Reporting with Microsoft SQL Server 2012. Learn to quickly create reports in SSRS and Power View as well as understand the best use of each reporting tool

James Serra, William Anton

Responsible AI in the Enterprise. Practical AI risk management for explainable, auditable, and safe models with hyperscalers and Azure OpenAI

Adnan Masood, Heather Dawe, Ed Price, Dr. Ehsan Adeli

Responsible AI in the Enterprise is a comprehensive guide to implementing ethical, transparent, and compliant AI systems in an organization. With a focus on understanding key concepts of machine learning models, this book equips you with techniques and algorithms to tackle complex issues such as bias, fairness, and model governance. Throughout the book, you’ll gain an understanding of FairLearn and InterpretML, along with Google What-If Tool, ML Fairness Gym, IBM AI 360 Fairness tool, and Aequitas. You’ll uncover various aspects of responsible AI, including model interpretability, monitoring and management of model drift, and compliance recommendations. You’ll gain practical insights into using AI governance tools to ensure fairness, bias mitigation, explainability, privacy compliance, and privacy in an enterprise setting. Additionally, you’ll explore interpretability toolkits and fairness measures offered by major cloud AI providers like IBM, Amazon, Google, and Microsoft, while discovering how to use FairLearn for fairness assessment and bias mitigation. You’ll also learn to build explainable models using global and local feature summary, local surrogate model, Shapley values, anchors, and counterfactual explanations.By the end of this book, you’ll be well-equipped with tools and techniques to create transparent and accountable machine learning models.

Ripple Quick Start Guide. Get started with XRP and develop applications on Ripple's blockchain

Febin John James

This book starts by giving you an understanding of the basics of blockchain and the Ripple protocol. You will then get some hands-on experience of working with XRP.You will learn how to set up a Ripple wallet and see how seamlessly you can transfer money abroad. You will learn about different types of wallets through which you can store and transact XRP, along with the security precautions you need to take to keep your money safe.Since Ripple is currency agnostic, it can enable the transfer of value in USD, EUR, and any other currency. You can even transfer digital assets using Ripple. You will see how you can pay an international merchant with their own native currency and how Ripple can exchange it on the ?y. Once you understand the applications of Ripple, you will learn how to create a conditionally-held escrow using the Ripple API, and how to send and cash checks.Finally, you will also understand the common misconceptions people have about Ripple and discover the potential risks you must consider before making investment decisions.By the end of this book, you will have a solid foundation for working with Ripple's blockchain. Using it, you will be able to solve problems caused by traditional systems in your respective industry.

Rola archiwów w procesie wdrażania systemów elektronicznego zarządzania dokumentacją. Z doświadczeń archiwów szkół wyższych, instytucji naukowych i kulturalnych oraz państwowych i samorządowych jednostek organizacyjnych

red. Antoni Barciak, Dorota Drzewiecka, Katarzyna Pepłowska

Książka omawia trudny proces jakim jest wdrażanie systemów EZD w działalności jednostek organizacyjnych w kontekście informatyzacji państwa.  W literaturze naukowej  coraz więcej miejsca poświęca się tematyce projektowania i wdrażania systemów do elektronicznego zarządzania dokumentacją. Niestety zbyt mało mówi się o udziale archiwistów, często można odnieść wrażanie, że są oni pomijani w tym ważnym procesie. Z drugiej strony, należy przypomnieć, że wiedza, którą dysponują archiwiści w wielu kwestiach związanych z zarządzaniem dokumentacją pozwoliłaby uniknąć licznych problemów występujących w praktyce. Niniejsza książka wypełnią tę lukę, bowiem koncentruje się na doświadczeniach archiwów i ich roli w procesie wdrażania EZD. Książka  jest  szerokim spojrzeniem na działalność archiwów. Jest adresowana archiwistom, pracownikom jednostek organizacyjnych, dysponentom oraz studentom. Zawiera w sobie praktyczne wyjaśnienie procesów wdrażania EZD dzięki czemu może stanowić cenne źródło wiedzy dla wszystkich, którzy obecnie zmagają z  problemem EZD.

