Decoding the Data Journey

For many businesses, the data journey begins and ends with a spreadsheet. But what happens when you hit the limits of Excel? How do you build a truly data-literate workforce capable of driving real strategy?

In this Episode of The BPP Digital Edge, host Idris Fabiyi sits down with Donna Kane, Programme Lead for Data at BPP, to map out the modern data journey. They uncover a "quiet revolution" where the most impactful data professionals aren't new graduates, but experienced employees being upskilled with foundational data skills.

In this episode, you will learn:

• The key milestones in the evolution of data tools, from Excel's dominance to the rise of Power BI.
• Why the typical data apprentice is often an experienced professional looking to level up, not a school leaver.
• A clear breakdown of what a "Data Technician" apprenticeship actually involves.
• The essential skills-from AI awareness to security-that data professionals need for the future of work.
• Donna's single most important piece of advice is for any organisation beginning its data transformation.

Tune in to discover how to unlock the hidden data potential that already exists within your team.

Episode Transcript

SPEAKER_00 (00:00):
Welcome to the BPP Digital Edge, the podcast where
we explore how big ideas createreal world impact.
And I'm your host, Idris Fabie,Head of Innovation and
Technology at BPP University,School of Technology.
Now in this episode, I want usto have a think about the data

(00:22):
revolution.
When we say data revolution,what comes to mind?
Who comes to mind?
Do you think it's a young codersat behind a desk writing
queries?
Or do you think it's someonewriting complex algorithms or
writing all manner of complexscripts and coding?
Or maybe you're thinking it's agraduate.

(00:44):
Maybe you think it's a graduatewho's never known a world
without AI and thinks everythingis attached to a script or a
prompt.
But what if I told you that thereal story is happening
somewhere else?
What if the most important datatransformations aren't just
happening for the nextgeneration, but for the
professionals who are already intheir careers, just looking to
level up?

(01:06):
Well, today's guest sees thisreality every single day.
Today, I'm delighted to bejoined by Donna Kane.
Donna, is the level three andlevel four program lead for our
data courses.
She's helping to lead this quietrevolution.
Donna shares the interestingfact that a large number of
people learning foundationaldata skills today are actually

(01:27):
experienced professionalslooking to upskill.
So in this episode...
We're not just talking about thejourney from Excel to AI.
We're talking about the peoplemaking that journey and the
skills that truly matter and howit's never too late to become a
data professional.
So stick around.
This one's going to beinteresting.

(01:55):
So Donna, tell us aboutyourself.

SPEAKER_01 (01:58):
So my name is Donna Kane.
I am the level three dataprogram lead.
I originally joined SGO trainingback in 2021, where I came in as
a hybrid role, contentdevelopment for the new level
three data technician standard,a technical trainer and skills

(02:19):
coach all at once.
So that was quite an intensefirst year.
I ended up being the programlead probably about 18 months,
two years after that to developthe curriculum further.
Subsequently transferred over toBPP a little over two years ago
and I'm now program lead acrossthe Firebrand, SGO and BPP for

(02:44):
the level three data technicianprograms and I'm proud to say
that within the School ofTechnology at BPP it is one of
the largest programs so it'sdone really well.

SPEAKER_00 (02:55):
Thank you for that.
So how has the way we work withdata today, how's it evolved in
the early days of Excel?

SPEAKER_01 (03:05):
Probably size of data storage and how we interact
with it and the tools, theextent of the tools we utilize.

SPEAKER_00 (03:15):
Fantastic.

SPEAKER_01 (03:16):
Expanded.

SPEAKER_00 (03:16):
So for yourself then, given your experience, why
do you think Excel was such agame changer?

SPEAKER_01 (03:25):
It's intuitive.
It's user-friendly.
It is a mainstream tool, as inobviously the Microsoft Suite
side of things.
Everybody has access to it.
It is open to multiple formatsof data, types of data, and it

(03:46):
constantly reviews itself anddoesn't stay put.
It's constantly evolving,listening to people's feedback
and is on a continuous wheel ofimprovement.
So it's like you blink andsomething else has changed.
So it's ever evolving.

SPEAKER_00 (04:07):
I've been an avid user of Excel myself.
And one thing I would say isjust its ability to visualize
the data that you can give itvery, very quickly.
But what do you think some ofthe key milestones have been
in...
the way we use Excel today?

