Good morning. Can everybody hear me? Um My name is Val. I am presales manager for yoga. So, what I'd like to talk about today is um how with my career? And ba I has transformed. Um I started my career um as a mainframe programmer.Um I did not want to go into bi I wanted to be a, a um beauty therapist, but my dad felt that that was not um uh a good um a good career for a woman and he then persuaded me to do go into it. Sorry, my apologies. I just want to make sure my screen is everything is um showing proper, you know. OK. So, so, so the only change, the only, the only cause is change and that is truer now than ever because um technology is always evolving and I'd like to share how um with technology and how it evolved, how my career has evolved. So I started my career as a mainframe program. Um like I said, with the advice of my dad um um 16 and then 16 years later I made the jump into um B I and I do that. Sorry, my apologies. I just wanted to keep my um so I started my B A career um coding oracle pros and stored procedures and created star streamers for all up, all up condos cubes, right?

It was lots of fun and it laid the foundation for my career and we should never um we, we should never despise small beginnings because nothing is ever gained. You need to choose your career strategically and, and, and because it's a short term goal and, and, and the IP value, OK. And, and how today we refer to that as 3rd, 2nd generation I um the second generation education B I is about your decentralized distribution of your reports. Um Use dependency on your it team um and not a lot of self-service for your users. Um Sorry, gosh, sorry, my apologies. I realize I wasn't talking. OK. So let me just start that again. So, um when I started my career, um I started my career as a mainframe programmer. Uh Eventually, 16 years later, I do the shift to I um and I've not regretted the move um yet since, right? Um When I started um in MBI, I was coding oracle. So, procedures doing starches um for all our co ces, but a lot of focus on 2nd, 2nd generation B I is that it's so centralized and you have to wait. Um The turnaround is very slow and you have to wait for information.

Um But you never should, you should never despise your, your, your beginnings because it's about gaining experience and getting IP value and um and choosing your next job strategically. Um So second generation are behind, there's a lot of, a lot of room for self self service.

There's a lot of dependency they centralized and information is very slow. And, and that's when we, when we talk about, gosh, um when we refer to we come and we talk about um sorry, we talk about second, we talk about the the evolution of business intelligence. So as, as my career evolved, so did technology um I started as a developer and I ended up leading MBIT for a multinational um it company. Um but, but the rate of of information um delivery is very slow. So you, you actually need to, you need to produce information at the rate of of data, right? And our objective as a team was to translate into supply insights and rather than get actual information. And, and that's where I realize that B I is not delivering information at the speed of business. And, and I just like to clarify what I mean. My apologies are uh but screens are so mixed up here. OK? So I just like to clarify what I when I talk about. So we we we're talking, we're looking at explosion of data, the data is coming from everywhere and structures, massive increase of data demand for analytics data um data is is is here OK. So B I has broken dam walls and it's it's flooding every organization, right? It became clear the second generation B I with a bat approach with one day old data is not suffice, we need insights at the speed of business. OK?

So this this is what leads me, led me to the next evolution of my career. OK. That of technology and a third generation behind architect for Click. OK. So click is a leader with a vision of active intelligence and an end to end data pipeline. OK? They deliver real insight. You know what I want to talk about a passive B I, we want to talk about active intelligence. So, so, so what is the difference between passive and active? Um B I so passive B I is where there's a 24 hour cycle and to be I team will deliver a solution for you to produce reports for you. Whereas active intelligence brings data and motion data and rest and it allows you to generate insights real time. So and so so it's it's not a matter of transforming into third generation B I. OK. In other words, we must not change and metamorphic because what more to change more formally is good or bad. We should evolution. Neither do we in evolution like sorry, my apologies, we need to reform because reform talks about change for the good. If we look at the world, how the world is shifting. Um apologies. I'm not even sure how to make the screen here. So if you look at the world shift and the trends driving modernization. Um so, so why do we have to modernize our our data and analytics? Because there's different types of data, data, different types of data sources, structured and unstructured data sources.

And the shift has really forced business to look at a data management data strategy and not A B I strategy. OK. It's it's we need to deliver information at the speed of business and we need to look at data warehouse modernization. No longer can we develop? Ma there's still one version of the truth. So I in old school B so you were taught, you deliver um a data part that shares you the one version of the truth. But the reality is you can only share one store one version of the fact because the business is changing. So the truth changes all the time. So with the data, both methodology, you have the opportunity to store many versions of the facts and your data mark will then store the version of the truth. Um King Guiana who is the author of Snowflake says we need to be questioning an agile data we architecture because data and business needs your time um data and it needs to be able to scale. OK. So I'm very fortunate I work with you that our processing to it is enabled to create this connected data and analysis strategy that ultimately results in business outcomes and drives reformation and drives tangible value. OK.

