So I'm going to talk about um something I feel very passionate about. I've, I'm Val Klein back. I'm um from South Africa. Um And I've been in the Business Intelligence Space for the last 17 years, but I started my career really as a co um software developer.And um um so I just want to talk about something that I'm passionate about because what I'm passionate about is change. And I feel that in, in my field as a software developer, I mean, you know, you have to learn and grow and um and, and the other thing I'm very passionate about is obviously seeing women grow in our industry. So my topic is about what has changed about last from the last year to this year in the data analytics space. If not everything, what I, what I'm going to talk about is the evolution of business intelligence. And for me, um in the last 17 years, I've watched B I go from first generation to second generation to third generation. So what I'm gonna talk about in first generation, we really spoke, looked about and we, we dealt with um central centralization of it. We talked about and we saw the different technologies, Ola cubes, cognos. When I started developing, we looked at cognos cubes um and everything was centralized and we had to wait for it and to develop solutions, we had a question and then we had to wait.

And then we were looked at third generation B I and third generation really talks about um democratized new data. We want data on real time and we want dates to be available on prem and on cloud. So I in my career, I've worked through 1st, 2nd and 3rd generation B I. So now we are at the fourth wave of business intelligence. And why I say we are at the fourth wave is because what is driving the fourth wave really is data modernization and we're talking about data integration because um as a B I developer or solutions architect, I always feel that everybody can develop A B I um solution, right? We have power B I, we have click, we have tableau but I think what really is driving the fourth wave of business intelligence is how do we integrate our data? How do we scale our data? Because we're not talking about structured data, we're talking about unstructured data. And I think this is what this is where my passion comes in as a, as a a solutions architect. So what what really is driving the this trend of data integration is moving data to the cloud. We want faster we want fast application development, we want scalability and we want elasticity, we want to be able to do things on real time in the cloud. And we want to really modernize um our legacy systems.

And I think that is one of the things that is driving our cloud application development. The second part is that with data warehousing, you know, when we build

solutions in business

intelligence, data and analytics, we talk about a data warehouse, but we all know that a lot of work in modeling and data warehouse comes in your etl. And so we want to automate this process and we want to be able to develop

solutions and automate it so that we can have faster delivery because we want to move to delivery and

solutions. And that is why we also look at data lakes because Data Lakes really accommodates your unstructured data. We want to accommodate and leverage artificial intelligence, machine learning. Um

internet things for

me, the idea of business intelligence or data analytics is really to be able to make business decisions at the speed of business, right? Because because business and data is changing all the time. Um So what we

when we look at this,

the trends that are driving data analytics

in 2022 we

look at Data lakes, it's not a part of data warehouse anymore. We want to leverage the power of of building a data lakes and we need to understand why a data lake. Um We want to need to demarcus data science. We also want to focus on right data, not big data. Uh There was a huge drive about big data but now we want to the shift is more towards right data. We also

want to look at data analytics in a place. Data analytics

will dominate

in the business processes because

we cannot measure what we don't understand. And we can't, if we don't understand how our business is doing, we cannot be, we won't not be profitable and we cannot be um predict um or analyze our information or just have a strategy. And then data fabric is a new um I enterprise it trend and I'll speak a little bit about data fabrics. Data fabrics is something that is new.

It's a new trend because

we really want to get our data strategy in, in one compartment. And we talk about decentralizing our data and we want to go, we're on self-service at B I and we want governance because we have to do data privacy and things like that. So data management will really become a big part, a

critical part in the modern

data fabric. And then we talk about M multi cloud because we want um of course, it's about saving costs and we want to leverage our data and we want to pay for what we only are using. So really the maintenance on, on prem um is really not feasible as we're going to move

to a big data and more

modern data integration. And then of course, for me, what I feel passionate about is incorporating the right

skills and the capabilities within your data and analytics

organization. Uh That is something I feel very passionate about. OK, so very simple. Why would we use a data lake, not a data warehouse? So

we all, we all know traditionally etl we

extracted and we transport information. We built

a star schema, we build business views and then

we build dashboards for our clients. Um We also wanted them to drill down information and and we wanted them to, you know, sort of give themselves

those B I but now we're moving towards fourth

generation and we're talking about uh we no longer want to extract and load and then transform, we want to ex I mean extract load and then transform because we, we want our data to be available. So it's no longer, I mean you traditional systems, we had to wait 24 hours. If I captured something on my er P system, I have to wait for batch processes tonight and then tomorrow I will get my reports and we don't want to extract, transform and load, we want to extra load and then transform, we want our data to be

available and we need a data lake, especially for data scientists because data

scientists need to be able to find trends within your data. And the reality

is um

social media data is really what is sets companies apart. So um whether it's whatsapp, whether it's Facebook, whether it's um

Instagram, we're really moving towards more

a environment where we have unstructured data. And from a marketing perspective, we need to be able to ha have data

in a data lake versus a data warehouse.

