As organizations around the world and across all fields look to capitalize on the growth potential of data science, data literacy is set to become an essential skill during the next decade. Here, dunnhumby’s Vijay Balaji Madheswaran explores the history of data science, and looks towards a future in which everyone needs to talk the language of data.
Back in the early 1990s, commercial data science was still in it’s infancy. In fact, even the term “data science” didn’t really exist at that point – not in the common lexicon, at least. At that point, the skill of extracting knowledge from large datasets and using it to solve high-dimensional problems was a niche one, reserved only for a select few at the leading edge of mathematics and computing.
Over the course of the next two decades, the number of people in possession of these specialized skills continued to grow. As businesses started to become cognisant of the competitive advantage that data analytics could provide, commercial interest – and vacancies for talented professionals – soared. Very quickly, data science changed from an isolated pursuit to a vital tool, and companies of all kinds naturally rallied behind the people who could wield it effectively.
The awakening of the corporate world to the potential of data science wasn’t the only driving force during that time, however. Running in parallel was a significant improvement in our ability to cheaply house and process vast amounts of data, driven by huge advances in storage and computation. As our own capability to exploit data continued to grow, technology improved in tandem, allowing us to augment our skills further still.
20 years of rapid progress leads us to today, an age in which data science has developed an almost cult-like status. Greater access to tools and learning means that data science has now become a sought-after career path, and a prestigious one, too. At the start of the past decade, the Harvard Business Review dubbed data science as “the sexiest job of the 21st Century”1, and pondered a future in which data professionals might eventually be so in demand that shortages would eventually loom.
That speculation was not, as it happens, unwarranted. In the past few years, we’ve begun to see a clear gap emerging between the supply and demand of skilled workers: there are now three times as many job postings in the data field than there are job searches2.
As demand for qualified data professionals has grown, however, we’ve also seen something of a democratization in what it means to be a data scientist. Most people who handle data today, whether in large volumes or small chunks, are involved in data science to at least some degree. Computational modelling for software development, financial or operational modelling, even sales forecasts – they all require at least some degree of data science ability.
This has given rise to a group of people that can best be referred to as “citizen data scientists”.
These “citizens” aren’t data scientists by trade. While they might need to generate models using advanced diagnostic analytics or predictive and prescriptive capabilities, their actual role sits outside of the field of statistics and analytics. Instead, citizen data scientists can be found in areas such as finance, sales, operations, and more. In the same way that most of us now use computers at work but aren’t computer scientists, citizen data scientists use data science to get their job done, even though it’s not their full-time vocation.
As the number of people sitting in those roles continues to grow, some of the responsibilities that today’s data scientists bear are likely to be passed down to that secondary group. That’s in addition to automation, which will take on a significant portion of a data scientist’s traditional workload by itself.
If their work is being filtered down to other parties then, does that mean that data scientists will disappear? Far from it. Instead, I believe that we’re on the cusp of an age in which we fundamentally change what it means to be a data scientist. Just as the role began with specialists and niche interests, the democratization of data science will free up highly skilled professionals to focus on delivering true value – something I’ll touch on more in my next post in this series.
Making this vision a reality, of course, means that we need to ensure that our citizen data scientists have everything they need to thrive. The key to that is data literacy, and the priority now should be on providing everyone in an organization with the capability to read, understand, and communicate through data.
I think that there are seven key areas that businesses need to address in order to make that happen.
By the end of this decade, data science will become a universal skill – one that stands alongside the likes of mathematics, basic statistics, and computing in terms of its ubiquity. As we move into the decade of data literacy, we all have a responsibility to ensure that we’re speaking the same language.
Vijay Balaji Madheswaran is Director of Applied Data Science for dunnhumby APAC. Focused on investment, partnership, access, and customization, Vijay is passionate about helping Retailers and Brands realize the full value of their data.
Cookie | Description |
---|---|
cli_user_preference | The cookie is set by the GDPR Cookie Consent plugin and is used to store the yes/no selection the consent given for cookie usage. It does not store any personal data. |
cookielawinfo-checkbox-advertisement | Set by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Advertisement" category . |
cookielawinfo-checkbox-analytics | Set by the GDPR Cookie Consent plugin, this cookie is used to record the user consent for the cookies in the "Analytics" category . |
cookielawinfo-checkbox-necessary | This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary". |
CookieLawInfoConsent | The cookie is set by the GDPR Cookie Consent plugin and is used to store the summary of the consent given for cookie usage. It does not store any personal data. |
viewed_cookie_policy | The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data. |
wsaffinity | Set by the dunnhumby website, that allows all subsequent traffic and requests from an initial client session to be passed to the same server in the pool. Session affinity is also referred to as session persistence, server affinity, server persistence, or server sticky. |
Cookie | Description |
---|---|
wordpress_test_cookie | WordPress cookie to read if cookies can be placed, and lasts for the session. |
wp_lang | This cookie is used to remember the language chosen by the user while browsing. |
Cookie | Description |
---|---|
CONSENT | YouTube sets this cookie via embedded youtube-videos and registers anonymous statistical data. |
