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Collaboration and content management are the major business needs of every organization in this increasingly global and connected environment. Microsoft SharePoint is a solution to these needs that offers a software platform that facilitates collaboration and provides content management features for the effective implementation of business processes. With a vast amount of functionality available with SharePoint, it is easy to get confused in carrying out administrative tasks.Microsoft SharePoint 2010 Administration Cookbook starts off by demonstrating the various upgrading and post-upgrading tasks to be performed in SharePoint 2010. Next come recipes for managing SharePoint service-level applications and for monitoring the SharePoint environment. The book introduces one of the best new tools that should be in your arsenal, PowerShell, and the commands you will need to script your tasks with Powershell.Collaboration and content management are the most important features of SharePoint and this book contains many recipes that focus on improving them. Enterprise monitoring and reporting are also covered in detail so that you can ensure that your SharePoint implementation is up and running all the time. You will find recipes to manage and customize SharePoint Search.When you are half way through the book, you will explore more advanced and interesting topics such as customizing and securing the SharePoint environment. You will learn to extend SharePoint to include features similar to social networking sites such as Facebook and Twitter. Lastly, the book covers backup and recovery solutions for SharePoint so that you can ensure that your system is protected from data loss and virus attacks.
After scrutinizing numerous cybersecurity strategies, Microsoft’s former Global Chief Security Advisor in this book helps you understand the efficacy of popular cybersecurity strategies and more.Cybersecurity Threats, Malware Trends, and Strategies offers an unprecedented long-term view of the global threat landscape by examining the twenty-year trend in vulnerability disclosures and exploitation, nearly a decade of regional differences in malware infections, the socio-economic factors that underpin them, and how global malware has evolved. This will give you further perspectives into malware protection for your organization. It also examines internet-based threats that CISOs should be aware of.The book will provide you with an evaluation of the various cybersecurity strategies that have ultimately failed over the past twenty years, along with one or two that have actually worked. It will help executives and security and compliance professionals understand how cloud computing is a game changer for them.By the end of this book, you will know how to measure the effectiveness of your organization’s cybersecurity strategy and the efficacy of the vendors you employ to help you protect your organization and yourself.
We’re living in an era where cyber threat intelligence is becoming more important. Cyber threat intelligence routinely informs tactical and strategic decision-making throughout organizational operations. However, finding the right resources on the fundamentals of operationalizing a threat intelligence function can be challenging, and that’s where this book helps.In Operationalizing Threat Intelligence, you’ll explore cyber threat intelligence in five fundamental areas: defining threat intelligence, developing threat intelligence, collecting threat intelligence, enrichment and analysis, and finally production of threat intelligence. You’ll start by finding out what threat intelligence is and where it can be applied. Next, you’ll discover techniques for performing cyber threat intelligence collection and analysis using open source tools. The book also examines commonly used frameworks and policies as well as fundamental operational security concepts. Later, you’ll focus on enriching and analyzing threat intelligence through pivoting and threat hunting. Finally, you’ll examine detailed mechanisms for the production of intelligence.By the end of this book, you’ll be equipped with the right tools and understand what it takes to operationalize your own threat intelligence function, from collection to production.
Data mining is an integral part of the data science pipeline. It is the foundation of any successful data-driven strategy – without it, you'll never be able to uncover truly transformative insights. Since data is vital to just about every modern organization, it is worth taking the next step to unlock even greater value and more meaningful understanding.If you already know the fundamentals of data mining with Python, you are now ready to experiment with more interesting, advanced data analytics techniques using Python's easy-to-use interface and extensive range of libraries. In this book, you'll go deeper into many often overlooked areas of data mining, including association rule mining, entity matching, network mining, sentiment analysis, named entity recognition, text summarization, topic modeling, and anomaly detection. For each data mining technique, we'll review the state-of-the-art and current best practices before comparing a wide variety of strategies for solving each problem. We will then implement example solutions using real-world data from the domain of software engineering, and we will spend time learning how to understand and interpret the results we get.By the end of this book, you will have solid experience implementing some of the most interesting and relevant data mining techniques available today, and you will have achieved a greater fluency in the important field of Python data analytics.
Grafana is an open-source analytical platform used to analyze and monitoring time-series data. This beginner's guide will help you get to grips with Grafana's new features for querying, visualizing, and exploring metrics and logs no matter where they are stored.The book begins by showing you how to install and set up the Grafana server. You'll explore the working mechanism of various components of the Grafana interface along with its security features, and learn how to visualize and monitor data using, InfluxDB, Prometheus, Logstash, and Elasticsearch. This Grafana book covers the advanced features of the Graph panel and shows you how Stat, Table, Bar Gauge, and Text are used. You'll build dynamic dashboards to perform end-to-end analytics and label and organize dashboards into folders to make them easier to find. As you progress, the book delves into the administrative aspects of Grafana by creating alerts, setting permissions for teams, and implementing user authentication. Along with exploring Grafana's multi-cloud monitoring support, you'll also learn about Grafana Loki, which is a backend logger for users running Prometheus and Kubernetes.By the end of this book, you'll have gained all the knowledge you need to start building interactive dashboards.
H2O is an open source, fast, and scalable machine learning framework that allows you to build models using big data and then easily productionalize them in diverse enterprise environments.Machine Learning at Scale with H2O begins with an overview of the challenges faced in building machine learning models on large enterprise systems, and then addresses how H2O helps you to overcome them. You’ll start by exploring H2O’s in-memory distributed architecture and find out how it enables you to build highly accurate and explainable models on massive datasets using your favorite ML algorithms, language, and IDE. You’ll also get to grips with the seamless integration of H2O model building and deployment with Spark using H2O Sparkling Water. You’ll then learn how to easily deploy models with H2O MOJO. Next, the book shows you how H2O Enterprise Steam handles admin configurations and user management, and then helps you to identify different stakeholder perspectives that a data scientist must understand in order to succeed in an enterprise setting. Finally, you’ll be introduced to the H2O AI Cloud platform and explore the entire machine learning life cycle using multiple advanced AI capabilities.By the end of this book, you’ll be able to build and deploy advanced, state-of-the-art machine learning models for your business needs.