So why do I say information because we need to improve for the better. It's not good enough to transform. And the companies that are going to reform are the companies that are gonna lead in the specific industries? So, so where do I see technology moving? Huh um The technology trends that are will drive the transformation is machine language artificial intelligence. These are the technologies that rule to propel your organization into a digital transformation. OK. It's about finding the patterns for data with A I and L in sense, we need the right people and we need the skills because technology makes it happen but people, technology makes it impossible but people make it happen. So in my opinion, data literacy is an essential skill for business used to become self sufficient and to get effective value and get value out of their data. So this leads to my second point fine the data necessary movement. Ultimately, the more things change, the more things stay the same. And how do we how do people see data? We say data is the foundation of our economy. Pardon me? You say data is the new world, right? So, so we need to become data liter, literate. Data literacy is defined as the ability or do you need to understand and argue with data?

Um It, it is the ability to understand your data sources your me your analytical methods plus your techniques and be able to to drop in some value outcome which essentially will improve decision and action. Um Moreover Ghana has predicted by 2023 data literacy will become an explicit necessity and drive off any business value. OK. By skiing, your your your your your your employees increasing the data literacy and you empowering them to better utilize the dentists data to really available them and give them the village to number one. Sorry, make better decisions, better decisions based on actual insight, medical risk and increased reward through act through data action, data driven actions and help an organization to be more productive and efficient hereby ultimately increasing profitability. So the way we see there's, there's three word to data literacy.

First, you want to establish a data literacy assessment within your organization and uh you, you want to get a report and a road map on where your po of excellency and the risk and then the media opportunity for improvement. If you want to have a training implementation program based on your assessment and you want you, you, you can have a class and read or ear and you, you want, you don't, not everybody needs to be a science, but everybody needs to understand and have a specific skill when if the job requires them to work with data.

And the third part is you need an adoption within, you need to create a culture of the literacy within your program in your, in your, in your company. OK. It's an, it's, it's an ongoing pro progress. It's about, it's about, it's about being making a, I mean, my apologies is our responsibility. It's to, to prove creoles of ladies in tech with the essential skill of data literacy. Um Data literacy is, is, is not about um being a data analyst or being a B I developer. It really is about understanding the trends in your data. How can you read data? What are the insights I found in my career that a lot of time spent um um B I teams or data teams analyzing data for business where if you empower your user with self-service B I or with data literacy that they can actually do the, do, do the analysis for themselves. I mean, I I led a team of P I developers and um the support task always outnumbered the project task. And then, and it's, it's a black state about bringing technology is what is the tool that makes it happen but what makes it possible? But it's the people that actually makes it, that makes it possible. Um I've got two kids and I always um I I, my, my mind is completely shifted when it comes to data.

Probably because I've been a lot in this industry if my son says to me, mom, um uh I failed the subject but I work these, these amount of hours and I'm like, what is, what is the data showing you the data is showing you that it's not good enough. So this this areas of improvement. So um we really need to change the way we think about, about data. And then my last point um apologies. I, so I've been in, in, in, I've been a software developer for 26 years and like I said, in the last 16 years, I did the shift to B I and um it's been the most rewarding career. I mean, I, it's so I have no regrets and I just wanted to share uh because I, I also, I mean, I like the idea of women taking and I, and I feel there's so big women have so much to offer. But I, and I, I always ask myself why are there so much for women um in, in tech? And my, my last point really speaks to the shift that can make you successful in, in tech jobs. And um I like to believe that I'm also involved as technology has evolved and um the last year, quit my job as a solutions architect. Um because at least some I believe sometimes you have to quit. OK?

And as we, we over function and we need to learn to over function and, and set healthy boundaries. Um we should be afraid of, of stop being afraid of what others think we should look at it for what we are. And speak the truth. Uh My, my favorite mentor is faith and you are on the same dimension and both demand to be filled. So quit thinking negatively, put your thoughts, thinking. I mean, being a female developer in a progressive competence is not easy. You need hair on your teeth. Perseverance is actually what is going to make you successful. And thank God for Google. You have to believe in yourself and you don't have to fake it until you make it. Um um And I also believe that a Christian that I can do all things to try to give me strength. We blaming um who's blaming, blaming only com comforts us for a short while and he gives us the illusion of that control. So for me personally, I get a bit offended, sorry when, when I hear things like men are doing this and men are leading and men are and, and, and, and women, we don't have to empower women. We are empowered. It's about um putting ourselves out there because we, we often want to be perfect. So my next point is quit being perfect. You can never be the perfect partner, mother, daughter, sister, you can never be, you cannot, you cannot have it all.

