to data warehousing, applications, and the business context so readers can get-up and running fast - Explains theoretical concepts and provides hands-on instruction on how to build and implement a data warehouse - Demystifies data vault modeling with beginning, intermediate, and advanced techniques - Discusses the advantages of the data vault approach over other techniques, also including the latest updates to Data Vault 2.0 and multiple improvements to Data Vault 1.0 |
| azure synapse analytics interview questions: Great Business Teams Howard M. Guttman, 2008-06-16 Understand and decode the inner workings of great business teams with the more than 30 in-depth examples in Great Business Teams: Cracking the Code for Standout Performance. Author Howard Guttman examines and dissects teams at top-management, business-unit, and functional levels and isolates five key factors that drive team performance to offer you insight into the ways these teams achieve success. Using this book, go directly to the marketplace to scrutinize teams in a variety of industries, evaluating the challenges they face and the methods they choose to manage these challenges. |
| azure synapse analytics interview questions: The Oxford Handbook of Spontaneous Thought Kieran C.R. Fox, Kalina Christoff, 2018-05-16 Where do spontaneous thoughts come from? It may be surprising that the seemingly straightforward answers from the mind or from the brain are in fact an incredibly recent understanding of the origins of spontaneous thought. For nearly all of human history, our thoughts - especially the most sudden, insightful, and important - were almost universally ascribed to divine or other external sources. Only in the past few centuries have we truly taken responsibility for their own mental content, and finally localized thought to the central nervous system - laying the foundations for a protoscience of spontaneous thought. But enormous questions still loom: what, exactly, is spontaneous thought? Why does our brain engage in spontaneous forms of thinking, and when is this most likely to occur? And perhaps the question most interesting and accessible from a scientific perspective: how does the brain generate and evaluate its own spontaneous creations? Spontaneous thought includes our daytime fantasies and mind-wandering; the flashes of insight and inspiration familiar to the artist, scientist, and inventor; and the nighttime visions we call dreams. This Handbook brings together views from neuroscience, psychology, philosophy, phenomenology, history, education, contemplative traditions, and clinical practice to begin to address the ubiquitous but poorly understood mental phenomena that we collectively call 'spontaneous thought.' In studying such an abstruse and seemingly impractical subject, we should remember that our capacity for spontaneity, originality, and creativity defines us as a species - and as individuals. Spontaneous forms of thought enable us to transcend not only the here and now of perceptual experience, but also the bonds of our deliberately-controlled and goal-directed cognition; they allow the space for us to be other than who we are, and for our minds to think beyond the limitations of our current viewpoints and beliefs. |
| azure synapse analytics interview questions: Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data Paul Zikopoulos, Chris Eaton, 2011-10-22 Big Data represents a new era in data exploration and utilization, and IBM is uniquely positioned to help clients navigate this transformation. This book reveals how IBM is leveraging open source Big Data technology, infused with IBM technologies, to deliver a robust, secure, highly available, enterprise-class Big Data platform. The three defining characteristics of Big Data--volume, variety, and velocity--are discussed. You'll get a primer on Hadoop and how IBM is hardening it for the enterprise, and learn when to leverage IBM InfoSphere BigInsights (Big Data at rest) and IBM InfoSphere Streams (Big Data in motion) technologies. Industry use cases are also included in this practical guide. Learn how IBM hardens Hadoop for enterprise-class scalability and reliability Gain insight into IBM's unique in-motion and at-rest Big Data analytics platform Learn tips and tricks for Big Data use cases and solutions Get a quick Hadoop primer |