SPEAKER_01 (04:29):
I think the way it's evolved its sort of function and
formula library to adapt toefficiency.
Some of the formulas that youused to have to create back
before some of the moreintelligent formulas and
functions came into play was solong-winded and complex and

(04:51):
complicated.
It laid it up to for syntaxerrors all the time and formulas
breaking and not working and theinvolvement of the functions and
formulas into sort of the mostrecent range of like dynamic
arrays for example have justmassively improved efficiency
and how we can actually presentwhat our data looks like whether

(05:15):
it's in tabular format or somesort of visualization format I
think it's just improved us asindividuals and prevents that
human error tripping up.

SPEAKER_00 (05:27):
Fantastic.
And when do you start movingbeyond spreadsheets?
As in what prompted the shiftthat spreadsheets was really
good and now we need more?
When do you think that was?
Or what do you think that was?

SPEAKER_01 (05:42):
Probably...
Early 20,000, sort of like 2010,a little bit before then, sort
of 2007 type of thing, where itstarted to come past more just a
table of data.
And that's where you started tosee the evolvement of
functionalities within the toolitself, leaving you set up to be

(06:04):
a bit more creative with the wayyour data looks.

SPEAKER_00 (06:07):
And I remember Microsoft Access.
I don't know if you've hadthe...

SPEAKER_01 (06:12):
Never had the pleasure

SPEAKER_00 (06:13):
of Access.
Access was wonderful.
And I remember at anorganization I used to work for,
they had an Access database.
And I would say that the needfor the Access database really
was we'd reached the limit thatwe could do with Excel.
Excel was really good, but Ithink we had something, I'd hate

(06:36):
to guess, but it was in thethousands of records inside of
Excel.
And after a bit, I think it justbecomes, the data becomes unreal
and you can't really extract theinsights that you really

SPEAKER_02 (06:50):
want

SPEAKER_00 (06:50):
out of Excel.
So we moved over to Access.
And Access was a really goodtool at the time.
So it was a really good steppingstone.
But in terms of visualization,what role do you think
visualization platforms likeTableau and Power BI play in the
way that non-technical peoplesee data?

SPEAKER_01 (07:14):
I think the interactivity, people who don't
need the skill set necessarily,as long as there's clear
guidance within the dashboarditself, for example, whether
it's labeling or instructionsfor that non-technical universe,
it becomes, because of theinteractivity of Power BI or
Tableau, for example, it allowsfor those non-technical users to

(07:36):
be able to manipulate datawithout having the skill set of
manipulating data just by theimplementation of interactive
features within a dashboardallowing them to filter and sort
or slice you know KPI metric allthose different things and it
just becomes very clear at theglance what that data is telling

(07:59):
them rather than having todecipher a pivot table then look
at the chart and bounce betweenthe two being able to create
these interactive dashboardsjust puts it on the front foot
for non-technical users as wellas technical.

SPEAKER_00 (08:15):
Absolutely and just to add on to that I think the
tools like the Tableau and thePower BI they've been really
instrumental to bridge that gapbecause I remember years ago
trying to learn R and R's justsuch an uncomfortable language
to use that it really is a bitof a blocker when it comes to

(08:40):
people taking on visualisationand creating.
You can create stunningvisualizations, as you know,
through things like that.
But when you're just very, whenit's very programmatic, it just
puts off a lot of people fromjoining the data analysis game.
start to see a real shift indecision making from intuition

(09:04):
based to data driven decisionsand AI driven, so to speak.
Where do you see this shift inthe future?

SPEAKER_01 (09:13):
I think we're just going to carry on this very
strong trajectory.
I think very rapidly we've seenin the last sort of three to
five years, even the smallest ofsmallest companies recognising
the importance and the value ofdata in an organisation I mean,
talk about a positive from anegative.

(09:34):
I think the awareness of datareally slammed home during
COVID.
Yes.

(09:59):
that awareness grow so rapidlysince like 2021, 22, when we
were all in COVID lockdown.
And I think it's that shiftbecause it's gone across all
sectors and the smallest ofbusinesses now, the importance
and the understanding and thevalue and security behind that
fact-based information ratherthan being guts and intuition.

