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Disruptive Analytics: Charting Your Strategy for Next-Generation Business Analytics
Learn all you need to know about seven key innovations disrupting business analytics today. These innovations—the open source business model, cloud analytics, the Hadoop ecosystem, Spark and in-memory analytics, streaming analytics, Deep Learning, and self-service analytics—are radically changing how businesses use data for competitive advantage. Taken together, they are disrupting the business analytics value chain, creating new opportunities.
Enterprises who seize the opportunity will thrive and prosper, while others struggle and disrupt or be disrupted. Disruptive Business Analytics provides strategies to profit from disruption. It shows you how to organize for insight, build and provision an open source stack, how to practice lean data warehousing, and how to assimilate disruptive innovations into an organization.
Through a short history of business analytics and a detailed survey of products and services, analytics authority Thomas W. Dinsmore provides a practical explanation of the most compelling innovations available today.
What You'll Learn
Discover how the open source business model works and how to make it work for youSee how cloud computing completely changes the economics of analyticsHarness the power of Hadoop and its ecosystemFind out why Apache Spark is everywhereDiscover the potential of streaming and real-time analyticsLearn what Deep Learning can do and why it mattersSee how self-service analytics can change the way organizations do businessWho This Book Is ForCorporate actors at all levels of responsibility for analysts, CIOs, CTOs, strategic decision makers, managers, systems architects, technical marketers, product developers, IT personnel, and consultants.
Enterprises who seize the opportunity will thrive and prosper, while others struggle and disrupt or be disrupted. Disruptive Business Analytics provides strategies to profit from disruption. It shows you how to organize for insight, build and provision an open source stack, how to practice lean data warehousing, and how to assimilate disruptive innovations into an organization.
Through a short history of business analytics and a detailed survey of products and services, analytics authority Thomas W. Dinsmore provides a practical explanation of the most compelling innovations available today.
What You'll Learn
Discover how the open source business model works and how to make it work for youSee how cloud computing completely changes the economics of analyticsHarness the power of Hadoop and its ecosystemFind out why Apache Spark is everywhereDiscover the potential of streaming and real-time analyticsLearn what Deep Learning can do and why it mattersSee how self-service analytics can change the way organizations do businessWho This Book Is ForCorporate actors at all levels of responsibility for analysts, CIOs, CTOs, strategic decision makers, managers, systems architects, technical marketers, product developers, IT personnel, and consultants.
413 pages, Kindle Edition
Published August 27, 2016
3 people are currently reading
47 people want to read
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April 23, 2023
"Disruptive Analytics: Charting Your Strategy for Next-Generation Business Analytics" by Thomas W. Dinsmore is an insightful and forward-thinking book that challenges traditional approaches to business analytics and provides a roadmap for leveraging disruptive analytics to gain a competitive advantage in the modern business landscape.
Dinsmore, a seasoned analytics professional and consultant, presents a compelling argument for the need to adapt and evolve analytics strategies to keep up with the rapid pace of technological advancements and changing business dynamics. He highlights the limitations of traditional analytics approaches and advocates for embracing disruptive analytics, which involve leveraging emerging technologies, new data sources, and advanced analytics techniques to drive innovation and transformative change.
One of the key strengths of "Disruptive Analytics" is its practical and actionable insights. Dinsmore provides a step-by-step guide for organizations to develop a disruptive analytics strategy, covering various aspects such as defining analytics goals, selecting the right analytics tools and technologies, building a data-driven culture, and implementing an agile analytics process. He also shares real-world case studies and examples to illustrate how disruptive analytics have been successfully implemented in different industries and organizations.
Another notable aspect of the book is its emphasis on the ethical implications of analytics. Dinsmore discusses the ethical considerations surrounding data collection, data privacy, bias in algorithms, and the responsible use of analytics in decision-making. He highlights the importance of ethical leadership and governance in the era of disruptive analytics, advocating for organizations to adopt ethical practices as an integral part of their analytics strategies.