| azure synapse analytics interview questions: Azure SQL Revealed Bob Ward, 2020-10-30 Access detailed content and examples on Azure SQL, a set of cloud services that allows for SQL Server to be deployed in the cloud. This book teaches the fundamentals of deployment, configuration, security, performance, and availability of Azure SQL from the perspective of these same tasks and capabilities in SQL Server. This distinct approach makes this book an ideal learning platform for readers familiar with SQL Server on-premises who want to migrate their skills toward providing cloud solutions to an enterprise market that is increasingly cloud-focused. If you know SQL Server, you will love this book. You will be able to take your existing knowledge of SQL Server and translate that knowledge into the world of cloud services from the Microsoft Azure platform, and in particular into Azure SQL. This book provides information never seen before about the history and architecture of Azure SQL. Author Bob Ward is a leading expert with access to and support from the Microsoft engineering team that built Azure SQL and related database cloud services. He presents powerful, behind-the-scenes insights into the workings of one of the most popular database cloud services in the industry. What You Will LearnKnow the history of Azure SQLDeploy, configure, and connect to Azure SQLChoose the correct way to deploy SQL Server in AzureMigrate existing SQL Server instances to Azure SQLMonitor and tune Azure SQL’s performance to meet your needsEnsure your data and application are highly availableSecure your data from attack and theft Who This Book Is For This book is designed to teach SQL Server in the Azure cloud to the SQL Server professional. Anyone who operates, manages, or develops applications for SQL Server will benefit from this book. Readers will be able to translate their current knowledge of SQL Server—especially of SQL Server 2019—directly to Azure. This book is ideal for database professionals looking to remain relevant as their customer base moves into the cloud. |
| azure synapse analytics interview questions: BigQuery for Data Warehousing Mark Mucchetti, 2020-12-20 Create a data warehouse, complete with reporting and dashboards using Google’s BigQuery technology. This book takes you from the basic concepts of data warehousing through the design, build, load, and maintenance phases. You will build capabilities to capture data from the operational environment, and then mine and analyze that data for insight into making your business more successful. You will gain practical knowledge about how to use BigQuery to solve data challenges in your organization. BigQuery is a managed cloud platform from Google that provides enterprise data warehousing and reporting capabilities. Part I of this book shows you how to design and provision a data warehouse in the BigQuery platform. Part II teaches you how to load and stream your operational data into the warehouse to make it ready for analysis and reporting. Parts III and IV cover querying and maintaining, helping you keep your information relevant with other Google Cloud Platform services and advanced BigQuery. Part V takes reporting to the next level by showing you how to create dashboards to provide at-a-glance visual representations of your business situation. Part VI provides an introduction to data science with BigQuery, covering machine learning and Jupyter notebooks. What You Will Learn Design a data warehouse for your project or organization Load data from a variety of external and internal sources Integrate other Google Cloud Platform services for more complex workflows Maintain and scale your data warehouse as your organization grows Analyze, report, and create dashboards on the information in the warehouse Become familiar with machine learning techniques using BigQuery ML Who This Book Is For Developers who want to provide business users with fast, reliable, and insightful analysis from operational data, and data analysts interested in a cloud-based solution that avoids the pain of provisioning their own servers. |
| azure synapse analytics interview questions: Business Intelligence Demystified Anoop Kumar V K, 2021-09-25 Clear your doubts about Business Intelligence and start your new journey KEY FEATURES ● Includes successful methods and innovative ideas to achieve success with BI. ● Vendor-neutral, unbiased, and based on experience. ● Highlights practical challenges in BI journeys. ● Covers financial aspects along with technical aspects. ● Showcases multiple BI organization models and the structure of BI teams. DESCRIPTION The book demystifies misconceptions and misinformation about BI. It provides clarity to almost everything related to BI in a simplified and unbiased way. It covers topics right from the definition of BI, terms used in the BI definition, coinage of BI, details of the different main uses of BI, processes that support the main uses, side benefits, and the level of importance of BI, various types of BI based on various parameters, main phases in the BI journey and the challenges faced in each of the phases in the BI journey. It clarifies myths about self-service BI and real-time BI. The book covers the structure of a typical internal BI team, BI organizational models, and the main roles in BI. It also clarifies the doubts around roles in BI. It explores the different components that add to the cost of BI and explains how to calculate the total cost of the ownership of BI and ROI for BI. It covers several ideas, including unconventional ideas to achieve BI success and also learn about IBI. It explains the different types of BI architectures, commonly used