So that it is available for data scientists that they can track and, and

do trend analysis, et cetera. And then also if we have data in a data

lake, it's really about faster time to delivery. So for those who don't know the difference between a data lake and a data warehouse. So I'm very old fashioned. I come from a a Ralph Kimball dimensional modeling methodology um where we actually have a data warehouse and you, you know, you process

your data, you build a business view. Um you,

it's for the business, they understand what they want and you model the data for them and um it's very costly to maintain a data warehouse. So every time a user wants a a change to a dashboard, it's a whole process. End to end,

there's a data lake is very

um it's always not unstructured. The purpose is not

to it's used for data scientists and is highly accessible. So the other point is dear democratization of data sites. So why would we want um why is the focus on data science exactly? Like I said, we're talking about internet of things. We want whatsapp, we want Facebook, we want social media information, we want Google, we want Google analytics. And really the pur the purpose of data science is to be able to integrate patterns in our data and then be able to then convert it into a, a structured format. And then I put it into a model so that we can actually do predictive analytics and do reporting on it. I mean, essentially, like I said, social media really has become our most valuable asset. OK? So why, why are we no longer focusing on big data but right data for business intelligence and data analytics, we really need the right data at this at at the right time. In order to make decisions, I think that is cool to the business. Um we need data to be accurate and we need them to be available. So we don't need big data dumps, we need data. We we understand that there are volumes of data but how we manage our data and how we integrate our data is always its core to our business. And for me, this is what I feel passionate about.

I always say um anybody can build a visualization but not everybody can understand your data and analyze your data. So a lot of the focus really is data analysis. A lot of focus is on analysis and design in my years of uh as being a software developer. And even now as a solutions delivery manager, analyzing and designing your data really is key to a successful implementation and and development. Um The next thing I wanna talk is about data analytics in place will dominate. I mean, Garner has predicted that data analytics will be a core function in all business processes. So I'm not sure here in South Africa, um developers get poached all the time because there's such a demand for our skills and it's very simple. Um for me, because data analytics really is about understanding your brain, your building solutions so that you can get national insights and you have to be able to make business decisions at the speed which you're getting data. And um it's all about real time data and you know, on time so that you can make actual insights. So um it's about trends, behavior prediction and CRE and increasing your business profitability. So I do understand in the whole software development space, there's a lot of different areas that one can um pursue. But I always feel that at this point in time, the data analytics is really, you know, sort of the cream of the crop.

It's a bit of a bias, her opinion of course. And then the next trend is is really about data fabrics as we move to large data and data integration, a lot of

focus has become on data

privacy and data management. So a data fabric is

really a strategic it enterprise.

Um trend. It's not really A B I or a data trend because essentially you want to be able to argument all your data within your integra in within your your company. And really data fabric has emerged as a

popular design choice to

simplify organization, data infrastructure and and and create a scalable architecture. So really, it's about having the security and governance around your whole

it infrastructure from your

services, your data management. And what I like about data management, data management speaks about your governance, about your security, about your policies and your data quality. And,

and so data fabric

really is about having your data in one place secured and governed. Uh at this point, of course, it's just an idea but I am

talking about friends. So

um I also find that in solutions delivery that a lot of focus is

going to be on process

and governance. And I think um this is exactly what we're alluding to in future with data analytics is that we have

to governance, regards our services, our ecosystems,

our data management, our storage management, um the connection and how we integrate um and argument solutions and the platforms that we integrate. And, and I think this is gonna be a huge drive um going forward and the whole concept is called a data fabric putting in in layman's terms. And then of

course, class in the last few years,

cloud technology has evolved and it's, it's only gonna grow and, and the purpose really of cloud technology is because traditional d data analytics platforms really couldn't handle the

complicity and the volumes and

costs of resources and maintenance of the environment. And so, so cloud and analytics really has taken off because there's new services, there's agility, um you allow, there's data modernization and there's new types. And of of

course, the total cost of ownership you only pay for what you use. So the drive for cloud technology

is a trend

that is here and it will continue because you can do deployments

within in hybrid or multi cloud or inter cloud. And really there's many components within the cloud

environment as well. Like Microsoft Azure, we use Microsoft. So you have um Microsoft sign ups, you have studio. So there's

a lot of security and quality and a lot of so a

lot of companies are going to migrate to the cloud for very many reasons. So um even from an

upskilling perspective, having a cloud part of your data strategy is not always a nice to have, it's gonna be a mu it is a must to have and then

something I feel passionate about um as a tech lead,

I I lead a team of software developers and I've been in the Business Intelligence

