Big Data for Enterprise Architects
(eBook)

Grouping Information

Book Cover Information

Hoopla Extract Information

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(
    [year] => 2019
    [artist] => Dr. Mehmet Yildiz
    [fiction] => 
    [coverImageUrl] => https://cover.hoopladigital.com/dra_9781393300038_270.jpeg
    [titleId] => 14941420
    [isbn] => 9781393300038
    [abridged] => 
    [language] => ENGLISH
    [profanity] => 
    [title] => Big Data for Enterprise Architects
    [demo] => 
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        )

    [pages] => 109
    [children] => 
    [artists] => Array
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            [0] => stdClass Object
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                    [name] => Dr. Mehmet Yildiz
                    [artistFormal] => Yildiz, Dr. Mehmet
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    [genres] => Array
        (
            [0] => Computers
            [1] => Data Modeling & Design
            [2] => Data Science
            [3] => Data Visualization
        )

    [price] => 1.35
    [id] => 14941420
    [edited] => 
    [kind] => EBOOK
    [active] => 1
    [upc] => 
    [synopsis] => The primary purpose of this unique book is to introduce Big Data solutions and the role of a Big Data Solution Architect in enterprise modernisation and transformation initiatives. The book is specifically designed, as a first of a kind on the market, to serve a specific purpose in mind. I intentionally narrated the book wearing my Big Data Solution Architecture role to provide clarity for the roles, responsibilities and significant duties. Also wearing my Enterprise Architect role, positioned the Enterprise Architects as observant to understand the solution approach, techniques, underlying technology stacks, and powerful tools by reading the experience as an observer.

The role of a Big Data Solution Architect is critical in modernising and transforming enterprises; therefore, this book provides a high-level view of the critical solution tasks with integrated technology stacks and tools which can provide insights to the Enterprise Architects by observing the role of a Big Data Solution Architect. To this end, the book provides two dimensions and audience group including both Enterprise and the Big Data Solution Architect.

Integrating Big Data with IoT and Cloud architectures provide substantial business benefits for modernising enterprise. This integration is a perfect match. IoT collects real-time data using smart objects. Big Data optimises vital data management solutions. Cloud collects, hosts, computes, stores, and disseminates valuable data rapidly.

IoT, Big Data, and Cloud Computing are three distinct technology domains with overlapping use cases. Each technology has its own merits; however, the combination of three creates a synergy and the golden opportunity for businesses to reap the exponential benefits. This combination can create technological magic for innovation when adequately architected, designed, implemented, and operated.

Based on these compelling functions, use cases, and business propositions, the primary focus of this book is to provide practical guidance on creating Big Data solutions integrated with IoT and Cloud service models. To this end, the book offers an architectural overview, solution practice, flexible governance, and underlying technical approach for creating integrated Big Data, Cloud, and IoT solutions. The book offers an introduction to the process of solution architecture, three distinct chapters comprising Big Data, Cloud, and the IoT with the final chapter, including conclusive remarks to consider for Big Data and Analytics solutions. These chapters include essential architectural points, solution practice, methodical rigour, techniques, technologies, and relevant tools.

Creating Big Data solutions are complex and complicated from multiple angles. However, with the awareness and guidance provided in this book, the Big Data solutions architects can be empowered to provide useful and productive solutions with growing confidence and the Enterprise Architects can learn from this experience.
    [url] => https://www.hoopladigital.com/title/14941420
    [pa] => 
    [publisher] => Mehmet Yildiz
    [purchaseModel] => INSTANT
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