Data Dynamo: Unleashing the Power of Big Data Analytics

Data Dynamo: Unleashing the Power of Big Data Analytics PDF Author: Mothiram Rajasekaran
Publisher: Leilani Katie Publication
ISBN: 9363484947
Category : Computers
Languages : en
Pages : 218

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Book Description
Mothiram Rajasekaran,Senior Solution Consultant, Cloudera, USA.

Data Dynamo: Unleashing the Power of Big Data Analytics

Data Dynamo: Unleashing the Power of Big Data Analytics PDF Author: Mothiram Rajasekaran
Publisher: Leilani Katie Publication
ISBN: 9363484947
Category : Computers
Languages : en
Pages : 218

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Book Description
Mothiram Rajasekaran,Senior Solution Consultant, Cloudera, USA.

Digital Dynamo: Unleashing the Power of Innovative Marketing in the Digital Age

Digital Dynamo: Unleashing the Power of Innovative Marketing in the Digital Age PDF Author: Abidur Rahman
Publisher: Ocleno
ISBN:
Category : Business & Economics
Languages : en
Pages : 9

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Book Description
Dive into the pulsating heart of the digital revolution with 'Digital Dynamo: Unleashing the Power of Innovative Marketing in the Digital Age.' In this compelling exploration, embark on a transformative journey through the ever-changing landscape of digital marketing. From the foundational principles that underpin online success to the cutting-edge technologies shaping the future, this book is your definitive guide to mastering the art and science of digital marketing. Discover the evolution of the internet, unravel the secrets of compelling online presence, and venture into the dynamic realms of social media marketing, digital advertising, and the ethical considerations that guide responsible marketing practices. Delve deep into the world of emerging technologies like augmented reality and artificial intelligence, and learn how to navigate the complexities of sustainability and social responsibility in the digital age. With in-depth insights, real-world case studies, and practical strategies, 'Digital Dynamo' equips you with the knowledge and tools to not only survive but thrive in the digital marketplace. Whether you're an entrepreneur aiming to establish an online presence or a seasoned marketer striving to stay ahead of the curve, this book is your compass, guiding you toward innovative, ethical, and human-centric digital marketing practices. Prepare to revolutionize your approach, forge authentic connections with your audience, and unleash the full potential of your digital marketing endeavors. Your journey to becoming a digital dynamo starts here.

Big Data Analytics

Big Data Analytics PDF Author: David Loshin
Publisher: Elsevier
ISBN: 0124186645
Category : Computers
Languages : en
Pages : 143

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Book Description
Big Data Analytics will assist managers in providing an overview of the drivers for introducing big data technology into the organization and for understanding the types of business problems best suited to big data analytics solutions, understanding the value drivers and benefits, strategic planning, developing a pilot, and eventually planning to integrate back into production within the enterprise. Guides the reader in assessing the opportunities and value proposition Overview of big data hardware and software architectures Presents a variety of technologies and how they fit into the big data ecosystem

Harness the Power of Big Data The IBM Big Data Platform

Harness the Power of Big Data The IBM Big Data Platform PDF Author: Paul Zikopoulos
Publisher: McGraw Hill Professional
ISBN: 0071808183
Category : Computers
Languages : en
Pages : 281

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Book Description
Boost your Big Data IQ! Gain insight into how to govern and consume IBM’s unique in-motion and at-rest Big Data analytic capabilities Big Data represents a new era of computing—an inflection point of opportunity where data in any format may be explored and utilized for breakthrough insights—whether that data is in-place, in-motion, or at-rest. IBM is uniquely positioned to help clients navigate this transformation. This book reveals how IBM is infusing open source Big Data technologies with IBM innovation that manifest in a platform capable of "changing the game." The four defining characteristics of Big Data—volume, variety, velocity, and veracity—are discussed. You’ll understand how IBM is fully committed to Hadoop and integrating it into the enterprise. Hear about how organizations are taking inventories of their existing Big Data assets, with search capabilities that help organizations discover what they could already know, and extend their reach into new data territories for unprecedented model accuracy and discovery. In this book you will also learn not just about the technologies that make up the IBM Big Data platform, but when to leverage its purpose-built engines for analytics on data in-motion and data at-rest. And you’ll gain an understanding of how and when to govern Big Data, and how IBM’s industry-leading InfoSphere integration and governance portfolio helps you understand, govern, and effectively utilize Big Data. Industry use cases are also included in this practical guide.