Salesforce Data Architect Certification Guide. Comprehensive coverage of the Salesforce Data Architect exam content to help you pass on the first attempt

Aaron Allport

The Salesforce Data Architect is a prerequisite exam for the Application Architect half of the Salesforce Certified Technical Architect credential. This book offers complete, up-to-date coverage of the Salesforce Data Architect exam so you can take it with confidence.The book is written in a clear, succinct way with self-assessment and practice exam questions, covering all the topics necessary to help you pass the exam with ease. You’ll understand the theory around Salesforce data modeling, database design, master data management (MDM), Salesforce data management (SDM), and data governance. Additionally, performance considerations associated with large data volumes will be covered. You’ll also get to grips with data migration and understand the supporting theory needed to achieve Salesforce Data Architect certification.By the end of this Salesforce book, you'll have covered everything you need to know to pass the Salesforce Data Architect certification exam and have a handy, on-the-job desktop reference guide to re-visit the concepts.

Salesforce Platform App Builder Certification Handbook. A handy guide that covers the most essential topics for Salesforce Platform App Builder Certification in an easy-to-understand format

Siddhesh Kabe

The Salesforce Certified Platform App Builder exam is for individuals who want to demonstrate their skills and knowledge in designing, building, and implementing custom applications using the declarative customization capabilities of Force.com. This book will build a strong foundation in Force.com to prepare you for the platform app builder certification exam. It will guide you through designing the interface while introducing the Lightning Process Builder. Next, we will implement business logic using various point and click features of Force.com. We will learn to manage data and create reports and dashboards. We will then learn to administer the force.com application by configuring the object-level, field-level, and record-level security. By the end of this book, you will be completely equipped to take the Platform App Builder certification exam.

SAP Data Services 4.x Cookbook. Delve into the SAP Data Services environment to efficiently prepare, implement, and develop ETL processes

Ivan Shomnikov, Stanislav Pereyaslov

Want to cost effectively deliver trusted information to all of your crucial business functions? SAP Data Services delivers one enterprise-class solution for data integration, data quality, data profiling, and text data processing. It boosts productivity with a single solution for data quality and data integration. SAP Data Services also enables you to move, improve, govern, and unlock big data. This book will lead you through the SAP Data Services environment to efficiently develop ETL processes. To begin with, you’ll learn to install, configure, and prepare the ETL development environment. You will get familiarized with the concepts of developing ETL processes with SAP Data Services. Starting from smallest unit of work- the data flow, the chapters will lead you to the highest organizational unit—the Data Services job, revealing the advanced techniques of ETL design. You will learn to import XML files by creating and implementing real-time jobs. It will then guide you through the ETL development patterns that enable the most effective performance when extracting, transforming, and loading data. You will also find out how to create validation functions and transforms.Finally, the book will show you the benefits of data quality management with the help of another SAP solution—Information Steward.

SAP NetWeaver MDM 7.1 Administrator's Guide

Uday Rao

Scala: Applied Machine Learning. Master the art of Machine Learning in Scala

Patrick R. Nicolas, Alex Kozlov, Pascal Bugnion

This Learning Path aims to put the entire world of machine learning with Scala in front of you. Scala for Data Science, the first module in this course, is a tutorial guide that provides tutorials on some of the most common Scala libraries for data science, allowing you to quickly get up to speed building data science and data engineering solutions.The second course, Scala for Machine Learning guides you through the process of building AI applications with diagrams, formal mathematical notation, source code snippets, and useful tips. A review of the Akka framework and Apache Spark clusters concludes the tutorial.The next module, Mastering Scala Machine Learning, is the final step in this course. It will take your knowledge to next level and help you use the knowledge to build advanced applications such as social media mining, intelligent news portals, and more. After a quick refresher on functional programming concepts using REPL, you will see some practical examples of setting up the development environment and tinkering with data. We will then explore working with Spark and MLlib using k-means and decision trees.By the end of this course, you will be a master at Scala machine learning and have enough expertise to be able to build complex machine learning projects using Scala.This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:? Scala for Data Science, Pascal Bugnion? Scala for Machine Learning, Patrick Nicolas? Mastering Scala Machine Learning, Alex Kozlov

