Take the Training Wheels off Your Big Data
Are you maximizing the value of Big Data? Are you generating powerful business insights? Are you able to analyze critical data on the fly regardless of where it’s generated within your business ecosystem?
Does your Big Data environment look like this?
Instead of this?
Both will get you where you’re going, but nobody would confuse the two.
Tradition Data Warehouses
Despite the recent hype, Big Data is not truly a new concept. Setting the Wayback Machine to 1991, I had the privilege of meeting Dr. Phil Neches, one of the pioneers of this discipline. Dr. Neches helped invent this stuff 30 years ago! But trying to compare a traditional Data Warehouse to today’s Big Data and Analytics solutions, although they are conceptually similar, is like comparing a child’s first bike to a 150-mph sport bike. They are vastly different to operate, they are designed for different purposes, and they yield significantly different results. Per Big Data analyst Mark Twain, “tis the difference between the lightning bug and the lightning.”
Don’t get me wrong. Data Warehouses have their place and are valuable business assets. But they rely on very clean, high-quality information that’s easily manipulated by relational databases, which expect to receive uncompromisingly consistent data. Unfortunately, the world has become a much messier place. Today, everything generates data — including that motorcycle, which uses IoT sensors to predict and correct for “rider exuberance.”
The Next Generation of Big Data
Modern IT is characterized by distributed computing environments and such volumes of data we never dreamed of back in 1991. We must now deal with inconsistent data types coming from almost everywhere. Is it Hot data? Warm data? Cold data? Is it noise that can be ignored, or an indicator of an impending trend or opportunity? How do we collect, compare, and analyze massive amounts of disparate data to make informed, real-time decisions before our competitors pass us in the fast lane?
Tradition Data Warehouses
Despite the recent hype, Big Data is not truly a new concept. Setting the Wayback Machine to 1991, I had the privilege of meeting Dr. Phil Neches, one of the pioneers of this discipline. Dr. Neches helped invent this stuff 30 years ago! But trying to compare a traditional Data Warehouse to today’s Big Data and Analytics solutions, although they are conceptually similar, is like comparing a child’s first bike to a 150-mph sport bike. They are vastly different to operate, they are designed for different purposes, and they yield significantly different results. Per Big Data analyst Mark Twain, “tis the difference between the lightning bug and the lightning.”
Don’t get me wrong. Data Warehouses have their place and are valuable business assets. But they rely on very clean, high-quality information that’s easily manipulated by relational databases, which expect to receive uncompromisingly consistent data. Unfortunately, the world has become a much messier place. Today, everything generates data — including that motorcycle, which uses IoT sensors to predict and correct for “rider exuberance.”
The Next Generation of Big Data
Modern IT is characterized by distributed computing environments and such volumes of data we never dreamed of back in 1991. We must now deal with inconsistent data types coming from almost everywhere. Is it Hot data? Warm data? Cold data? Is it noise that can be ignored, or an indicator of an impending trend or opportunity? How do we collect, compare, and analyze massive amounts of disparate data to make informed, real-time decisions before our competitors pass us in the fast lane?
Get more information about the Cisco-MapR solution.
Responding to this challenge requires 3 elements:
- Powerful, integrated infrastructure such as Cisco UCS, that combines scalable compute and storage with super-fast connectivity and world-class security.
- An open, Converged Data Platform, integrating the power of Hadoop and Spark with global event streaming, real-time database capabilities, and innovative data applications.
- And of course, experienced consulting and integration services to design and implement an elegant architecture that maximizes performance, improves business continuity, and ultimately lowers your total cost of ownership.
That may sound like a lot to take in, but with the right partners all you need to worry about is whether your Data Centre is ready to take off its Big Data training wheels and put on its big boy boots. Your partners will do the rest.
If so, Cisco, MapR, and Benchmark Corp., wish to invite you to our executive seminar about overcoming the limitations of traditional data warehouse technology, and instead, generating competitive value from Big Data, the Next Generation Data Warehouse.
April 12, 2017
Breakfast is 8:30am – 9:00am
Seminar is 9:00am – Noon
Location:
Cisco Systems Canada, Executive Briefing Centre
Waterpark Place, 88 Queens Quay West, Suite 2900
Toronto, ON M5J 0B8
Click here to register. I hope to see you there. In the meantime, I have a bike to ride (not saying which one).
Tags:- Big Data
- Cisco
- cisco big data
- cisco blog
- cisco canada
- Cisco Canada blog
- cisco data centre
- data center
- Data Centre
- UCS
