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Predictive Analytics for the Modern Enterprise

Predictive Analytics for the Modern Enterprise
Author: Nooruddin Abbas Ali
Publisher: "O'Reilly Media, Inc."
Total Pages: 358
Release: 2024-05-20
Genre: Computers
ISBN: 1098136829

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The surging predictive analytics market is expected to grow from $10.5 billion today to $28 billion by 2026. With the rise in automation across industries, the increase in data-driven decision-making, and the proliferation of IoT devices, predictive analytics has become an operational necessity in today's forward-thinking companies. If you're a data professional, you need to be aligned with your company's business activities more than ever before. This practical book provides the background, tools, and best practices necessary to help you design, implement, and operationalize predictive analytics on-premises or in the cloud. Explore ways that predictive analytics can provide direct input back to your business Understand mathematical tools commonly used in predictive analytics Learn the development frameworks used in predictive analytics applications Appreciate the role of predictive analytics in the machine learning process Examine industry implementations of predictive analytics Build, train, and retrain predictive models using Python and TensorFlow


Predictive Analytics for the Modern Enterprise

Predictive Analytics for the Modern Enterprise
Author: Nooruddin Abbas Ali
Publisher: "O'Reilly Media, Inc."
Total Pages: 361
Release: 2024-05-20
Genre: Computers
ISBN: 1098136837

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The surging predictive analytics market is expected to grow from $10.5 billion today to $28 billion by 2026. With the rise in automation across industries, the increase in data-driven decision-making, and the proliferation of IoT devices, predictive analytics has become an operational necessity in today's forward-thinking companies. If you're a data professional, you need to be aligned with your company's business activities more than ever before. This practical book provides the background, tools, and best practices necessary to help you design, implement, and operationalize predictive analytics on-premises or in the cloud. Explore ways that predictive analytics can provide direct input back to your business Understand mathematical tools commonly used in predictive analytics Learn the development frameworks used in predictive analytics applications Appreciate the role of predictive analytics in the machine learning process Examine industry implementations of predictive analytics Build, train, and retrain predictive models using Python and TensorFlow


Modern Enterprise Business Intelligence and Data Management

Modern Enterprise Business Intelligence and Data Management
Author: Alan Simon
Publisher: Morgan Kaufmann
Total Pages: 99
Release: 2014-08-28
Genre: Computers
ISBN: 0128017457

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Nearly every large corporation and governmental agency is taking a fresh look at their current enterprise-scale business intelligence (BI) and data warehousing implementations at the dawn of the "Big Data Era"...and most see a critical need to revitalize their current capabilities. Whether they find the frustrating and business-impeding continuation of a long-standing "silos of data" problem, or an over-reliance on static production reports at the expense of predictive analytics and other true business intelligence capabilities, or a lack of progress in achieving the long-sought-after enterprise-wide "single version of the truth" – or all of the above – IT Directors, strategists, and architects find that they need to go back to the drawing board and produce a brand new BI/data warehousing roadmap to help move their enterprises from their current state to one where the promises of emerging technologies and a generation’s worth of best practices can finally deliver high-impact, architecturally evolvable enterprise-scale business intelligence and data warehousing. Author Alan Simon, whose BI and data warehousing experience dates back to the late 1970s and who has personally delivered or led more than thirty enterprise-wide BI/data warehousing roadmap engagements since the mid-1990s, details a comprehensive step-by-step approach to building a best practices-driven, multi-year roadmap in the quest for architecturally evolvable BI and data warehousing at the enterprise scale. Simon addresses the triad of technology, work processes, and organizational/human factors considerations in a manner that blends the visionary and the pragmatic. Takes a fresh look at true enterprise-scale BI/DW in the "Dawn of the Big Data Era" Details a checklist-based approach to surveying one’s current state and identifying which components are enterprise-ready and which ones are impeding the key objectives of enterprise-scale BI/DW Provides an approach for how to analyze and test-bed emerging technologies and architectures and then figure out how to include the relevant ones in the roadmaps that will be developed Presents a tried-and-true methodology for building a phased, incremental, and iterative enterprise BI/DW roadmap that is closely aligned with an organization’s business imperatives, organizational culture, and other considerations


Computing Predictive Analytics Business Intelligence and Economics

Computing Predictive Analytics Business Intelligence and Economics
Author: Cyrus F. Nourani
Publisher: Apple Academic Press
Total Pages: 312
Release: 2021-03-31
Genre:
ISBN: 9781774634196

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This volume brings together research and system designs that address the scientific basis and the practical systems design issues that support areas ranging from intelligent business interfaces and predictive analytics to economics modeling. Applications for management science and IT have been of interest areas for business schools and computing experts during recent years. Among the areas that are being treated are modern analytics, heterogeneous computing, business intelligence, ERP (enterprise resource planning), and decision science. Consumers have been pledging their love for data visualizations for a while now, and data is the area being explored, such as B2B and EC (E-commerce), E-business and the Intelligent Web, CRM (customer relationship management), infrastructures, and more. The digitization implications of these many new applications are described and explored in this informative volume. One of BookAuthority's Best New Analytics Books to Read in 2020!