So you have to stop being hard on yourself and ask for help, make sure you have a good support structure and nothing is impossible. Ask and you will receive. Um And then my last point is good line, I think lying and pretending is so deeply ingrained in us. We notice it. We say we are ok. We do be great. We say yes, we want to scream no, we have to be authentic and true to ourselves. First, people are attracted to authenticity and you have to be vulnerable. I realize that when you are vulnerable, uh it actually makes your life so much simpler and easier because you will then be able to say, you know what I need help. And it's amazing people will help you. Um Few years ago, I was in a bit man. One of my also unhappy with my manager. Um this colleague of mine gave me this book and he said, read this book by Robin Sharma Leader with no title. And what really stood out for me in the end, the book was every day leave people better than you found them and see what that does for your career. And I found that that is, that is very true because essentially people are your business. Um What would I give my, what, what advice would I give myself? Um My apologies. The journey has been worthwhile being, data, being in data and analytics space has been a very rewarding career. I have no regrets.

I like I said to think I wanted to become a beauty. The I mean, I like my hair to be right, perfectionist. But thankfully I had a dad who was wise and had an insight and he pushed me into a career um that if every day you are prepared to learn and step out of your comfort zone, um you will never regret being in the best industry of this generation and generation to come. Um And then I, my last point, sorry is we are living in the best time to make the shift from second to third generation behind. If anything COVID has taught us is that we have to shift. Um Nothing stays the same. So I just like to share quickly um on, on, on uh my view on winning uh um how to bring it with, with, with analytics. But number one, you have to be, you have to start with the Yes, w in a plan, what are you trying to achieve? Who, who are you trying to do? And why does it matter? How do you measure success? My second point is you need business discovery spotlight data quality issues because you will never have perfect data. You'll wait forever if you're waiting for perfect data. So you need to be able to use your analytics tools, your current tools and, and and the analog, the anomalies from them, then engage with people and share your insights with them and together we can improve our data quality of the time.

My, my, my third point is team up with the design users like to, to see great visualization and it's important to get the right person on board. So because because you want that right aesthetic aesthetics, you want your, your, your your visualization to talk to your user because what is, what is that visualization? It is actually information of your data in a picture. And and so you should never neglect the best practices but to get a good design in your team, because everybody likes to teach pictures and then you want to learn to play and, and OK, that creates a perfect model for your, for your data on the first time, the first step. OK? Um You need to learn about your data and you want to give your users' power to connect to your data. And that's what third generation about data um data. Sorry. Third generation of B I talks about is the demo of data. It's about giving empowering your users to use your data. Um So that this is, that is self, very self sufficient and this is governed and it's secure in the third, you want to sell it. So how do you sell, sell your data analytics strategy to your business and you know it data analytics is different to your normal BR project. OK. So if you want to know, you have to act like a software vendor, you have to stop promoting it.

Um You need to list maybe the, the help of your marketing department. So in order to drive analytics through your organization, most important, you need to find a champion, someone who is influential or a team that is influential, that is that you can empower them. You need to turn believers to what's impossible and then they will have and this success will then drive the value through the use of your business. You want to do the number seven, you want to go with cross opportunity, OK? Because this repeat success and you want to repeat success and you want a boy for years, OK? You want to bring together a team that is in charge that decides the role of analytics, define the standards and rules and tools and then, and, and doing interation process over time. So, analytics as well, you, you're going to have KPIS in your company and you need to get it right. So you want to, you may not, you may develop an app that is temporary and you want to throw away. Um It's important to have a dual process because you want to keep your, your day to day in business as usual while you're doing your analytics strategy. And then now you want to put the ball away from reporting.

So both B A programs focused on pr reporting, it all looks the same. They providing information, then they tell you what, but you need to know why. So if you challenge your efforts and focus on taking the discovery and your exploration capabilities and lost, you want to turn your data into a profit center are you sitting in an information goal whose organizations pay good money to access your proprietary data or could you use it to add value for your customers?

Step back and think about the way you can monetize the data you already have. So for me, in conclusion, I have done this journey from mainframe programming to business intelligence and second generation. We are now in third generation B I and we want to develop solutions, end to end solutions. We do not want to spend, I was developing our etl we don't want to spend hours um building a data mart and data schemer and, and star schemers. So it is about um getting the right people on board. It's right about the right tools. Um And ultimately, it's about action, actionable insights and value to your business. And just the last one, companies that reform will the companies will be the companies that lead in the industries.

Thank you.