technologies, tools, and concepts in BI and provides clarity about the boundary of BI w.r.t technologies, tools, and concepts. The book helps you lay a very strong foundation and provides the right perspective about BI. It enables you to start or restart your journey with BI. WHAT YOU WILL LEARN ● Builds a strong conceptual foundation in BI. ● Gives the right perspective and clarity on BI uses, challenges, and architectures. ● Enables you to make the right decisions on the BI structure, organization model, and budget. ● Explains which type of BI solution is required for your business. ● Applies successful BI ideas. WHO THIS BOOK IS FOR This book is a must-read for business managers, BI aspirants, CxOs, and all those who want to drive the business value with data-driven insights. TABLE OF CONTENTS 1. What is Business Intelligence? 2. Why do Businesses need BI? 3. Types of Business Intelligence 4. Challenges in Business Intelligence 5. Roles in Business Intelligence 6. Financials of Business Intelligence 7. Ideas for Success with BI 8. Introduction to IBI 9. BI Architectures 10. Demystify Tech, Tools, and Concepts in BI |
| azure synapse analytics interview questions: NoSQL Data Models Olivier Pivert, 2018-07-27 The topic of NoSQL databases has recently emerged, to face the Big Data challenge, namely the ever increasing volume of data to be handled. It is now recognized that relational databases are not appropriate in this context, implying that new database models and techniques are needed. This book presents recent research works, covering the following basic aspects: semantic data management, graph databases, and big data management in cloud environments. The chapters in this book report on research about the evolution of basic concepts such as data models, query languages, and new challenges regarding implementation issues. |
| azure synapse analytics interview questions: Big Data Balamurugan Balusamy, Nandhini Abirami R, Seifedine Kadry, Amir H. Gandomi, 2021-03-15 Learn Big Data from the ground up with this complete and up-to-date resource from leaders in the field Big Data: Concepts, Technology, and Architecture delivers a comprehensive treatment of Big Data tools, terminology, and technology perfectly suited to a wide range of business professionals, academic researchers, and students. Beginning with a fulsome overview of what we mean when we say, “Big Data,” the book moves on to discuss every stage of the lifecycle of Big Data. You’ll learn about the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions like SQL, data processing, data analytics, machine learning, and data mining. You’ll also discover how specific technologies like Apache Hadoop, SQOOP, and Flume work. Big Data also covers the central topic of big data visualization with Tableau, and you’ll learn how to create scatter plots, histograms, bar, line, and pie charts with that software. Accessibly organized, Big Data includes illuminating case studies throughout the material, showing you how the included concepts have been applied in real-world settings. Some of those concepts include: The common challenges facing big data technology and technologists, like data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns Relational and non-relational databases, like RDBMS, NoSQL, and NewSQL databases Virtualizing Big Data through encapsulation, partitioning, and isolating, as well as big data server virtualization Apache software, including Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive The Big Data analytics lifecycle, including business case evaluation, data preparation, extraction, transformation, analysis, and visualization Perfect for data scientists, data engineers, and database managers, Big Data also belongs on the bookshelves of business intelligence analysts who are required to make decisions based on large volumes of information. Executives and managers who lead teams responsible for keeping or understanding large datasets will also benefit from this book. |
| azure synapse analytics interview questions: MBA Insider Al Dea, 2020-01-28 MBA Insider is a guide for helping prospective and current MBA students make the most of their MBA Experience. With expert guidance, best practices, and actionable recommendations, readers will walk away with the information they need to understand how to navigate their MBA experience and achieve their career goals faster. The book contains a detailed walk through of the key elements of the MBA experience, real first-person stories from 50+ MBA students and alum, and actionable recommendations on key topics ranging from academics, internship recruiting, career development, and student activities. |