A Modern Enterprise Architecture Approach

A Modern Enterprise Architecture Approach
Author: Dr Mehmet Yildiz
Publisher: Steps Publishing Australia
Total Pages: 216
Release: 2019-10-07
Genre: Computers
ISBN:

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The revised version of this book to provide essential guidance, compelling ideas, and unique ways to Enterprise Architects so that they can successfully perform complex enterprise modernisation initiatives transforming from chaos to coherence. This is not an ordinary theory book describing Enterprise Architecture in detail. There are myriad of books on the market and in libraries discussing details of enterprise architecture. My aim here is to highlight success factors and reflect lessons learnt from the field within enterprise modernisation and transformation context. As a practising Senior Enterprise Architect, myself, I read hundreds of those books and articles to learn different views. They have been valuable to me to establish my foundations in the earlier phase of my profession. However, what is missing now is a concise guidance book showing Enterprise Architects the novel approaches, insights from the real-life experience and experimentations, and pointing out the differentiating technologies for enterprise modernisation. If only there were such a guide when I started engaging in modernisation and transformation programs. The biggest lesson learned is the business outcome of the enterprise modernisation. What genuinely matters for business is the return on investment of the enterprise architecture and its monetising capabilities. The rest is the theory because nowadays sponsoring executives, due to economic climate, have no interest, attention, or tolerance for non-profitable ventures. I am sorry for disappointing some idealistic Enterprise Architects, but with due respect, it is the reality, and we cannot change it. This book deals with reality rather than theoretical perfection. Anyone against this view on this climate must be coming from another planet. In this concise, uncluttered and easy-to-read book, I attempt to show the significant pain points and valuable considerations for enterprise modernisation using a structured approach and a simple narration especially considering my audience from non-English speaking backgrounds. The architectural rigour is still essential. We cannot compromise the rigour aiming to the quality of products and services as a target outcome. However, there must be a delicate balance among architectural rigour, business value, and speed to the market. I applied this pragmatic approach to multiple substantial transformation initiatives and complex modernisations programs. The key point is using an incrementally progressing iterative approach to every aspect of modernisation initiatives, including people, processes, tools, and technologies as a whole. Starting with a high-level view of enterprise architecture to set the context, I provided a dozen of distinct chapters to point out and elaborate on the factors which can make a real difference in dealing with complexity and producing excellent modernisation initiatives. As eminent leaders, Enterprise Architects are the critical talents who can undertake this massive mission using their people and technology skills, in addition to many critical attributes such as calm and composed approach. Let's keep in mind that as Enterprise Architects, we are architects, not firefighters! I have full confidence that this book can provide valuable insights and some 'aha' moments for talented architects like yourself to tackle this enormous mission of turning chaos to coherence.


Predictive Business Analytics

Predictive Business Analytics
Author: Lawrence Maisel
Publisher: John Wiley & Sons
Total Pages: 276
Release: 2013-10-07
Genre: Business & Economics
ISBN: 1118175565

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Discover the breakthrough tool your company can use to make winning decisions This forward-thinking book addresses the emergence of predictive business analytics, how it can help redefine the way your organization operates, and many of the misconceptions that impede the adoption of this new management capability. Filled with case examples, Predictive Business Analytics defines ways in which specific industries have applied these techniques and tools and how predictive business analytics can complement other financial applications such as budgeting, forecasting, and performance reporting. Examines how predictive business analytics can help your organization understand its various drivers of performance, their relationship to future outcomes, and improve managerial decision-making Looks at how to develop new insights and understand business performance based on extensive use of data, statistical and quantitative analysis, and explanatory and predictive modeling Written for senior financial professionals, as well as general and divisional senior management Visionary and effective, Predictive Business Analytics reveals how you can use your business's skills, technologies, tools, and processes for continuous analysis of past business performance to gain forward-looking insight and drive business decisions and actions.