(10:21):
Okay, you can have situationswhere you have incorrect data
gathering, which can skewresults and then you get
incorrect outputs.
But fundamentally, if If thedata's right, the insights that
you can get from that, you can'targue with the numbers, as it
were, and you can make moreinformed decisions from it.
So I do think that shift camethere.
I mean, down to one person beingthat data department in a small

(10:45):
organization.
I recently had a student onprogram that I taught.
He worked in products likematerial company, high-end sort
of supply of material, but hewas it.
He was the data person, had noidea about it.
And he was learning all theskills and taking them back to
the organization saying, look,this is what we can actually do

(11:07):
with this data.
And that was an extremely smallorganization.
So I think that value is notjust fit for the big
organizations anymore.
It's down to those smallerstartup companies or smaller
intricate companies realizingwhat their data can tell them
from customer information, etcetera, and how they can use it

(11:30):
to benefit them.
Well,

SPEAKER_00 (11:30):
that's really, really insightful that Donna.
Thank you.
Okay.
So, you know, your role as theprogram lead for data
technician, you know, I thinkjust leading on from what you
have just said there, I think itjust outlines how important your
role is because you are the, inessence, you're the direct link.
The entry.
Yeah.
The entry point for a lot ofthese organizations to become

(11:54):
data literate and to become moreresilient when it comes to
collection of the data that theydo in the processing of the
data.
What does it take for anorganization to truly build data
literacy in their workforce?

SPEAKER_01 (12:12):
Awareness of the people within the roles that are
going to be coming on toprogramme.
People think level three, entrylevel, they immediately think
school leavers and that sort ofage group.
But in actual fact, a massivepercentage of the people that
come on programme are peopleupskilling, as I talked about

(12:34):
how data is becoming importantand they don't really know how
to use it.
So they're taking people thathave potentially been in a role
for eight to 10 years, thathaven't got that full
understanding.
They probably work with Excel,but it's a niche portion that
they've needed for their job.
Self-taught, massive gaps inknowledge.
And then that understanding anddesire to make better use of the

(12:56):
data is bringing these peoplethat have been in their roles a
lot longer to get thefundamental and essential
digital skills, the data skillson program to be able to take it
back to the organization forthem to effectively use the data
that has been coming into thecompany for years.
is but they just haven't knownwhat to do with it so you're
more talking definitely over 25more in the 30 year olds bracket

(13:21):
a large portion of people comingon on program

SPEAKER_02 (13:24):
yeah

SPEAKER_01 (13:25):
so i think it's an understanding of that

SPEAKER_02 (13:28):
yeah

SPEAKER_01 (13:29):
for the forefront

SPEAKER_02 (13:30):
yeah

SPEAKER_01 (13:30):
and then solid understanding of the standard
itself okay so seeing whatexpectancies are required to
achieve the endpoint so havingan inside out understanding of
your program you have to havethat as your base you can't just
come into it not reallyunderstanding the standard

(13:52):
because you're building thecontent you're building the
program around thosecompetencies and those ksbs and
then having that awareness ofthe range of age industries
sectors that are coming on boardso that you can cater to them

SPEAKER_00 (14:08):
brilliant you know i said that's a really really
lovely answer and you knowsomething i'm always thinking of
because of our audience or notnecessarily knowing who our
audience is going to be used alot of technical apprenticeship
jargon in there so could youjust outline what when when you
say the competencies for theprogram what could you just
outline that

SPEAKER_01 (14:29):
please yeah so the apprenticeship standard requires
the individual apprentices tomeet a range of knowledge skills
and what we call behaviors inorder to meet the end point
assessment so that's a it's 16knowledges, so 16 knowledge
points that they need to learnand apply in the workplace.
And 18 skills and sixbehaviours.

(14:52):
So behaviours are more aboutwork-based sort of environment,
communications, interactivity,collaboration, initiative.
So they're your behaviours.
And then the knowledge isunderstanding how to do
something and the awareness ofhow to do it.
And then the skills is thentaking that knowledge and
physically applying the skillbased from that knowledge into

(15:15):
the

SPEAKER_00 (15:15):
workplace.
Fantastic.
Thank you.
And that's a really good seguefor my next question.
Because when we say skills,because obviously a lot of your
students leave your course withlots of skills, but what would
you say are the most importantskills for the next generation

(15:36):
of data professionals?

UNKNOWN (15:39):
Yeah.