| azure synapse analytics interview questions: Data Engineering with Python Paul Crickard, 2020-10-23 Build, monitor, and manage real-time data pipelines to create data engineering infrastructure efficiently using open-source Apache projects Key Features Become well-versed in data architectures, data preparation, and data optimization skills with the help of practical examples Design data models and learn how to extract, transform, and load (ETL) data using Python Schedule, automate, and monitor complex data pipelines in production Book DescriptionData engineering provides the foundation for data science and analytics, and forms an important part of all businesses. This book will help you to explore various tools and methods that are used for understanding the data engineering process using Python. The book will show you how to tackle challenges commonly faced in different aspects of data engineering. You’ll start with an introduction to the basics of data engineering, along with the technologies and frameworks required to build data pipelines to work with large datasets. You’ll learn how to transform and clean data and perform analytics to get the most out of your data. As you advance, you'll discover how to work with big data of varying complexity and production databases, and build data pipelines. Using real-world examples, you’ll build architectures on which you’ll learn how to deploy data pipelines. By the end of this Python book, you’ll have gained a clear understanding of data modeling techniques, and will be able to confidently build data engineering pipelines for tracking data, running quality checks, and making necessary changes in production.What you will learn Understand how data engineering supports data science workflows Discover how to extract data from files and databases and then clean, transform, and enrich it Configure processors for handling different file formats as well as both relational and NoSQL databases Find out how to implement a data pipeline and dashboard to visualize results Use staging and validation to check data before landing in the warehouse Build real-time pipelines with staging areas that perform validation and handle failures Get to grips with deploying pipelines in the production environment Who this book is for This book is for data analysts, ETL developers, and anyone looking to get started with or transition to the field of data engineering or refresh their knowledge of data engineering using Python. This book will also be useful for students planning to build a career in data engineering or IT professionals preparing for a transition. No previous knowledge of data engineering is required. |
| azure synapse analytics interview questions: Transformers for Natural Language Processing Denis Rothman, 2021-01-29 Publisher's Note: A new edition of this book is out now that includes working with GPT-3 and comparing the results with other models. It includes even more use cases, such as casual language analysis and computer vision tasks, as well as an introduction to OpenAI's Codex. Key FeaturesBuild and implement state-of-the-art language models, such as the original Transformer, BERT, T5, and GPT-2, using concepts that outperform classical deep learning modelsGo through hands-on applications in Python using Google Colaboratory Notebooks with nothing to install on a local machineTest transformer models on advanced use casesBook Description The transformer architecture has proved to be revolutionary in outperforming the classical RNN and CNN models in use today. With an apply-as-you-learn approach, Transformers for Natural Language Processing investigates in vast detail the deep learning for machine translations, speech-to-text, text-to-speech, language modeling, question answering, and many more NLP domains with transformers. The book takes you through NLP with Python and examines various eminent models and datasets within the transformer architecture created by pioneers such as Google, Facebook, Microsoft, OpenAI, and Hugging Face. The book trains you in three stages. The first stage introduces you to transformer architectures, starting with the original transformer, before moving on to RoBERTa, BERT, and DistilBERT models. You will discover training methods for smaller transformers that can outperform GPT-3 in some cases. In the second stage, you will apply transformers for Natural Language Understanding (NLU) and Natural Language Generation (NLG). Finally, the third stage will help you grasp advanced language understanding techniques such as optimizing social network datasets and fake news identification. By the end of this NLP book, you will understand transformers from a cognitive science perspective and be proficient in applying pretrained transformer models by tech giants to various datasets. What you will learnUse the latest pretrained transformer modelsGrasp the workings of the original Transformer, GPT-2, BERT, T5, and other transformer modelsCreate language understanding Python programs using concepts that outperform classical deep learning modelsUse a variety of NLP platforms, including Hugging Face, Trax, and AllenNLPApply Python, TensorFlow, and Keras programs to sentiment analysis, text summarization, speech recognition, machine translations, and moreMeasure the productivity of key transformers to define their scope, potential, and limits in productionWho this book is for Since the book does not teach basic programming, you must be familiar with neural networks, Python, PyTorch, and TensorFlow in order to learn their implementation with Transformers. Readers who can benefit the most from this book include experienced deep learning & NLP practitioners and data analysts & data scientists who want to process the increasing amounts of language-driven data. |
