Tag Archives: Big Data

Why the Internet of Things will change how you interact with customers

Originally published on SAS Voices.

Internet Of ThingsThere’s a lot of talk right now about the Internet of Things and how it’s likely the prime catalyst for the digital transformation of organizations over the next few years. Billions of sensors, and devices with sensors, all generating data in a hyper-connected world where it can be easily shared or transmitted – what could possibly go wrong?

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Will fluid and flowing big data be more important than stationary and at rest big data?

Originally posted on SAS Voices

MotionIt’s time. The first of the big data V’s, volume, seems to be coming under control technology wise, even if that technology has not been implemented everywhere. Prices of disks and memory are tumbling and the introduction of technologies, such as Hadoop, are making vast amounts of data cheap to store.

On top of that, numerous technologies have made it easier to process and manage that massive volume of data. In short, the technologies and tools organizations need to deal with the problem of volume are now readily available.

Just when it seemed we could all take a small break from the big data assault on our organizations, since now we can store and process massive amounts of data, the second V, velocity, is gaining in importance – and most organizations are not ready.

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Four levels of Hadoop adoption maturity

Originally published on SAS Voices

So you’ve been monitoring or are already on the journey with Hadoop — and you’re wondering: Where are we on the adoption curve compared to the market in general?

Based on my interactions with numerous companies, I want to share what I think that curve looks like so that you can orientate your organization and decide if you’re leading the way or lagging behind. Neither is inherently bad, but you do need to be conscious of where you are and why.

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Want to profit from Hadoop? Consider these 4 reasons for developing a big data innovation lab

Originally posted on SAS Voices.

How can you use an innovation lab to be as agile and innovative as a startup? Are there different types of innovation labs and if so what is the difference?

I answered these two questions in previous posts, and now I will answer a third pressing question: how can you build the business case once you’ve decide to develop an innovation lab?

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The tale of two innovation labs for big data

Originally published on SAS Voices

Recently I have been out speaking with a number of organizations about the idea of the innovation lab concept , which I discussed in a previous blog post, as the way to unleash the power of big data and make even the largest of companies as agile as a start-up. During my discussions there are a couple of things that I am observing, that I wanted to share with you, since it seems there are different types of innovation labs in organizations:

  1. Many companies have something I am going to label an IT innovation lab where they are experimenting with “big data” technologies. These IT innovation labs are NOT the same as the “data related” innovation lab that companies need to put in place to remain agile in this new digital world. The focus of the IT innovation lab is to test the technology and its integration whereas the focus of the “data related” innovation lab is to test hypothesis around mashups of data and different analytical approaches In the digital world, information gleaned from data is your best competitive weapon, and speed is a critical component to your success.  It is my opinion these should be separate and distinct in a companies strategy as each has a role to play. This post will focus on the tale of two labs and how they differ.
  2. Tight budgets, and the significantly different focus of the “data focused” innovation lab, are causing organizations to ask for support to obtain funding given it is generally a new concept to not have a concrete business problem solved as part of asking for an investment. A second post in this series will focus on how I suggest organizations can build the business case for the data focused innovation lab which I believe is vital to the future success of all organizations no matter how large or small they are.

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