SPEAKER_01 (15:40):
So with the program that we've obviously developing
now, it's about the awareness ofthe intelligent tools and the AI
development, the trend in AI.
It's definitely not goinganywhere.
It's becoming rapidly mainstreamnow.
And organizations that have beensort of shunned to it and closed
door on it are now realizingthat they can't.

(16:01):
So I think it's theunderstanding of those
intelligent tools, even theintelligent tools based within
Excel, for example, You'removing into things like Power
Query, which have got thoseintelligent bases.
And some of those, the patternrecognition and that sort of
thing, the algorithms aremachine learning led.
So you've definitely got AIembedded in that.

(16:22):
But then you've also gotintuitive tools, so just more
intelligent tools.
And it's about the awareness ofwhat those tools can do for
efficiency.
But then when we come to the GenAI side of things, it's about
making sure that youremployees...
So as an employer are not beingleft behind.

(16:44):
So even though they might notnecessarily utilize them as a
full-time thing within theirrole, understanding how to
effectively use these tools tokeep up with technology and
trends as the industry's move iscrucial because otherwise you're
going to find yourself withmassive gaps and being left
behind.
And then you're going to fallinto a part of competitive edge

(17:07):
changing and shifting.
If your employees haven't gotthat skill set or that awareness
even if it's just an awarenessand they don't always actually
have the ability to apply theskills the understanding and the
awareness of them i think iscrucial and i think more people
are you starting to they'rebleeding into their personal
lives as well these tools arebleeding into people's personal

(17:29):
lives as well so if we caneffectively teach those tools
you're talking about a across-party sort of skill set
both in the workplace and at andpersonal life.
So I think it's crucial foreverybody to keep, maintain
ahead of the curve, if you like,as we move forward with this.

SPEAKER_00 (17:48):
Fantastic.
You know, and that was going tobe my second question to follow
that question, which is if youcould give one piece of advice
to a team, to an organization,like you mentioned earlier, it
just doesn't apply to the largeorganizations, even medium to
small size organizations aswell.
So if you could give them onepiece of advice for starting

(18:09):
their data transfertransformation journey what
would that be

SPEAKER_01 (18:14):
ensure that you've got awareness about the security
compliance and ethics side ofthings before going full steam
into utilizing the tools becauseas amazing as these tools are
they come with a lot of risksbehind them as well so i think
understanding what you'redealing with as a tool being

(18:36):
aware of the fact that it isartificial intelligence We do
have something calledhallucination where they make
things up.
They pull links that don'texist.
So it's about having that humanvalidation of the information
that you get from these tools aswell.
So I think it's very importantto have an awareness of that
side of things as well beforefull force going into utilizing

(19:00):
the tools without thatawareness.

SPEAKER_00 (19:06):
That is absolutely wonderful.
Thank you so much, Donna.
You've been absolutelyfantastic.
I just want to ask you a fewmore quickfire questions.
Yeah, don't take too long tothink about them.
But first question, tea orcoffee?
Tea.
And what

SPEAKER_02 (19:24):
was your first computer?
ZX Spectrum.
ZX Spectrum.

SPEAKER_01 (19:33):
Soft keyboard.
Wow.
A little soft keyboard.

SPEAKER_00 (19:37):
Used to

SPEAKER_01 (19:38):
stick.

SPEAKER_00 (19:39):
The keys used to stick.
I remember I had a laptop likethat.
Lotus works.
And what's your favourite food?

SPEAKER_01 (19:49):
I had to tell one.
I think it would have to beItalian.
Nice.
Particularly, there's a dishcalled al forno, which is made
with spicy salami sausage andmozzarella.

SPEAKER_00 (20:02):
That sounds nice.
And back in school, what wasyour favourite subject?

SPEAKER_01 (20:08):
Theatre.

SPEAKER_00 (20:09):
Theatre.
Nice.
And if you could give a16-year-old version of you...
Some advice?
What would it be?
Career advice, beg your pardon.

SPEAKER_01 (20:23):
Study harder and speak to your careers officer
more because I left school andwent to the theatre school
without really planning out whatI was going to do with that
skill.

SPEAKER_00 (20:37):
Awesome.
Thank you so much.
Thank you very much for takingpart in this episode of the BPP
Digital Edge.
Awesome.
Thank you very much.

SPEAKER_01 (20:48):
Good to talk to you.
Thank you.