This week in data – 16th November

It’s the issue that more businesses are struggling to solve: how to value their data sets.

Now, it seems like we’re finally heading towards an answer.

A new piece at Forbes has put forward some ideas for how businesses can start identifying an accepted method for putting a dollar sign on data. The piece, written by Gartner, refers to six different methods for valuing information:

  • Intrinsic value
  • Business value
  • Performance value
  • Cost value
  • Market value
  • Economic value

Each of these are unique and apply to only certain circumstances. But as the piece itself argues, picking one puts a business on a better path to actually valuing their data accurately.

Meanwhile, a new piece in the Australian Financial Review also took on the problem to somehow connect information with a valuation method. Except this time, it’s all about tax.

It poses a question: how can society come up with a new taxation method when most wealth in the future will be concentrated in intellectual property, not physical assets?

One possible solution, it posits, is taxing consumption of information: “consumption of online goods and services is what generates the user data that companies can then monetise”. The only problem is exactly what the Forbes article attempted to address, which is how can businesses actually determine the true value of the data they collect?

Creating a new taxation method in a data-led world won’t be easy, the AFR argues. But it does offer one way forward.

In other news:

Bill Gates is known for his generosity in fighting disease. In a personal blog post, Gates wrote about a number of different ways he intends to start diverting his own resources to help fight Alzheimer’s.

One of those ways is by gathering the data used in studies, or holed up in pharmaceutical company walls that is currently inaccessible.

“We should compile this data in a common form, so that we get a better sense of how the disease progresses, how that progression is determined by gender and age, and how genetics determines your likelihood of getting Alzheimer’s,” he says. “This would make it easier for researchers to look for patterns and identify new pathways for treatment.”

Using data to solve massive medical and social problems is also on the agenda at Princeton, which has just announced the success of an experiment that uses information to help the wellbeing of children living in poverty.

As part of a challenge, scientists around the world were asked to look through 54 million data points collected through a separate study. They were tasked with predicting trends like grade point averages in disadvantaged children, or to find correlations that could help influence policy decisions at various government levels.

“Ultimately, the goal of this community-generated model is to provide policymakers with information that could help spark new theories about how to improve the lives of future generations of disadvantaged children,” the article states.

The results of the experiment are already showing fruit: highlighting again that the benefits of big data extend far beyond the corporate realm into society as a whole.

Worth a read:

Many organisations get overwhelmed when it comes to deciding what data they need to analyse, and why. This piece gives you a primer on how to avoid burnout and stop gathering irrelevant information that will just bog you down. Tech Republic.

Artificial intelligence is the buzzword tech companies – and many companies outside of tech – are chasing after. But in order to utilise great AI businesses need to get their data foundations right first, and it isn’t happening. ZDNet.

Until next week.

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