Dinsmore's writing style is engaging and accessible, making complex concepts and techniques understandable for readers with varying levels of analytics expertise. He presents his ideas and insights in a clear and logical manner, backed by research and practical examples, making it easy for readers to grasp the concepts and apply them in their own organizations.
However, it is important to note that "Disruptive Analytics" may not be suitable for readers who are looking for a more traditional approach to business analytics or those who are not familiar with advanced analytics techniques and emerging technologies. The book is primarily targeted towards professionals and leaders who are already familiar with the basics of analytics and are looking to explore new ways to gain a competitive edge through disruptive analytics.
In conclusion, "Disruptive Analytics: Charting Your Strategy for Next-Generation Business Analytics" is a thought-provoking and practical guide for organizations looking to leverage disruptive analytics to stay ahead in the rapidly evolving business landscape. Dinsmore's insights, practical examples, and emphasis on ethical considerations make this book a valuable resource for analytics professionals, business leaders, and anyone interested in the future of business analytics.
Dinsmore, a seasoned analytics professional and consultant, presents a compelling argument for the need to adapt and evolve analytics strategies to keep up with the rapid pace of technological advancements and changing business dynamics. He highlights the limitations of traditional analytics approaches and advocates for embracing disruptive analytics, which involve leveraging emerging technologies, new data sources, and advanced analytics techniques to drive innovation and transformative change.
One of the key strengths of "Disruptive Analytics" is its practical and actionable insights. Dinsmore provides a step-by-step guide for organizations to develop a disruptive analytics strategy, covering various aspects such as defining analytics goals, selecting the right analytics tools and technologies, building a data-driven culture, and implementing an agile analytics process. He also shares real-world case studies and examples to illustrate how disruptive analytics have been successfully implemented in different industries and organizations.
Another notable aspect of the book is its emphasis on the ethical implications of analytics. Dinsmore discusses the ethical considerations surrounding data collection, data privacy, bias in algorithms, and the responsible use of analytics in decision-making. He highlights the importance of ethical leadership and governance in the era of disruptive analytics, advocating for organizations to adopt ethical practices as an integral part of their analytics strategies.
Dinsmore's writing style is engaging and accessible, making complex concepts and techniques understandable for readers with varying levels of analytics expertise. He presents his ideas and insights in a clear and logical manner, backed by research and practical examples, making it easy for readers to grasp the concepts and apply them in their own organizations.
However, it is important to note that "Disruptive Analytics" may not be suitable for readers who are looking for a more traditional approach to business analytics or those who are not familiar with advanced analytics techniques and emerging technologies. The book is primarily targeted towards professionals and leaders who are already familiar with the basics of analytics and are looking to explore new ways to gain a competitive edge through disruptive analytics.
In conclusion, "Disruptive Analytics: Charting Your Strategy for Next-Generation Business Analytics" is a thought-provoking and practical guide for organizations looking to leverage disruptive analytics to stay ahead in the rapidly evolving business landscape. Dinsmore's insights, practical examples, and emphasis on ethical considerations make this book a valuable resource for analytics professionals, business leaders, and anyone interested in the future of business analytics.
September 25, 2016
Disclosures: I've worked or consulted for several of the companies mentioned in this book. Also I've been a fan of Mr. Dinsmore's weekly Big Analytics Roundup for a while now -- especially the tone that cuts through the marketing hype when necessary -- though I've never actually met him.
But perhaps most importantly, my actual job is product manager for the Hadoop initiatives at a business intelligence tool company. So a more personalized title for this book would be something like "How To Do Your Job, Dummy: Plus Other Cool, Related Stuff You Should Know."
The mystery at the heart of the book is this: If analytics as an industry is growing -- at a predicted 11% CAGR -- then why are the industry leaders like Oracle, SAP, IBM, SAS, and Teradata having flat or declining sales in their traditional software or hardware businesses?