| azure synapse analytics interview questions: SQL the One Uday Arumilli, 2016-12-17 Congratulations! You are going to WIN your next SQL Server interview. “SQL The One” book can guide you to achieve the success in your next interview. This book covers Microsoft SQL Server interview experiences, questions and answers for a range of SQL DBA’s and SQL Server Professionals. All of these questions have been collected from the people who attended interviews at various multinational companies across the world. It also covers “How to prepare for a SQL DBA interview?” and “How to become an expert in your career?” Salient Features of Book All interview questions are asked in various MNC Covers 1090 real time questions and answers 254 questions on SQL Server Performance Tuning Covers all SQL Server HA & DR features 316 questions on SQL Server HA & DR features Lots of scenario based questions Covers SQL Server 2005, 2008, 2008 R2, 2012, 2014 and 2016 Questions are categorized In-depth explanations An Interview Experience with Microsoft Useful as a reference guide for SQL DBA Interview preparation |
| azure synapse analytics interview questions: Introduction to Data Science Rafael A. Irizarry, 2019-11-20 Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert. |
| azure synapse analytics interview questions: Microsoft Azure Architect Technologies and Design Complete Study Guide Benjamin Perkins, William Panek, 2021-01-13 Become a proficient Microsoft Azure solutions architect Azure certifications are critical to the millions of IT professionals Microsoft has certified as MCSE and MCSA in Windows Server in the last 20 years. All of these professionals need to certify in key Azure exams to stay current and advance in their careers. Exams AZ-303 and AZ-304 are the key solutions architect exams that experienced Windows professionals will find most useful at the intermediate and advanced points of their careers. Microsoft Azure Architect Technologies and Design Complete Study Guide Exams AZ-303 and AZ-304 covers the two critical Microsoft Azure exams that intermediate and advanced Microsoft IT professionals will need to show proficiency as their organizations move to the Azure cloud. Understand Azure Set up your Microsoft Cloud network Solve real-world problems Get the confidence to pass the exam By learning all of these things plus using the Study Guide review questions and practice exams, the reader will be ready to take the exam and perform the job with confidence. |
| azure synapse analytics interview questions: Implementing Power BI in the Enterprise Greg Low, 2021-06-09 Power BI is an amazing tool. It's so easy to get started with and to develop a proof of concept. Enterprises want more than that. They need to create analytics using professional techniques. In this unique book, Dr Greg Low shows you how he has implemented many successful Power BI implementations in enterprises. If you want a book on building better visualizations in Power BI, this is not the book for you. Instead, this book will teach you about architecture, identity and security, building a supporting data warehouse, using DevOps and project management tools, learning to use Azure Data Factory and source control with your projects. It also describes how he implements projects for clients with differing levels of cloud tolerance, from the cloud natives, to cloud friendlies, to cloud conservatives, and to those clients who are not cloud friendly at all. |
| azure synapse analytics interview questions: .Net Interview Questions Koirala, 2005-09-15 |
| azure synapse analytics interview questions: Pro Azure Governance and Security Peter De Tender, David Rendon, Samuel Erskine, 2019-06-19 Any IT professional can tell you that managing security is a top priority and even more so when working in the cloud. Access to accurate and timely security information is critical, but governance and control must first be enabled. This guide shows you how to take advantage of Azure's vast and powerful built-in security tools and capabilities for your application workloads. Pro Azure Governance and Security offers a comprehensive look at the governance features available with Microsoft Azure and demonstrates how to integrate them with your hybrid and Azure environments, drawing on the author's experiences from years in the field. Learn about the array of controls implemented within Microsoft Azure from two valuable perspectives: the customer and Microsoft operations. Beginning with the top-level subscription hierarchy, learn about the most important built-in