Scala for Machine Learning. Build systems for data processing, machine learning, and deep learning - Second Edition

Patrick R. Nicolas

The discovery of information through data clustering and classification is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, engineering design, logistics, manufacturing, and trading strategies, to detection of genetic anomalies. The book is your one stop guide that introduces you to the functional capabilities of the Scala programming language that are critical to the creation of machine learning algorithms such as dependency injection and implicits. You start by learning data preprocessing and filtering techniques. Following this, you'll move on to unsupervised learning techniques such as clustering and dimension reduction, followed by probabilistic graphical models such as Naïve Bayes, hidden Markov models and Monte Carlo inference. Further, it covers the discriminative algorithms such as linear, logistic regression with regularization, kernelization, support vector machines, neural networks, and deep learning. You’ll move on to evolutionary computing, multibandit algorithms, and reinforcement learning.Finally, the book includes a comprehensive overview of parallel computing in Scala and Akka followed by a description of Apache Spark and its ML library. With updated codes based on the latest version of Scala and comprehensive examples, this book will ensure that you have more than just a solid fundamental knowledge in machine learning with Scala.

Scalable Data Architecture with Java. Build efficient enterprise-grade data architecting solutions using Java

Sinchan Banerjee

Java architectural patterns and tools help architects to build reliable, scalable, and secure data engineering solutions that collect, manipulate, and publish data.This book will help you make the most of the architecting data solutions available with clear and actionable advice from an expert.You’ll start with an overview of data architecture, exploring responsibilities of a Java data architect, and learning about various data formats, data storage, databases, and data application platforms as well as how to choose them. Next, you’ll understand how to architect a batch and real-time data processing pipeline. You’ll also get to grips with the various Java data processing patterns, before progressing to data security and governance. The later chapters will show you how to publish Data as a Service and how you can architect it. Finally, you’ll focus on how to evaluate and recommend an architecture by developing performance benchmarks, estimations, and various decision metrics.By the end of this book, you’ll be able to successfully orchestrate data architecture solutions using Java and related technologies as well as to evaluate and present the most suitable solution to your clients.

Scientific Computing with Python 3. Click here to enter text

Claus Führer, Jan Erik Solem, Olivier Verdier

Python can be used for more than just general-purpose programming. It is a free, open source language and environment that has tremendous potential for use within the domain of scientific computing. This book presents Python in tight connection with mathematical applications and demonstrates how to use various concepts in Python for computing purposes, including examples with the latest version of Python 3. Python is an effective tool to use when coupling scientific computing and mathematics and this book will teach you how to use it for linear algebra, arrays, plotting, iterating, functions, polynomials, and much more.

scikit-learn Cookbook. Over 80 recipes for machine learning in Python with scikit-learn - Second Edition

Julian Avila, Trent Hauck

Python is quickly becoming the go-to language for analysts and data scientists due to its simplicity and flexibility, and within the Python data space, scikit-learn is the unequivocal choice for machine learning. This book includes walk throughs and solutions to the common as well as the not-so-common problems in machine learning, and how scikit-learn can be leveraged to perform various machine learning tasks effectively.The second edition begins with taking you through recipes on evaluating the statistical properties of data and generates synthetic data for machine learning modelling. As you progress through the chapters, you will comes across recipes that will teach you to implement techniques like data pre-processing, linear regression, logistic regression, K-NN, Naïve Bayes, classification, decision trees, Ensembles and much more. Furthermore, you’ll learn to optimize your models with multi-class classification, cross validation, model evaluation and dive deeper in to implementing deep learning with scikit-learn. Along with covering the enhanced features on model section, API and new features like classifiers, regressors and estimators the book also contains recipes on evaluating and fine-tuning the performance of your model. By the end of this book, you will have explored plethora of features offered by scikit-learn for Python to solve any machine learning problem you come across.