Big Data Analytics

Big Data Analytics PDF Author: Arun K. Somani
Publisher: CRC Press
ISBN: 1351180320
Category : Computers
Languages : en
Pages : 399

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Book Description
The proposed book will discuss various aspects of big data Analytics. It will deliberate upon the tools, technology, applications, use cases and research directions in the field. Chapters would be contributed by researchers, scientist and practitioners from various reputed universities and organizations for the benefit of readers.

DIGITAL DYNAMO: UNLEASHING THE POWER OF MODERN MARKETING

DIGITAL DYNAMO: UNLEASHING THE POWER OF MODERN MARKETING PDF Author: Ms. Kaushaki Sondhi
Publisher: JEC PUBLICATION
ISBN: 9358507322
Category : Juvenile Fiction
Languages : en
Pages : 270

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Book Description
"Digital Dynamo: Unleashing the Power of Modern Marketing" is a comprehensive guide that dives deep into the dynamic world of digital marketing, providing readers with a strategic roadmap to navigate the ever-evolving landscape and maximize their online presence. This book will equip marketers, business owners, and aspiring digital enthusiasts with practical insights, real-world case studies, and actionable strategies to succeed in the digital realm. In this comprehensive exploration of digital marketing, we delved into various aspects of creating effective strategies, connecting with audiences, and staying ahead in the ever-evolving digital landscape. We started by defining digital marketing and recognizing its significance in modern business. We traced its evolution, dissecting its impact on traditional marketing practices. Understanding the components of a successful digital marketing strategy was a pivotal step, where we emphasized setting clear goals tailored to business needs and identifying target audiences through buyer personas. We explored content strategy creation, content format diversification, and leveraging storytelling to emotionally engage customers. The journey ventured into the realm of social media, where we discussed major platforms, organic and paid strategies, and the art of building a loyal community. We then navigated the intricacies of SEO, both on-page and off-page, while emphasizing the importance of staying current with search engine algorithm changes. Pay-per-click advertising, including Google Ads and Bing Ads, was demystified, accompanied by insights into crafting effective ad copy and optimizing campaigns for ROI. We expanded into search engine marketing (SEM) and display advertising, revealing their potential impact. Email campaigns took center stage, from designing engaging content and compelling subject lines to building segmented lists and automating sequences for nurturing and retention. The role of data analytics was highlighted, showcasing its power in shaping strategies, tracking performance, and understanding customer behavior. Wrapping up, we explored emerging technologies like AI, chatbots, and virtual reality, envisioning their integration into future marketing efforts. Ethical considerations underscored the importance of maintaining consumer trust and data security. Finally, building transparency and trust emerged as the bedrock of successful digital marketing, culminating in a holistic perspective on navigating the dynamic digital landscape.

Big Data Science & Analytics

Big Data Science & Analytics PDF Author: Arshdeep Bahga
Publisher: Vpt
ISBN: 9780996025539
Category :
Languages : en
Pages : 544

