Nori S., Scott J. BI and Analytics on a Data Lake: The Definitive Guide

MapR Technologies, 2016.Much of the history of computing and information technology has been less than glamorous, often comprised of “business plumbing” work like payroll, HR, data storage, and the like. Then along came analytics and business intelligence (BI), precipitating a collective “Aha!” moment that reverberated from IT right through the C-suite. Here was a set of truly business-first technologies and solutions capable of optimizing decision-making to lower costs, speed time-to-market, and drive real competitive advantage, among other vital benefits. Now BI and analytics are being paired with the latest IT phenomena, big data. The impact of this union promises to be a disruptive game-changer, both for business and IT. The reason is simple. Somewhere in the area of 75% of data available to the enterprise today goes unused. This data holds the keys to a deeper, richer understanding of customers, competitors, markets, and trends.
The distinction of use cases
This book is intended to discuss BI and analytics in a capacity where the business is not yet leveraging a big data platform to build new applications to serve business needs. It is rather common for people to build brand new applications directly atop a Converged Data Platform. There are many benefits from the application development side of the house.
As new applications are built on this platform, new analytics can be applied. This brings an inherent benefit of not having to move the data between the system of record and the platform for which analytics are performed as they are one in the same. While legacy systems are still in place, coexistence is a very happy place to be, and that is the major focus of this book.BI, Analytics, and Big Data: The “A-ha!” Moment
Without tools, data is nothing but an expenseWhat you’ll learnTaming — and exploiting — the data beast
Old solutions won’t work for the new normal
BI and analytics at-a-glance
Defining terms
New Platforms Bring New Approaches
Setting the scene
Really big, big data
Brave new world of big data analytics
How we got here
RDBMS benefits package
The fox in the hen house
IT evolution, not revolution
Which platform to use?
Data warehouses
Massively parallel processing systems (MPPs)
Hadoop
Data lakes vs. data warehouses
Choices
Criteria for selecting the right big data analytics platform
Defining terms
Navigating the SQL-on-Hadoop landscape
Where SQL fits
Batch SQL
Interactive SQL
In-memory SQL
Operational SQL
The Analytics Revolution
System overload at Kobo
Analytics
Big data has opened some new options
Preparing for analytics
Analytics at the Speed of Light
The move to in-memory
What’s the deal with streaming?
The SAP HANA platform
SAP HANA Vora
Use cases
The Promise of Predictive Analytics and Machine Learning - Seeing the Future
Making educated guesses
Predictive analytics
Machine learning
Tools and terms
Your Turn - How to Make Analytics Work for You
8 Steps
The open-source equation
Big Data Analytics: How It’s Being Done in the Real World
Winning characteristics
UnitedHealthcare
TransUnion
Harte Hank
comScore
Conclusions and Recommendations