Securing Hadoop. Implement robust end-to-end security for your Hadoop ecosystem

Sudheesh Narayan

Security of Big Data is one of the biggest concerns for enterprises today. How do we protect the sensitive information in a Hadoop ecosystem? How can we integrate Hadoop security with existing enterprise security systems? What are the challenges in securing Hadoop and its ecosystem? These are the questions which need to be answered in order to ensure effective management of Big Data. Hadoop, along with Kerberos, provides security features which enable Big Data management and which keep data secure.This book is a practitioner's guide for securing a Hadoop-based Big Data platform. This book provides you with a step-by-step approach to implementing end-to-end security along with a solid foundation of knowledge of the Hadoop and Kerberos security models.This practical, hands-on guide looks at the security challenges involved in securing sensitive data in a Hadoop-based Big Data platform and also covers the Security Reference Architecture for securing Big Data. It will take you through the internals of the Hadoop and Kerberos security models and will provide detailed implementation steps for securing Hadoop. You will also learn how the internals of the Hadoop security model are implemented, how to integrate Enterprise Security Systems with Hadoop security, and how you can manage and control user access to a Hadoop ecosystem seamlessly. You will also get acquainted with implementing audit logging and security incident monitoring within a Big Data platform.

Serverless ETL and Analytics with AWS Glue. Your comprehensive reference guide to learning about AWS Glue and its features

Vishal Pathak, Subramanya Vajiraya, Noritaka Sekiyama, Tomohiro Tanaka, ...

Organizations these days have gravitated toward services such as AWS Glue that undertake undifferentiated heavy lifting and provide serverless Spark, enabling you to create and manage data lakes in a serverless fashion. This guide shows you how AWS Glue can be used to solve real-world problems along with helping you learn about data processing, data integration, and building data lakes.Beginning with AWS Glue basics, this book teaches you how to perform various aspects of data analysis such as ad hoc queries, data visualization, and real-time analysis using this service. It also provides a walk-through of CI/CD for AWS Glue and how to shift left on quality using automated regression tests. You’ll find out how data security aspects such as access control, encryption, auditing, and networking are implemented, as well as getting to grips with useful techniques such as picking the right file format, compression, partitioning, and bucketing. As you advance, you’ll discover AWS Glue features such as crawlers, Lake Formation, governed tables, lineage, DataBrew, Glue Studio, and custom connectors. The concluding chapters help you to understand various performance tuning, troubleshooting, and monitoring options.By the end of this AWS book, you’ll be able to create, manage, troubleshoot, and deploy ETL pipelines using AWS Glue.

Serverless Machine Learning with Amazon Redshift ML. Create, train, and deploy machine learning models using familiar SQL commands

Debu Panda, Phil Bates, Bhanu Pittampally, Sumeet Joshi, ...

Amazon Redshift Serverless enables organizations to run petabyte-scale cloud data warehouses quickly and in a cost-effective way, enabling data science professionals to efficiently deploy cloud data warehouses and leverage easy-to-use tools to train models and run predictions. This practical guide will help developers and data professionals working with Amazon Redshift data warehouses to put their SQL knowledge to work for training and deploying machine learning models.The book begins by helping you to explore the inner workings of Redshift Serverless as well as the foundations of data analytics and types of data machine learning. With the help of step-by-step explanations of essential concepts and practical examples, you’ll then learn to build your own classification and regression models. As you advance, you’ll find out how to deploy various types of machine learning projects using familiar SQL code, before delving into Redshift ML. In the concluding chapters, you’ll discover best practices for implementing serverless architecture with Redshift.By the end of this book, you’ll be able to configure and deploy Amazon Redshift Serverless, train and deploy machine learning models using Amazon Redshift ML, and run inference queries at scale.