Azure security services and features, as well as how to use Azure Policies and Blueprints as a means for security and governance. A series of hands-on exercises teaches you the concepts of Azure Governance: how to enable and deploy Azure Security Center, integrate RBAC (role-based access control), and set up Azure Operations and Monitoring. Get introduced to the new Azure Sentinel solution that offers SIEM as a service for security incident management and proactive hunting. What You'll Learn Understand different architectural designs for implementing Azure Security Operate and monitor an Azure environmentDeploy Azure Governance, Policies, and BlueprintsDiscover key Azure features that enhance securityImplement and confidently access Azure Security CenterGet to know Azure Sentinel Who This Book Is For Technical engineers, consultants, solution and cloud architects, IT managers, and SecOps teams who need to understand how to integrate governance, security, and compliance in hybrid and Azure environments. A basic understanding of Azure or other public cloud platforms is beneficial, but not required. |
| azure synapse analytics interview questions: The Disordered Mind Eric R. Kandel, 2018-08-28 A Nobel Prize–winning neuroscientist’s probing investigation of what brain disorders can tell us about human nature Eric R. Kandel, the winner of the Nobel Prize in Physiology or Medicine for his foundational research into memory storage in the brain, is one of the pioneers of modern brain science. His work continues to shape our understanding of how learning and memory work and to break down age-old barriers between the sciences and the arts. In his seminal new book, The Disordered Mind, Kandel draws on a lifetime of pathbreaking research and the work of many other leading neuroscientists to take us on an unusual tour of the brain. He confronts one of the most difficult questions we face: How does our mind, our individual sense of self, emerge from the physical matter of the brain? The brain’s 86 billion neurons communicate with one another through very precise connections. But sometimes those connections are disrupted. The brain processes that give rise to our mind can become disordered, resulting in diseases such as autism, depression, schizophrenia, Parkinson’s, addiction, and post-traumatic stress disorder. While these disruptions bring great suffering, they can also reveal the mysteries of how the brain produces our most fundamental experiences and capabilities—the very nature of what it means to be human. Studies of autism illuminate the neurological foundations of our social instincts; research into depression offers important insights on emotions and the integrity of the self; and paradigm-shifting work on addiction has led to a new understanding of the relationship between pleasure and willpower. By studying disruptions to typical brain functioning and exploring their potential treatments, we will deepen our understanding of thought, feeling, behavior, memory, and creativity. Only then can we grapple with the big question of how billions of neurons generate consciousness itself. |
| azure synapse analytics interview questions: Big Data Applications and Use Cases Patrick C. K. Hung, 2016-05-18 This book presents different use cases in big data applications and related practical experiences. Many businesses today are increasingly interested in utilizing big data technologies for supporting their business intelligence so that it is becoming more and more important to understand the various practical issues from different practical use cases. This book provides clear proof that big data technologies are playing an ever increasing important and critical role in a new cross-discipline research between computer science and business. |
| azure synapse analytics interview questions: Data Mining and Predictive Analytics Daniel T. Larose, 2015-02-19 Learn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis. The authors apply a unified “white box” approach to data mining methods and models. This approach is designed to walk readers through the operations and nuances of the various methods, using small data sets, so readers can gain an insight into the inner workings of the method under review. Chapters provide readers with hands-on analysis problems, representing an opportunity for readers to apply their newly-acquired data mining expertise to solving real problems using large, real-world data sets. Data Mining and Predictive Analytics: Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language Features over 750 chapter exercises, allowing readers to assess their understanding of the new material Provides a detailed case study that brings together the lessons learned in the book Includes access to the companion website, www.dataminingconsultant, with exclusive password-protected instructor content Data Mining and Predictive Analytics will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives. |
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