The future of data science looks spectacular

The future of data science looks spectacular

It wasn’t that long ago that we lived in an entirely analogue world. From telephones to televisions and books to binders, digital technology was largely relegated to the laboratory.

But during the 1960s, computing had started to make its way into the back offices of larger organisations, performing functions like accounting, payroll and stock management. Yet, the vast majority of systems at that time (such as the healthcare system, electricity grids or transport networks) and the technology we interacted with were still analogue.

Roll forward a generation, and today our world is highly digital. Ones and zeroes pervade our lives. Computing has invaded almost every aspect of human endeavour, from health care and manufacturing, to telecommunications, sport, entertainment and the media.

Take smartphones, which have been around for less than a decade, and consider how many separate analogue things they have replaced: a street directory, cassette player, notebook, address book, newspaper, camera, video camera, postcards, compass, diary, dictaphone, pager, phone and even a spirit level!

Underpinning this, of course, has been the explosion of the internet. In addition to the use of the internet by humans, we are seeing an even more pervasive use for connecting all manner of devices, machines and systems together – the so-called Internet of Things (or the “Industrial Internet” or “Internet-of-Everything”).

We now live in an era where most systems have been instrumented and produce very large volumes of digital data. The analysis of this data can provide insights into these systems in ways that were never possible in an analogue world.

Data science is bringing together fields such as statistics, machine learning, analytics and visualisation to provide a rigorous foundation for this field. And it is doing this in the same way that computer science emerged in the 1950s to underpin computing.

In the past, we have successfully developed complex mathematical models to explain and predict physical phenomena. For example, we can accurately predict the strength of a bridge, or the interaction of chemical molecules.

Then there’s the weather, which is notoriously difficult to forecast. Yet, based on numerical weather prediction models and large volumes of observational data along with powerful computers, we have improved forecast accuracy to the point where a five-day forecast today is as reliable as a two-day forecast was 20 years ago.

Share it:
Share it:

[Social9_Share class=”s9-widget-wrapper”]

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.

You Might Be Interested In

What if the LOB had digital democratization

11 Feb, 2018

Everyone is enthusiastic about the flow of insight that will be unleashed by big data and the internet of things. …

Read more

What Hiring Managers Need to Understand About Data Scientists

2 May, 2016

Michael Li recently wrote inEntrepreneur.com, “AtThe Data Incubator, I’ve spoken to hundreds of employers looking to hire data scientists — …

Read more

Not the time for standards in Open Data, yet

29 Apr, 2016

It seems with the rise of a new technology, it soon follows on the discussion on how to standardize it. …

Read more

Do You Want to Share Your Story?

Bring your insights on Data, Visualization, Innovation or Business Agility to our community. Let them learn from your experience.

Get the 3 STEPS

To Drive Analytics Adoption
And manage change

3-steps-to-drive-analytics-adoption

Get Access to Event Discounts

Switch your 7wData account from Subscriber to Event Discount Member by clicking the button below and get access to event discounts. Learn & Grow together with us in a more profitable way!

Get Access to Event Discounts

Create a 7wData account and get access to event discounts. Learn & Grow together with us in a more profitable way!

Don't miss Out!

Stay in touch and receive in depth articles, guides, news & commentary of all things data.