Serwer SQL 2008. Usługi biznesowe. Analiza i eksploracja danych

Danuta Mendrala, Marcin Szeliga

Business Intelligence -- Twoja recepta na sukces! Jak zastosować bazy analityczne? Jak wykorzystać język MDX? Jak administrować serwerem SSAS 2008? Informacja jest bezcenna. Umiejętność jej właściwego wykorzystania i zarządzania nią również stanowi ogromną wartość. Autorzy Microsoft SQL Server, wydajnego serwera baz danych, zauważyli to już blisko dziesięć lat temu. To właśnie w Microsoft SQL Server 2000 zostały po raz pierwszy wprowadzone usługi analityczne. Dzięki możliwościom SQL Server 2008 również Ty możesz podejmować właściwe decyzje biznesowe i osiągnąć sukces! Książka "Serwer SQL 2008. Usługi biznesowe. Analiza i eksploracja danych " jest długo oczekiwaną pozycją, której autorzy w sposób kompleksowy podejmują tematykę związaną z Business Intelligence. Dzięki niej zdobędziesz szczegółowe informacje na temat hurtowni danych, baz analitycznych oraz języka MDX. Ponadto dowiesz się, w jaki sposób administrować serwerem SSAS 2008 oraz jak wykorzystać arkusz kalkulacyjny Excel jako klienta baz analitycznych. Dodatkowo zapoznasz się z różnymi technikami eksploracji danych oraz sposobami tworzenia ich projektów. Jeżeli chcesz podejmować celne decyzje poprzez analizę danych, ta książka jest właśnie dla Ciebie! Hurtownie danych Projektowanie systemów Business Intelligence Modelowanie danych Bazy analityczne Serwery OLAP Serwer SSAS 2008 Obiekty analitycznych baz danych Projektowanie i tworzenie baz analitycznych Wykorzystanie języka MDX Administrowanie serwerem SSAS 2008 Wykorzystanie arkusza kalkulacyjnego Excel 2007 jako klienta baz analitycznych Zastosowania eksploracji danych Tworzenie projektów eksploracji danych Wykorzystanie dodatku Data Mining dla pakietu Office 2007 Zarządzaj informacjami tak, by przynosiły Ci korzyść.

Seven NoSQL Databases in a Week. Get up and running with the fundamentals and functionalities of seven of the most popular NoSQL databases

Aaron Ploetz, Devram Kandhare, Sudarshan Kadambi, Xun (Brian) Wu

This is the golden age of open source NoSQL databases. With enterprises having to work with large amounts of unstructured data and moving away from expensive monolithic architecture, the adoption of NoSQL databases is rapidly increasing. Being familiar with the popular NoSQL databases and knowing how to use them is a must for budding DBAs and developers.This book introduces you to the different types of NoSQL databases and gets you started with seven of the most popular NoSQL databases used by enterprises today. We start off with a brief overview of what NoSQL databases are, followed by an explanation of why and when to use them. The book then covers the seven most popular databases in each of these categories: MongoDB, Amazon DynamoDB, Redis, HBase, Cassandra, In?uxDB, and Neo4j. The book doesn't go into too much detail about each database but teachesyou enough to get started with them.By the end of this book, you will have a thorough understanding of the different NoSQL databases and their functionalities, empowering you to select and use the rightdatabase according to your needs.