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Book Description
We are living in the dawn of what has been termed as the "Fourth Industrial Revolution," which is marked through the emergence of "cyber-physical systems" where software interfaces seamlessly over networks with physical systems, such as sensors, smartphones, vehicles, power grids or buildings, to create a new world of Internet of Things (IoT). Data and information are fuel of this new age where powerful analytics algorithms burn this fuel to generate decisions that are expected to create a smarter and more efficient world for all of us to live in. This new area of technology has been defined as Big Data Science and Analytics, and the industrial and academic communities are realizing this as a competitive technology that can generate significant new wealth and opportunity. Big data is defined as collections of datasets whose volume, velocity or variety is so large that it is difficult to store, manage, process and analyze the data using traditional databases and data processing tools. Big data science and analytics deals with collection, storage, processing and analysis of massive-scale data. Industry surveys, by Gartner and e-Skills, for instance, predict that there will be over 2 million job openings for engineers and scientists trained in the area of data science and analytics alone, and that the job market is in this area is growing at a 150 percent year-over-year growth rate. We have written this textbook, as part of our expanding "A Hands-On Approach"(TM) series, to meet this need at colleges and universities, and also for big data service providers who may be interested in offering a broader perspective of this emerging field to accompany their customer and developer training programs. The typical reader is expected to have completed a couple of courses in programming using traditional high-level languages at the college-level, and is either a senior or a beginning graduate student in one of the science, technology, engineering or mathematics (STEM) fields. An accompanying website for this book contains additional support for instruction and learning (www.big-data-analytics-book.com) The book is organized into three main parts, comprising a total of twelve chapters. Part I provides an introduction to big data, applications of big data, and big data science and analytics patterns and architectures. A novel data science and analytics application system design methodology is proposed and its realization through use of open-source big data frameworks is described. This methodology describes big data analytics applications as realization of the proposed Alpha, Beta, Gamma and Delta models, that comprise tools and frameworks for collecting and ingesting data from various sources into the big data analytics infrastructure, distributed filesystems and non-relational (NoSQL) databases for data storage, and processing frameworks for batch and real-time analytics. This new methodology forms the pedagogical foundation of this book. Part II introduces the reader to various tools and frameworks for big data analytics, and the architectural and programming aspects of these frameworks, with examples in Python. We describe Publish-Subscribe messaging frameworks (Kafka & Kinesis), Source-Sink connectors (Flume), Database Connectors (Sqoop), Messaging Queues (RabbitMQ, ZeroMQ, RestMQ, Amazon SQS) and custom REST, WebSocket and MQTT-based connectors. The reader is introduced to data storage, batch and real-time analysis, and interactive querying frameworks including HDFS, Hadoop, MapReduce, YARN, Pig, Oozie, Spark, Solr, HBase, Storm, Spark Streaming, Spark SQL, Hive, Amazon Redshift and Google BigQuery. Also described are serving databases (MySQL, Amazon DynamoDB, Cassandra, MongoDB) and the Django Python web framework. Part III introduces the reader to various machine learning algorithms with examples using the Spark MLlib and H2O frameworks, and visualizations using frameworks such as Lightning, Pygal and Seaborn.

Practical Big Data Analytics

Practical Big Data Analytics PDF Author: Nataraj Dasgupta
Publisher: Packt Publishing Ltd
ISBN: 1783554401
Category : Computers
Languages : en
Pages : 402

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Book Description
Get command of your organizational Big Data using the power of data science and analytics Key Features A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Book Description Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book. What you will learn - Get a 360-degree view into the world of Big Data, data science and machine learning - Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives - Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R - Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions - Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications - Understand corporate strategies for successful Big Data and data science projects - Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies Who this book is for The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience.

Big Data Analytics

Big Data Analytics PDF Author: Frank J. Ohlhorst
Publisher: John Wiley & Sons
ISBN: 1118239040
Category : Business & Economics
Languages : en
Pages : 176

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Book Description
Unique insights to implement big data analytics and reap big returns to your bottom line Focusing on the business and financial value of big data analytics, respected technology journalist Frank J. Ohlhorst shares his insights on the newly emerging field of big data analytics in Big Data Analytics. This breakthrough book demonstrates the importance of analytics, defines the processes, highlights the tangible and intangible values and discusses how you can turn a business liability into actionable material that can be used to redefine markets, improve profits and identify new business opportunities. Reveals big data analytics as the next wave for businesses looking for competitive advantage Takes an in-depth look at the financial value of big data analytics Offers tools and best practices for working with big data Once the domain of large on-line retailers such as eBay and Amazon, big data is now accessible by businesses of all sizes and across industries. From how to mine the data your company collects, to the data that is available on the outside, Big Data Analytics shows how you can leverage big data into a key component in your business's growth strategy.

Big Data, Big Analytics

Big Data, Big Analytics PDF Author: Michael Minelli
Publisher: John Wiley & Sons
ISBN: 111814760X
Category : Business & Economics
Languages : en
Pages : 230

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Book Description
Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.) Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more.