Business intelligence and analytics software enable businesses to analyze performance data in order to make better decisions through the use of cloud computing--an Internet-based model for convenient, on-demand network access to a shared pool of configurable computing resources. This book is a practitioner's guide for successful evaluation and design for implementation of Cognos Business Intelligence cloud solution, for either Cognos 8 BI or Cognos Business Intelligence Version 10. With pragmatic and practical information about the best practices and guidelines, as well as specific software and configuration steps, this guide for solutions and IT architects includes detailed screen shots, code samples, and input instructions.

This IBM Redbooks® publication presents a Smart Analytics Cloud. The IBM Smart Analytics Cloud is an IBM offering to enable delivery of business intelligence and analytics at the customer location in a private cloud deployment. The offering leverages a combination of IBM hardware, software and services to offer customers a complete solution that is enabled at their site. In this publication, we provide the background and product information for decision-makers to proceed with a cloud solution. The content ranges from an introduction to cloud computing to details about our lab implementation. The core of the book discusses the business value, architecture, and functionality of a Smart Analytics Cloud. To provide deeper perspective, documentation is also provided about implementation of one specific Smart Analytics Cloud solution that we created in our lab environment. Additionally, we also describe the IBM Smart Analytics Cloud service offering that can help you create your own Smart Analytics cloud solution that is tailored to your business needs.

Big data is currently one of the most critical emerging technologies. Organizations around the world are looking to exploit the explosive growth of data to unlock previously hidden insights in the hope of creating new revenue streams, gaining operational efficiencies, and obtaining greater understanding of customer needs. It is important to think of big data and analytics together. Big data is the term used to describe the recent explosion of different types of data from disparate sources. Analytics is about examining data to derive interesting and relevant trends and patterns, which can be used to inform decisions, optimize processes, and even drive new business models. With today's deluge of data comes the problems of processing that data, obtaining the correct skills to manage and analyze that data, and establishing rules to govern the data's use and distribution. The big data technology stack is ever growing and sometimes confusing, even more so when we add the complexities of setting up big data environments with large up-front investments. Cloud computing seems to be a perfect vehicle for hosting big data workloads. However, working on big data in the cloud brings its own challenge of reconciling two contradictory design principles. Cloud computing is based on the concepts of consolidation and resource pooling, but big data systems (such as Hadoop) are built on the shared nothing principle, where each node is independent and self-sufficient. A solution architecture that can allow these mutually exclusive principles to coexist is required to truly exploit the elasticity and ease-of-use of cloud computing for big data environments. This IBM® RedpaperTM publication is aimed at chief architects, line-of-business executives, and CIOs to provide an understanding of the cloud-related challenges they face and give prescriptive guidance for how to realize the benefits of big data solutions quickly and cost-effectively.

Build end-to-end AI solutions with IBM Cloud Pak for Data to operationalize AI on a secure platform based on cloud-native reliability, cost-effective multitenancy, and efficient resource management Key FeaturesExplore data virtualization by accessing data in real time without moving itUnify the data and AI experience with the integrated end-to-end platformExplore the AI life cycle and learn to build, experiment, and operationalize trusted AI at scaleBook Description Cloud Pak for Data is IBM's modern data and AI platform that includes strategic offerings from its data and AI portfolio delivered in a cloud-native fashion with the flexibility of deployment on any cloud. The platform offers a unique approach to addressing modern challenges with an integrated mix of proprietary, open-source, and third-party services. You'll begin by getting to grips with key concepts in modern data management and artificial intelligence (AI), reviewing real-life use cases, and developing an appreciation of the AI Ladder principle. Once you've gotten to grips with the basics, you will explore how Cloud Pak for Data helps in the elegant implementation of the AI Ladder practice to collect, organize, analyze, and infuse data and trustworthy AI across your business. As you advance, you'll discover the capabilities of the platform and extension services, including how they are packaged and priced. With the help of examples present throughout the book, you will gain a deep understanding of the platform, from its rich capabilities and technical architecture to its ecosystem and key go-to-market aspects. By the end of this IBM book, you'll be able to apply IBM Cloud Pak for Data's prescriptive practices and leverage its capabilities to build a trusted data foundation and accelerate AI adoption in your enterprise. What you will learnUnderstand the importance of digital transformations and the role of data and AI platformsGet to grips with data architecture and its relevance in driving AI adoption using IBM's AI LadderUnderstand Cloud Pak for Data, its value proposition, capabilities, and unique differentiatorsDelve into the pricing, packaging, key use cases, and competitors of Cloud Pak for DataUse the Cloud Pak for Data ecosystem with premium IBM and third-party servicesDiscover IBM's vibrant ecosystem of proprietary, open-source, and third-party offerings from over 35 ISVsWho this book is for This book is for data scientists, data stewards, developers, and data-focused business executives interested in learning about IBM's Cloud Pak for Data. Knowledge of technical concepts related to data science and familiarity with data analytics and AI initiatives at various levels of maturity are required to make the most of this book.

This innovative new textbook, co-authored by an established academic and a leading practitioner, is the first to bring together issues of cloud computing, business intelligence and big data analytics in order to explore how organisations use cloud technology to analyse data and make decisions. In addition to offering an up-to-date exploration of key issues relating to data privacy and ethics, information governance, and the future of analytics, the text describes the options available in deploying analytic solutions to the cloud and draws on real-world, international examples from companies such as Rolls Royce, Lego, Volkswagen and Samsung. Combining academic and practitioner perspectives that are crucial to the understanding of this growing field, Business Analytics acts an ideal core text for undergraduate, postgraduate and MBA modules on Big Data, Business and Data Analytics, and Business Intelligence, as well as functioning as a supplementary text for modules in Marketing Analytics. The book is also an invaluable resource for practitioners and will quickly enable the next generation of 'Information Builders' within organisations to understand innovative cloud based-analytic solutions.

A Complete Blueprint for Maximizing the Value of Business Intelligence in the Enterprise The typical enterprise recognizes the immense potential of business intelligence (BI) and its impact upon many facets within the organization—but it’s not easy to transform BI’s potential into real business value. In The New Era of Enterprise Business Intelligence, top BI expert Mike Biere presents a complete blueprint for creating winning BI strategies and infrastructure, and systematically maximizing the value of information throughout the enterprise. This product-independent guide brings together start-to-finish guidance and practical checklists for every senior IT executive, planner, strategist, implementer, and the actual business users themselves. Drawing on thousands of hours working with enterprise customers, Biere helps decision-makers choose from today’s unprecedented spectrum of options, including the latest BI platform suites and appliances. He offers practical, “in-the-trenches” insights on a wide spectrum of planning and implementation issues, from segmenting and supporting users to working with unstructured data. Coverage includes Understanding the scope of today’s BI solutions and how they fit into existing infrastructure Assessing new options such as SaaS and cloud-based technologies Avoiding technology biases and other “project killers” Developing effective RFIs/RFPs and proofs of concept Setting up competency centers and planning for skills development Crafting a better experience for all your business users Supporting the requirements of senior executives, including performance management Cost-justifying BI solutions and measuring success Working with enterprise content management, text analytics, and search Planning and constructing portals, mashups, and other user interfaces Previewing the future of BI