Siatka danych. Nowoczesna koncepcja samoobsługowej infrastruktury danych

Zhamak Dehghani

Dostęp do danych jest warunkiem rozwoju niejednej organizacji. Aby w pełni skorzystać z ich potencjału i uzyskać dzięki nim konkretną wartość, konieczne jest odpowiednie zarządzanie danymi. Obecnie stosowane rozwiązania w tym zakresie nie nadążają już za złożonością dzisiejszych organizacji, rozprzestrzenianiem się źródeł danych i rosnącymi aspiracjami inżynierów, którzy rozwijają techniki sztucznej inteligencji i analizy danych. Odpowiedzią na te potrzeby może być siatka danych (Data Mesh), jednak praktyczna implementacja tej koncepcji wymaga istotnej zmiany myślenia. Ta książka szczegółowo wyjaśnia paradygmat siatki danych, a przy tym koncentruje się na jego praktycznym zastosowaniu. Zgodnie z tym nowatorskim podejściem dane należy traktować jako produkt, a dziedziny - jako główne zagadnienie. Poza wyjaśnieniem paradygmatu opisano tu zasady projektowania wysokopoziomowej architektury komponentów siatki danych, a także przedstawiono wskazówki i porady dotyczące ewolucyjnej realizacji siatki danych w organizacji. Tematyka ta została potraktowana wszechstronnie: omówiono kwestie technologiczne, organizacyjne, jak również socjologiczne i kulturowe. Dzięki temu jest to cenna lektura zarówno dla architektów i inżynierów, jak i dla badaczy, analityków danych, wreszcie dla liderów i kierowników zespołów. W książce: wyczerpujące wprowadzenie do paradygmatu siatki danych siatka danych i jej komponenty projektowanie architektury siatki danych opracowywanie i realizacja strategii siatki danych zdecentralizowany model własności danych przejście z hurtowni i jezior danych do rozproszonej siatki danych Siatka danych: kolejny etap rozwoju technologii big data!

Simplifying Data Engineering and Analytics with Delta. Create analytics-ready data that fuels artificial intelligence and business intelligence

Anindita Mahapatra, Doug May

Delta helps you generate reliable insights at scale and simplifies architecture around data pipelines, allowing you to focus primarily on refining the use cases being worked on. This is especially important when you consider that existing architecture is frequently reused for new use cases.In this book, you’ll learn about the principles of distributed computing, data modeling techniques, and big data design patterns and templates that help solve end-to-end data flow problems for common scenarios and are reusable across use cases and industry verticals. You’ll also learn how to recover from errors and the best practices around handling structured, semi-structured, and unstructured data using Delta. After that, you’ll get to grips with features such as ACID transactions on big data, disciplined schema evolution, time travel to help rewind a dataset to a different time or version, and unified batch and streaming capabilities that will help you build agile and robust data products.By the end of this Delta book, you’ll be able to use Delta as the foundational block for creating analytics-ready data that fuels all AI/BI use cases.

Simplifying Hybrid Cloud Adoption with AWS. Realize edge computing and build compelling hybrid solutions on premises with AWS Outposts

Frankie Costa Negro

The hybrid edge specialty is often misunderstood because it began with an on-premises-focused view encompassing everything not running inside the traditional data center. If you too have workloads that need to live on premises and need a solution to bridge the gap between both worlds, this book will show you how AWS Outposts allows workloads to leverage the benefits of the cloud running on top of AWS technology.In this book, you’ll learn what the Edge space is, the capabilities to look for when selecting a solution to operate in this realm, and how AWS Outposts delivers. The use cases for Outposts are thoroughly explained and the physical characteristics are detailed alongside the service logical constructs and facility requirements. You’ll gain a comprehensive understanding of the sales process—from order placement to rack delivery to your location. As you advance, you’ll explore how AWS Outposts works in real life with step-by-step examples using AWS CLI and AWS Console before concluding your journey with an extensive overview of security and business continuity for maximizing the value delivered by the product.By the end of this book, you’ll be able to create compelling hybrid architectures, solve complex use cases for hybrid scenarios, and get ready for your way forward with the help of expert guidance.