fs_cid | Set by FullStory to correlate sessions for diagnostics and session consistency; not always set. |
fs_lua | Set by FullStory to record the time of the user’s last activity, helping manage session timeouts. |
fs_session | Set by FullStory to manage session flow and recording. Not always visible or applicable across all implementations. |
fs_uid | Set by FullStory to uniquely identify a user’s browser. Used for session replay and user analytics. Does not contain personal data directly. |
VISITOR_INFO1_LIVE | Set by YouTube to estimate user bandwidth and improve video quality by adjusting playback speed. |
VISITOR_PRIVACY_METADATA | Set by YouTube to store privacy preferences and metadata related to user consent and settings. |
vuid | Vimeo installs this cookie to collect tracking information by setting a unique ID to embed videos to the website. |
YSC | Set by YouTube to track user sessions and maintain video playback state during a browser session. |
yt-remote-device-id | YouTube sets this cookie to store the video preferences of the user using embedded YouTube video. |
yt.innertube::nextId | This cookie, set by YouTube, registers a unique ID to store data on what videos from YouTube the user has seen. |
yt.innertube::requests | This cookie, set by YouTube, registers a unique ID to store data on what videos from YouTube the user has seen. |
_ga | The _ga cookie, installed by Google Analytics, calculates visitor, session and campaign data and also keeps track of site usage for the site's analytics report. The cookie stores information anonymously and assigns a randomly generated number to recognise unique visitors. |
_ga_* | Set by Google Analytics to persist session state. |
_gid | Installed by Google Analytics, _gid cookie stores information on how visitors use a website, while also creating an analytics report of the website's performance. Some of the data that are collected include the number of visitors, their source, and the pages they visit anonymously. |
_lfa | This cookie is set by the provider Leadfeeder to identify the IP address of devices visiting the website, in order to retarget multiple users routing from the same IP address. |
Cookie | Description |
---|---|
aam_uuid | Set by LinkedIn, for ID sync for Adobe Audience Manager. |
AEC | Set by Google, ‘AEC’ cookies ensure that requests within a browsing session are made by the user, and not by other sites. These cookies prevent malicious sites from acting on behalf of a user without that user’s knowledge. |
AMCVS_14215E3D5995C57C0A495C55%40AdobeOrg | Set by LinkedIn, indicates the start of a session for Adobe Experience Cloud. |
AMCV_14215E3D5995C57C0A495C55%40AdobeOrg | Set by LinkedIn, Unique Identifier for Adobe Experience Cloud. |
AnalyticsSyncHistory | Set by LinkedIn, used to store information about the time a sync with the lms_analytics cookie took place for users in the Designated Countries (which LinkedIn determines as European Union (EU), European Economic Area (EEA), and Switzerland). |
bcookie | LinkedIn sets this cookie from LinkedIn share buttons and ad tags to recognise browser ID. |
bscookie | LinkedIn sets this cookie to store performed actions on the website. |
DV | Set by Google, used for the purpose of targeted advertising, to collect information about how visitors use our site. |
ELOQUA | This cookie is set by Eloqua Marketing Automation Tool. It contains a unique identifier to recognise returning visitors and track their visit data across multiple visits and multiple OpenText Websites. This data is logged in pseudonymised form, unless a visitor provides us with their personal data through creating a profile, such as when signing up for events or for downloading information that is not available to the public. |
gpv_pn | Set by LinkedIn, used to retain and fetch previous page visited in Adobe Analytics. |
lang | Session-based cookie, set by LinkedIn, used to set default locale/language. |
lidc | Set by LinkedIn, used for routing from Share buttons and ad tags. |
lidc | LinkedIn sets the lidc cookie to facilitate data center selection. |
li_gc | Set by LinkedIn to store consent of guests regarding the use of cookies for non-essential purposes. |
li_sugr | Set by LinkedIn, used to make a probabilistic match of a user's identity outside the Designated Countries (which LinkedIn determines as European Union (EU), European Economic Area (EEA), and Switzerland). |
lms_analytics | Set by LinkedIn to identify LinkedIn Members in the Designated Countries (which LinkedIn determines as European Union (EU), European Economic Area (EEA), and Switzerland) for analytics. |
NID | Set by Google, registers a unique ID that identifies a returning user’s device. The ID is used for targeted ads. |
OGP / OGPC | Set by Google, cookie enables the functionality of Google Maps. |
OTZ | Set by Google, used to support Google’s advertising services. This cookie is used by Google Analytics to provide an analysis of website visitors in aggregate. |
s_cc | Set by LinkedIn, used to determine if cookies are enabled for Adobe Analytics. |
s_ips | Set by LinkedIn, tracks percent of page viewed. |
s_plt | Set by LinkedIn, this cookie tracks the time that the previous page took to load. |
s_pltp | Set by LinkedIn, this cookie provides page name value (URL) for use by Adobe Analytics. |
s_ppv | Set by LinkedIn, used by Adobe Analytics to retain and fetch what percentage of a page was viewed. |
s_sq | Set by LinkedIn, used to store information about the previous link that was clicked on by the user by Adobe Analytics. |
s_tp | Set by LinkedIn, this cookie measures a visitor’s scroll activity to see how much of a page they view before moving on to another page. |
s_tslv | Set by LinkedIn, used to retain and fetch time since last visit in Adobe Analytics. |
test_cookie | Set by doubleclick.net (part of Google), the purpose of the cookie is to determine if the users' browser supports cookies. |
U | Set by LinkedIn, Browser Identifier for users outside the Designated Countries (which LinkedIn determines as European Union (EU), European Economic Area (EEA), and Switzerland). |
UserMatchHistory | LinkedIn sets this cookie for LinkedIn Ads ID syncing. |
UserMatchHistory | This cookie is used by LinkedIn Ads to help dunnhumby measure advertising performance. More information can be found in their cookie policy. |
yt-remote-connected-devices | YouTube sets this cookie to store the video preferences of the user using embedded YouTube video. |
_gcl_au | Set by Google Tag Manager to store and track conversion events. It is typically associated with Google Ads, but may be set even if no active ad campaigns are running, especially when GTM is configured with default settings. The cookie helps measure the effectiveness of ad clicks in relation to site actions. |