Space for the last 17

years is actually incorporating, incorporating the right skills and even has things as involved, incorporating the right skills and cap capabilities, your your data analytics organization is key because the roles have evolved. And um um bef when I started as a developer, you had, you had to develop into end solutions. You had to be able to transform your data, extract your data, transform your data, load your data, then build bottle your data and then you should be able to build a visualization but things have changed. So now sort of broken the skill set from B I developer, a visualization expert to a data engineer and a data science. And I think I say to my team, um the best position to be in today as a developer is to be able to obviously upskill yourself in all areas.

Um So it's just very

interesting because obviously it has the tools has evolved um the demand to not build that warehouse has sort of got to got sort of a bit of a sidetrack

where I I still

feel that the power of building A B I solution wise in your data integration in your data analysis and your data market. And so it's very interesting to see how um this is ha has evolved as well. So my second

key um key point that what I wanted to take out for my talk is really about

what skill set does a female tech leader need.

So I've been, I've led teams

of le led teams of developers in the last few years. And to me, the biggest skill set is grit I actually Googled what grit is. And like according to Wiki, to Wikipedia, grit means a non non conti noc trait based on an individual's perseverance

of effort combined with a passion for particular long term goal or an end

state.

Uh It is and powerful

motivation to achieve an objective. And I think for me, this is really what it takes to be a female tech leader is grid. Um And then, so that is, that is Wikipedia's um definition. So I decided to ask, I asked myself, what is grit and what does it look like in a software development space? I've been a software developer for 26 years and it talks about, for me, this is sorry, this is my, my view. It really

is about boundaries and and boundaries is really about,

this is my space. This is what I can do and what this is what I can do and I will protect my boundaries at all costs. Um Tenacity and perseverance go with grit, tenacity. There are days that you are

going to not like your job. There are

days you're gonna be tired, exhausted, miserable. Um I find that a

lot of software developers

are introverts. So um at the end of the day, you really don't want to talk to anybody. So it's really about ethnicity and perseverance is really one of the big things. One of the other things that I learned um in my journey as a software developer is authenticity and truth. So I say to my team um speak your truth. And I, and I feel very passionate about

speaking your truth and

authenticity. I um even with my kids, I've got a son and a daughter who are teenagers and I say to them, where have you? I have this exercise that I do mentally in my head. Um Where today or where this week have I said y yes when I wanted to say no. And then sometimes I have to go back and I have to ask myself, I have to, then obviously, it's difficult to rectify a situation where you said yes. And then afterwards you say no.

But I felt that if you say if you're authentic and you speak as there is so much

less stress,

you feel so much

free. So for me, that is actually number one. But um and this is what I'm learning as I'm going along and my, my, my team will

say when I I'm

doing performance reviews and they will say to you, yes, we told you to speak our truth because if they didn't deliver, they didn't meet a deadline, they didn't speak the truth and, and speak your truth goes with vulnerability. So this is something I feel

passionate about and then empathy,

I mean empathy. I have been a developer for so many years. If somebody in my team comes to me and says to me this, that and the other, I can put myself in their shoes and I can have the empathy to understand where they're coming from. I also have the ability to understand because I've done that being that and worn the T shirt and I find empathy is really a great leadership skill. Um Offense is something I learned now recently because I'm part of the leadership team and my company. So I, I've learned that offense is really a trap. People are gonna criticize you. People are going to not be happy with you. People are going to insult you at the end of the day, offense is a trap. You need to be able to take everything with a pinch yourself and move on. I think this is where a lot of women lose, sort of lose the battle because we, we, we, you know, we get branded as very emotional and when you take the emotions out of a job and I think offense really is a trap. You

know, I always

say to myself, turn the offense into a learning lesson. What can I learn out of that situation? Uh Another thing that I also

noticed in my years as a female um software developer is that

men above you and men are below, you treat you

differently. So the guys who report to me will treat me different to the men who report to me who I report to, for example, on the same level. And I think you just need to be mindful of that.