Skazany na sukces. Kariera w Data Science

Jacqueline Nolis, Emily Robinson

Nauka o danych, zwana danologią, zyskuje na znaczeniu. Dane dla gospodarki są tym, czym dotąd były węgiel, stal i ropa naftowa. Umiejętność korzystania z wiedzy zawartej w danych decyduje o efektywności prowadzenia działalności gospodarczej i determinuje rozwój nowych modeli, rozwiązań i relacji gospodarczych. Już teraz specjaliści danolodzy są rozchwytywani na rynku pracy. Aby jednak w pełni i do końca wykorzystać pojawiające się możliwości, trzeba wiedzieć, w jaki sposób podejść do trudnego zagadnienia, jakim jest budowanie ścieżki kariery i podążanie nią w odpowiednim dla siebie tempie. To praktyczny przewodnik, dzięki któremu łatwiej zdobędziesz pierwszą pracę związaną z badaniem danych, szybciej staniesz się cenionym specjalistą i w miarę rozwoju zawodowego będziesz coraz trafniej wychwytywać pojawiające się możliwości awansu i zmiany pracy na atrakcyjniejszą. Dowiesz się, jak zdobyć podstawowe umiejętności i jak faktycznie wyglądają konkretne stanowiska pracy. Opisano tu również, jak pomyślnie przejść przez proces rekrutacji i zaaklimatyzować się w nowych warunkach. Nie zabrakło cennych wskazówek dotyczących awansowania na stanowiska kierownicze. Jako danolog prędko się przekonasz, że zawarta tutaj wiedza nietechniczna jest bardzo potrzebna do osiągnięcia sukcesu na polu badania danych. Dzięki tej książce dowiesz się, jak: tworzyć świetne portfolio projektów z zakresu badania danych wyszukiwać, oceniać i negocjować oferty z klasą zmieniać miejsca pracy wybierać i skutecznie realizować scenariusze kariery poradzili sobie inni wybitni analitycy danych! Danologia: nauka, pasja i sposób na życie!

Smarter Decisions - The Intersection of Internet of Things and Decision Science. A comprehensive guide for solving IoT business problems using decision science

Jojo Moolayil

With an increasing number of devices getting connected to the Internet, massive amounts of data are being generated that can be used for analysis. This book helps you to understand Internet of Things in depth and decision science, and solve business use cases. With IoT, the frequency and impact of the problem is huge. Addressing a problem with such a huge impact requires a very structured approach. The entire journey of addressing the problem by defining it, designing the solution, and executing it using decision science is articulated in this book through engaging and easy-to-understand business use cases. You will get a detailed understanding of IoT, decision science, and the art of solving a business problem in IoT through decision science. By the end of this book, you’ll have an understanding of the complex aspects of decision making in IoT and will be able to take that knowledge with you onto whatever project calls for it

SolarWinds Server & Application Monitor: Deployment and Administration. Ensuring high availability for your IT services can be problematic, but with this tutorial on SolarWinds SAM it suddenly becomes a lot more feasible. It's the perfect primer for one of the most intuitive, enterprise-level monitors around

Justin Brant

As a network or system administrator, your primary responsibility is to ensure high availability of all managed IT services. There are a number of monitoring tools available; but these can be complicated and expensive, and may only monitor certain areas of your network. SolarWinds Server & Application Monitor is an intuitive, all-encompassing, yet cost effective, enterprise-level network monitoring service.A concise and practical, hands-on guide that will teach you how utilize SolarWinds SAM. It provides step-by-step tutorials to walk you through every feature, while teaching you how to tailor the product to your own network environment.This book will guide you through equipping your network devices and servers for SolarWinds SAM utilization. It will provide a sequential, hands-on overview of the product, and is suited for networks of all sizes, ranging from small businesses to larger enterprises.You will learn how to populate SolarWinds SAM with nodes, then classify and group nodes to tailor the product to your network environment. By doing so, you will benefit from key features such as automated alerts, traps, and reports. Each feature is explained in a practical and useful manner via tutorials and real-world examples to help you start monitoring your network quickly and efficiently, while keeping security implications in mind by applying enterprise-level best practices.