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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 decline: 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 you
- See how cloud computing completely changes the economics of analytics
- Harness the power of Hadoop and its ecosystem
- Find out why Apache Spark is everywhere
- Discover the potential of streaming and real-time analytics
- Learn what Deep Learning can do and why it matters
- See how self-service analytics can change the way organizations do business
Corporate actors at all levels of responsibility for analytics: analysts, CIOs, CTOs, strategic decision makers, managers, systems architects, technical marketers, product developers, IT personnel, and consultants.
- Sales Rank: #707834 in Books
- Published on: 2016-08-28
- Released on: 2016-08-28
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x .64" w x 6.10" l, .0 pounds
- Binding: Paperback
- 262 pages
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5 of 5 people found the following review helpful.
A good read and food for thought if you make a living in the analytics world
By Phil
I picked up Dinsmore’s book a few days ago and thought I would leave my impressions. Note this is not a review! First, I really enjoyed the history of the analytics platforms. The second and third chapters were very informative (History and Open Source respectively) and I learned a few things!
Regarding Open Source, I agree that we will see Python supplant R as the “go to language” for analytics in the Open Source arena. It might take a few years but if my customers interests are indicative of this trend, it will happen.
Dinsmore does an admirable job in Chapter 4 on Hadoop. This chapter is fairly dense reading for me mainly because there are a lot of terms and definitions in this chapter. If you were ever looking for an overview of the Hadoop ecosystem, this is probably a good start.
The other chapter I really liked was Chapter 6. This chapter deals with streaming analytics and I believe we are just in the infancy of this revolution. Smart Cities will be a very visible platform for many people to see and benefit from streaming analytics.
I would like to see in a future edition a presentation of the role of the analytics workstation and flash memory in the analytics framework. Data Scientist who are developing algorithms and processing data are often using workstations in lieu of servers. Perhaps even a few pages on how nVidia is revolutionizing the analytics world with CUDA processing on high power workstations. I think I would enjoy that.
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