Modern Analytics Methodologies

Modern Analytics Methodologies
Author: Michele Chambers
Publisher: Pearson Education
Total Pages: 272
Release: 2015
Genre: Business & Economics
ISBN: 0133498581

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Many organizations now understand the gap between their current analytical capabilities and where they need to be. Far fewer organizations know how to overcome that gap, monetize analytics, and fully capitalize on Big Data. Modern Analytics Methodologies helps you customize a complete roadmap for implementing analytics that supports your strategy, aligns with your culture, and is unique for your organization. Drawing on work with dozens of leading enterprises, Michele Chambers and Thomas Dinsmore describe high-value applications from many industries, and help you systematically identify and deliver on your company's best opportunities. Writing for both professionals and students, they show how to: Leverage the convergence of macro trends ranging from "flattening" and "green" to Big Data and machine learning Go beyond the Analytics Maturity Model: power your unique business strategy with an equally focused analytics strategy Link key business objectives with core characteristics of your organization, value chain, and stakeholders Take advantage of game changing opportunities before competitors do Effectively integrate the managerial and operational aspects of analytics Measure performance with dashboards, scorecards, visualization, simulation, and more Prioritize and score prospective analytics projects Identify "Quick Wins" you can implement while you're planning for the long-term Build an effective Analytic Program Office to make your roadmap persistent Update and revise your roadmap for new needs and technologies


The Enterprise Big Data Lake

The Enterprise Big Data Lake
Author: Alex Gorelik
Publisher: "O'Reilly Media, Inc."
Total Pages: 224
Release: 2019-02-21
Genre: Computers
ISBN: 1491931507

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The data lake is a daring new approach for harnessing the power of big data technology and providing convenient self-service capabilities. But is it right for your company? This book is based on discussions with practitioners and executives from more than a hundred organizations, ranging from data-driven companies such as Google, LinkedIn, and Facebook, to governments and traditional corporate enterprises. You’ll learn what a data lake is, why enterprises need one, and how to build one successfully with the best practices in this book. Alex Gorelik, CTO and founder of Waterline Data, explains why old systems and processes can no longer support data needs in the enterprise. Then, in a collection of essays about data lake implementation, you’ll examine data lake initiatives, analytic projects, experiences, and best practices from data experts working in various industries. Get a succinct introduction to data warehousing, big data, and data science Learn various paths enterprises take to build a data lake Explore how to build a self-service model and best practices for providing analysts access to the data Use different methods for architecting your data lake Discover ways to implement a data lake from experts in different industries


Win with Advanced Business Analytics

Win with Advanced Business Analytics
Author: Jean-Paul Isson
Publisher: John Wiley & Sons
Total Pages: 416
Release: 2012-10-09
Genre: Business & Economics
ISBN: 1118370600

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Plain English guidance for strategic business analytics and big data implementation In today's challenging economy, business analytics and big data have become more and more ubiquitous. While some businesses don't even know where to start, others are struggling to move from beyond basic reporting. In some instances management and executives do not see the value of analytics or have a clear understanding of business analytics vision mandate and benefits. Win with Advanced Analytics focuses on integrating multiple types of intelligence, such as web analytics, customer feedback, competitive intelligence, customer behavior, and industry intelligence into your business practice. Provides the essential concept and framework to implement business analytics Written clearly for a nontechnical audience Filled with case studies across a variety of industries Uniquely focuses on integrating multiple types of big data intelligence into your business Companies now operate on a global scale and are inundated with a large volume of data from multiple locations and sources: B2B data, B2C data, traffic data, transactional data, third party vendor data, macroeconomic data, etc. Packed with case studies from multiple countries across a variety of industries, Win with Advanced Analytics provides a comprehensive framework and applications of how to leverage business analytics/big data to outpace the competition.


Enterprise Analytics

Enterprise Analytics
Author: Thomas H. Davenport
Publisher: FT Press
Total Pages: 287
Release: 2012-09-13
Genre: Business & Economics
ISBN: 0133039463

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Normal 0 false false false MicrosoftInternetExplorer4 The Definitive Guide to Enterprise-Level Analytics Strategy, Technology, Implementation, and Management Organizations are capturing exponentially larger amounts of data than ever, and now they have to figure out what to do with it. Using analytics, you can harness this data, discover hidden patterns, and use this knowledge to act meaningfully for competitive advantage. Suddenly, you can go beyond understanding “how, when, and where” events have occurred, to understand why – and use this knowledge to reshape the future. Now, analytics pioneer Tom Davenport and the world-renowned experts at the International Institute for Analytics (IIA) have brought together the latest techniques, best practices, and research on analytics in a single primer for maximizing the value of enterprise data. Enterprise Analytics is today’s definitive guide to analytics strategy, planning, organization, implementation, and usage. It covers everything from building better analytics organizations to gathering data; implementing predictive analytics to linking analysis with organizational performance. The authors offer specific insights for optimizing supply chains, online services, marketing, fraud detection, and many other business functions. They support their powerful techniques with many real-world examples, including chapter-length case studies from healthcare, retail, and financial services. Enterprise Analytics will be an invaluable resource for every business and technical professional who wants to make better data-driven decisions: operations, supply chain, and product managers; product, financial, and marketing analysts; CIOs and other IT leaders; data, web, and data warehouse specialists, and many others.