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The 5 Phases of Big Data Adoption

Denial. Resistance. Acceptance. Embrace. Survival.

When talking about BigData adoption we must consider it at least from 2 perspectives: companies and end users. And for both cases adoption seems to be going through the same 5 phases listed above: denial, resistance, acceptance, embrace, survival.

Let’s firstly imagine how the 5 phases of big data adoption look for companies:

  • denial or there’s no such thing as BigData. Even if BigData is talked about for years and Google has been mentioning it in connection with all their technologies and solutions, not everyone believes there’s something called BigData. Maybe also the lack of a definition is helping with the denial. But when facing the 3 V’s: volume, variety, velocity— or even the 4 V’s: volume, velocity, variability, variety—you should recognize that its BigData.

  • resistance. Preparing for BigData is expensive and the results are uncertain. So who can guarantee the return on investment?

  • acceptance. Firstly it was only Google doing it. Now it is every other startup. So there must be something about it.

  • embrace: a whole (new) ecosystem is building around BigData. Once you have the data you can start making sense of it. But you need the data first and you better start collecting it instead of waiting for off-the-shelf technologies.

  • survival: the moment when the investments of the company in collecting, storing, analyzing Big Data start paying off.

For users the 5 phases of big data adoption are a bit more complicated:

  • denial: WTF is BigData and why would I care?

  • resistance: What is it for me?

    Users are asked to give away more and more information but what they are getting back is not so obvious. Take Facebook as an example: it’s encouraging users to share more information about themselves and in an as public as possible way. On the other hand, under the umbrella of protecting privacy, Facebook doesn’t share that information (even if you want it to) with anyone else except their advertising clients.

  • acceptance: all my friends are OK with sharing more data and it doesn’t seem to do them any harm. Not to mention that all the companies collecting my data are anonymizying it, so there’s nothing to worry about. Right?

    Unfortunately this is not completely true and Pete Warden’s post is an eye opener:

    Something that my friend Arvind Narayanan has taught me, both with theoretical papers and repeated practical demonstrations, is that this anonymization process is an illusion[1]. Precisely because there are now so many different public datasets to cross-reference, any set of records with a non-trivial amount of information on someone’s actions has a good chance of matching identifiable public records.

  • embrace: the light at the end of the tunnel is too bright to ignore it. The promises you hear are too appealing. So you open the gates: you share your location, your habits, you add sensors and collect data from your house and car, you authorize your bank to share your data.

  • survival: as for companies, you start to see the benefits: no more absurd ads when browsing, no more hidden fees from your bank account, reduced household costs.

The moment when BigData starts to pay back looks like a movie happy end with everyone benefiting from it. Not only those producing it, not only those monetizing it, not only those storing and processing it. But everyone.

Next exercise: Big Data Hype Cycle.


  1. My emphasis.  

Original title and link: The 5 Phases of Big Data Adoption (NoSQL database©myNoSQL)