Um because there really is, you know, you just have to be cognizant of it. And I think

emotional intelligence really is important and that's where the, the offense comes

in and then the growth mindset.

I mean, it's a given if you're not, if you're in it, business intelligence, um data analytics, if you don't have a growth mindset, I wouldn't even suggest you go

into this industry because you will learn every single

day of your life. And that is what I love about my job. Every day. I learn something new. I might not have to go on a course, but I've talked to my team or talked to um someone and I, I absolutely

will learn something. And that is what I

love about my job. And then of course, the passion um

for me, passion is

not about every day I get up and I deliver

solution. I have days where I hate getting,

um dislike my job. I'm tired, exhausted, tired of

dealing with the stress. But the passion is, I see my job as a service and a and an opportunity to

serve someone else. And I think

that is um really it's about mindset.

Um My job

is not about delivering solutions to a client. I see it as a service and a privilege to help someone

do their job better. So that's,

I guess that I, that is the passion that I have for what I do um something of one of the other skills that I feel um from the book, um Deadly from Barren Brown is that daring leaders who live their own values are never silent about hard things. And this really speaks

about to the authenticity. I

mean, I say to my son, um would you say something to your friends that

you wouldn't say to the class?

And, and this is the thing, it's daring to lead or daring to speak the truth really is what is important. You should not

be able to be silent about the things, hard things. And I

think this is what I learned. Um Most of my career at this point in my

life, I if I don't speak by truth, something inside of me don't sit well. So you

have to be able to live your values and never be silent about the things that matter or that's important to you. And then of course, we have to have the courage to walk and tell our story and write our own ending because dictate how we're going to live our lives. And then, I mean, if you look at the stats, um, 8% of women are or percent, uh sometimes I just get angry because really it's about a choice. It's not about who suggested something to me or what was a privilege or given to me. 27 years

later, I don't have regrets on my,

I, I love my job. I don't have regrets. Uh My goals have been

changed

over years, but I don't regret the decision to go into this career. And lastly, this is something that I found most um encouraging and something I feel passionate about.

And if there was a key takeaway from my session, this is what I love

about being a leader in, in my home because I'm a single mom or a leader in my industry or, or my company is that it's about extreme ownership. Um There's a book called Extreme Ownership and this is one of Joko Wing's quotes uh about extreme ownership. And he says, take ownership, take extreme ownership. Don't make excuses. Don't blame any other person or any other thing. Get control of your ego, don't hide your delicate pride from the truth. I love that.

Take ownership of everything

in your world, the good and the bad. Take ownership of your mistakes, take ownership of your shortfalls, take shown

ownership of your problems

and then take ownership of your solutions that will get those problems solved. Take ownership of your mission, take ownership of your job of your team, your future, your ownership of your life and lead. I love it that this is something

I feel passionate about. And I always ask myself, how

do I do this as a single mom and as a tech lead, but it's about extreme ownership and speaking about those, those are the two things I feel passionate about and then I quit. This

is a very controversial statement. So two years

ago, I, I moved to Joburg, I relocated to Joburg and I quit my job as a solutions architect. And this is the last thing I want to leave women. Um in the tech industry is sometimes we have to make shifts and we have to make changes and we have

to evolve and we have to transform to be able to be successful in our lives.

And I two years ago, I quit the job.

It was my dream job but I quit it because I reached burnout.

And, and this slide speaks to that. Um I quit over functioning. And I said, h him Andres, I quit being afraid what others think and negotiate for what I wanted. And I speak my truth. I could fall to think thinking being a female developer is a progressive and competitive market. It's not easy, fake

it until you make it.

I quit blaming others

because it comforts us for a

while in the illusion that we are in control on our fault. We still have a choice. We do not need to be empowered as women. We have power, quit being perfect or trying to be perfect, quit lying, lying to yourself, lying and pretending to be so deep lying and pretending so deeply in integrated in us that we even notice it. If we say, OK, we are doing great. We say yes. When we want to say no, be authentic and true to yourself. People are attracted to authenticity. And the last thing that I've learned in my journey and probably the most valuable thing that I've learned from a book by Robin Sharma, a leader with no title every day. Leave people better than you find them and see what it does for your career. Thank you, everyone. It

was my pleasure. We'll chat again.

Thank you. Bye.