Naturally it can only be the dreaded Scylla and Charybdis of every run-rate Silicon Valley business: Innovation and Disruption.
After a few short chapters giving an overview of traditional analytics and open source licensing and associated business models, he covers each major area of analytics disruption in nice detail: (Ch4) Hadoop, ecosystem, SQL dialects; (Ch5) In memory, Spark; (Ch6) Streaming, CEP, major projects; (Ch7) Cloud, major providers; (Ch8) Machine learning, recent trends, deep learning overview, major projects; (Ch9) Self-Service analytics, roles and, BI on Hadoop, goofy competitors of mine.
Then it ends with a call to action chapter for executives on how to be a disruptor instead of a disruptee. You can just slap this chapter into a PowerPoint and present it to your boss and take full credit for all the ideas if you want. I'm sure Mr. Dinsmore wouldn't mind. Or better yet you could hire him to help implement his ideas.
I'm not exactly sure how to describe the technical content of the book. I almost wrote that there is no technical content, but that is hardly true of a book that contains a description of a Restricted Boltzmann Machine. It would be more accurate to say that are no equations or code in this book, and that you can skip off to Wikipedia on your phone if you want to deep dive on something. (I did this a couple of times, for example to learn more about Apache Arrow, which was new to me.) There are also pull-outs that explain concepts like "embarrassingly parallel" that might be unfamiliar to people.
Highly recommended if you are working with data, BI, analytics, machine learning, etc. You could walk in to a job (my job, for instance) in analytics or business intelligence and be up to date on the latest trends at a high level, with some vendor management tips thrown in for good measure. Not wild about the list of vendors in Chapter 9, but that's something I'd rather discuss over a cup of coffee. Buy five copies for your company.
But perhaps most importantly, my actual job is product manager for the Hadoop initiatives at a business intelligence tool company. So a more personalized title for this book would be something like "How To Do Your Job, Dummy: Plus Other Cool, Related Stuff You Should Know."
The mystery at the heart of the book is this: If analytics as an industry is growing -- at a predicted 11% CAGR -- then why are the industry leaders like Oracle, SAP, IBM, SAS, and Teradata having flat or declining sales in their traditional software or hardware businesses?
Naturally it can only be the dreaded Scylla and Charybdis of every run-rate Silicon Valley business: Innovation and Disruption.
After a few short chapters giving an overview of traditional analytics and open source licensing and associated business models, he covers each major area of analytics disruption in nice detail: (Ch4) Hadoop, ecosystem, SQL dialects; (Ch5) In memory, Spark; (Ch6) Streaming, CEP, major projects; (Ch7) Cloud, major providers; (Ch8) Machine learning, recent trends, deep learning overview, major projects; (Ch9) Self-Service analytics, roles and, BI on Hadoop, goofy competitors of mine.
Then it ends with a call to action chapter for executives on how to be a disruptor instead of a disruptee. You can just slap this chapter into a PowerPoint and present it to your boss and take full credit for all the ideas if you want. I'm sure Mr. Dinsmore wouldn't mind. Or better yet you could hire him to help implement his ideas.
I'm not exactly sure how to describe the technical content of the book. I almost wrote that there is no technical content, but that is hardly true of a book that contains a description of a Restricted Boltzmann Machine. It would be more accurate to say that are no equations or code in this book, and that you can skip off to Wikipedia on your phone if you want to deep dive on something. (I did this a couple of times, for example to learn more about Apache Arrow, which was new to me.) There are also pull-outs that explain concepts like "embarrassingly parallel" that might be unfamiliar to people.
Highly recommended if you are working with data, BI, analytics, machine learning, etc. You could walk in to a job (my job, for instance) in analytics or business intelligence and be up to date on the latest trends at a high level, with some vendor management tips thrown in for good measure. Not wild about the list of vendors in Chapter 9, but that's something I'd rather discuss over a cup of coffee. Buy five copies for your company.
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