Zen and the Art of Data Maintenance: Big Data, More Data, BIG Issue

More, more, more!

We are culturally conditioned to want more. More money, more fun, more pleasure, more accomplishment, more intelligence, and yes, more data. There is an idea that if we get more, we will be happier and more successful. The need for more fuels consumerism and business.  Marketing efforts are often based on creating demand for more and for establishing that there is a lack of something— that something is missing.

Data is the new currency. As the publication, The Guardian, says, ‘Data is the new lifeblood of capitalism’[i]  and ‘Data has become the world’s most important resource.’ Yuval Noah Harari, author and historian made the same claim about data being the most important resource in the world and takes it a step further saying— he warns that whoever owns the data, owns the future. [ii]As a result, in the Big Data age, there seems to be a tendency towards wanting more data.

There is a useful Zen teaching sharing that a root cause of our difficulties come from our cravings and aversions. In other words, we have strong feelings about how we need certain things (and don’t need other things) and if these feelings are strong enough and when we don’t have these things, we suffer.

Is this true of data? Do we have a craving for data? Do organizations crave data? How much data is enough? Or is it ever enough?

A simple example of the attachment to data may be that for most people, their cell phone and its associated data is one of their most prized possessions. And we often create more data by taking pictures, videos, texting, emails, and posting on social media. Billions of IoT sensors are capturing huge amounts of data every second. The amount of data created is exponentially increasing. And there is always more data that we can capture so the pursuit of more data is often a never-ending task towards trying to fill a bottomless, unfillable bucket.

One rationale for collecting more data is the perception that it is often free. Let’s take another picture, video, share something on social media, text someone, and so on. After all, it’s free! Or is it? For example, it’s common to sign up for a retail program where we receive ‘free’ benefits and all we have to do is fill out a form, which is basically giving away data such as our contact information. Is there another price we pay for more data aside from money? Do we pay in lost privacy, in overloading our minds, in possible ways that our society becomes impersonalized?

In contrast to individuals collecting or giving away data, is it different for organizations to collect and maintain data? To stay competitive, organizations need to collect data and use it to achieve their missions. More data facilitates better models for artificial intelligence, machine learning, and data science. Many have stated that a poor data scientist with a great deal of data will create better models and results, and will outperform a great data scientist with much less data. So why not capture as much data as we can?

More Data Is Not Necessarily Better

There are many case studies and much written about this idea that more data does not necessarily produce more business value and in fact, more data may actually result in less business value.[iii] One example of this was when a utilities company was advised by a prominent consulting firm to load all of their archived data about customer bills for analysis and predictive purposes to see patterns in when customers had larger bills and used more heat. The models showed things that were pretty obvious, for example, that in colder months, people spent more on heat. The result was that the organization spent considerable time storing and managing data that didn’t help them further their mission.

Thus, instead of collecting as much data as possible in the hopes that it will help, an important question is ‘Which data is important and meaningful to capture and how can it help to achieve our purpose?’

In data science algorithms, some variables can be meaningful, but many of them will simply add complexity and confusion. Although large volumes of data can help identify what is more meaningful and true, the depth of data over time for certain variables is usually more important than collecting a great number many types of variables.

Power Versus Ethics and Morality

Information is power. In many ways, the more of this valuable resource we have, the more powerful we are. However, another consideration is to weigh the value of the data versus ethical and moral standards. 

It may be legal to collect and use data in ways that violate people’s privacy, especially when organizations say they are disclosing their privacy terms through long online agreements. But if people contractually give organizations these rights because there simply isn’t enough time to read all these privacy provision agreements whenever we need something, then it is ethical and moral to collect data at the expense of others’ privacy and security infringement?

So, is there a point when it is better not to collect data since it causes more harm than good? When bots and sensors collect data about us, many times without us even knowing, is it ethical to use this information to profile us? A key question is how much do we consider the collective whole and how this affects others when we collect and use data? Data is interesting in that unlike many assets, when we collect data, the party that provides the data to another party doesn’t lose it. However, it still affects people when data is gathered and used, so it seems that it is important to deeply consider our intentions and the consequences of collecting more and more data, as well as what data collected provides more benefit to the whole than not.

What Can We Do?

Regarding the collection of data, the most important thing we can do is to be aware. Zen is a Japanese word that means awareness. And this article about Zen and data emphasizes two key points:

  • There is a tendency to want more and more of the valuable resource called data, whether it helps or not
  • More data does not necessarily produce more business value

So, the solution to the issue of more, more, more data, even when it doesn’t help, is to be aware of this tendency to want more. Really? Just be aware? Don’t we have to do something? Of course, we also need to take appropriate actions, however, I am suggesting that we start with Zen or awareness. Ironically, the act of awareness leads to appropriate actions. If and when we become more aware of the tendency to inappropriately collect too much data or not the right types of data or with intentions that are not in the best interest of all, things will naturally change for the better and we will tend to move towards wiser actions regarding what we collect and how we use it.

[i] https://www.theguardian.com/technology/2018/jan/31/data-laws-corporate-america-capitalism

[ii] From the book, “21 Lessons for the 21st Century’, by Yuval Noah Harari

[iii] Why More Data Isn’t Always Better, By Sparta Science, April 10, 2018

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Len Silverston

Len Silverston

Len Silverston is a best-selling author, consultant, speaker and internationally acclaimed expert and thought leader in the fields of data governance, data modeling, data management, and in the human dynamics of integrating information data. He is the author of The Data Model Resource Book series (Volumes 1, 2, and 3), which describe hundreds of reusable data models. The volume 1 book was rated #12 on the Computer Literacy Best Seller List and his volume 1 and 2 books have been translated into Chinese and in 2009, he co-authored “The Data Model Resource Book, Volume 3, Universal Patterns for Data Modeling”, which has been translated into Korean. Mr. Silverston has published many articles and has been a keynote speaker at many international data conferences. He is the winner of the DAMA (Data Administration Management Association) International Professional Achievement Award and the DAMA International Community Award. He has given many keynotes and has received the highest speaker rating at several international conferences. Mr. Silverston's company, Universal Data Models, LLC, http://www.universaldatamodels.com provides consulting, training, publications, and software to enable information integration as well as people integration. - He is also a personal and corporate mindfulness coach, trainer, and teacher and has studied and taught many forms of spirituality and life development skills for over thirty years. He has attended, staffed and/or led hundreds of days of silent, intensive retreats as well as dozens of life development workshops. After intensive practice in Zen, he was ordained as a Zen Priest in 2011. ‘Kensho’ Len Silverston provides ongoing ‘Zen With Len’ (http://www.zenwithlen.com) individual and corporate coaching, seminars, meditation gatherings, and retreats.

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