In this episode, Felipe sat down with Aruna Kolluru, Chief Technologist for AI at Dell Technologies ahead of our Advancing AI Melbourne event on 6-7 April. She shared how they work on providing solutions for their customers and use all available technologies - AI, IoT, data, etc, - to reach their desired outcomes. Aruna works with clients across a vast range of industries and this is a testament to the power data & AI hold to promote growth and generate business value, regardless of the area you work in. In her own words, data has become the core of innovation for every industry. With the key role data plays in today’s organisations, making it accessible for the analytics team to extract insights from it is of the utmost importance. That’s why data platforms have become essential for providing reliable, quality data that can be leveraged to achieve business goals. Tune in for the full conversation with Aruna on how to leverage data platforms. You can also join her in person when she presents with David Siroky, Asia Pacific Head of AI, Data Analytics & HPC, Director, Dell Technologies at Advancing AI Melbourne (6-7 April, 2022). Huge thanks to our Diamond Sponsors, Dell Technologies and Microsoft for supporting this event for the data community - to learn more from them register here: https://www.datafuturology.com/advancing-ai --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Organisations are in constant need of innovation to fulfill their end consumer’s needs. That’s why several companies have started innovation areas to help update and grow their main business. Today we are focusing on starting a Machine Learning and AI initiative within these innovation areas to grow the value they are providing, scale their results and positively impact the rest of the organisation. We are joined by Ram Radhakrishnan, General Manager for Customer Analytics, AI & Data Science at WooliesX, where he is building world-class capabilities thanks to 250+ data practitioners coming together. Ram is certain that AI and ML are future capabilities able to take organisations to new heights, whether it be solving business problems or providing a unique customer experience. The AI & ML space is quite big and diverse, but both Ram and Felipe share how they’ve seen a huge rise in the demand for machine learning engineers due to the growing need of scaling and operationalizing models. When it comes to hiring, the most important skill he looks for in candidates is the right attitude and the desire to always keep learning. WooliesX has a focus on teams and their members and works for them to dedicate nearly 20% of their time towards developing their own skills and knowledge. Tune in for the full conversation where Ram goes into detail about WooliesX agile practices, their scope of work, growing their teams and what he believes are the most important upcoming skills in the data space. Enjoy the show! Check out our upcoming live events at datafuturology.com/events Read the full episode summary here. --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

In part one of this special episode, Felipe reflects on the path his career has taken from his first start-up company to how he started Data Futurology and to his latest role in Healthcare.  In this open and honest conversation, he reveals the mistakes he made along the way and the lessons he learned from those failures. Successful people do have struggles, but you must be willing to ask for help. Passionate about his field, Felipe began the Data Futurology podcast in 2018 when he realised he needed a productive outlet for his obsession! Fast forward to today and he has interviewed over 200 guests from Australia and around the world from companies such as NASA, Formula 1, the AFL. And even a futurist! Listen in next week for part two as Felipe takes Q&A from the audience. Quotes:  There were so many things I did wrong during that time and so many things that I learned during that time, but it was the best training ground because the stakes were so high, and I felt like I had to be improving so quickly. It taught me a lot of lessons and a lot of what has helped to well in corporate is the lessons from my time as an entrepreneur. The first year was tough. There was a huge education piece. Nobody understood data science. Nobody really cared about data science. I would go and speak to business heads and executives let’s talk about what we can do for your area. But people did not take it very seriously. I’ve interviewed over 200 guests, including the CTO from Nasa, Martin Ford a futurist, that was super exciting. We have had people on the show from all different industries. It’s been awesome. Enjoy the show! Thanks to our sponsor: Talent Insights Group --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

We are joined by Aurelie Jacquet, Chair of Standards Australia, an independent not-for-profit organisation that specializes in the development and adoption of internationally-aligned standards in Australia. Aurelie is an expert in governance, data ethics, privacy and responsible use of technology. She starts by sharing with us how her journey in the data and ethics world started. She is a lawyer by trade, who started as a litigator and then moved on to work in finance for algorithmic trading. Her interest in AI and ethics peaked in 2016, she soon realized all law initiatives regarding AI were done overseas, so she decided to venture into the world of standards and push for Australia to participate in the international standards around AI. Quotes: "A use case I see that keeps coming back is 'how do you manage privacy, bias and accountability?" "The solution you use to address fairness and bias should strongly align with the legal principles of fairness and bias." "If you don't have the right control in place, or the right filters, then your output can be problematic." Thanks to our sponsor: Talent Insights Read the full episode summary here: Ep #138 Enjoy the show! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

In our last episode, we have Alan Ho, Head of Global Partner Marketing at Tibco Software. We look back on the challenges brought by this year and, as it comes to an end, we reflect on what we need to do differently moving forward and what areas offer hope to those who wish to participate more actively in the data economy. As a part of today’s discussion, we also had the pleasure of chatting with Sara Tiew, Public Sector Leader & Job Redesign Practice Leader at Mercer around the topic of the future of work. Sara acknowledges the fear people have of losing their jobs due to technology and automation, but she clarifies that technology will also create several million new jobs. Therefore, it’s extremely important to help workers employed in roles that are at risk and transit them into new job opportunities available. Quotes: "When I look at diversity I am not just looking at gender diversity, I’m looking at cultural diversity. I’m looking at orientation diversity." "I want to spend my time giving back to society and what can I do in my capacity to support those that require this help." "The Pandemic has brought forward digitization. It has impacted such a great deal in countries that are not ready will face a bigger challenge, especially from a skillset perspective." "If you look at banking and tech sectors, they are always at the forefront of adopting technology." Thanks to our sponsors: Shine Solutions Group Talent Insights SAS Women in Analytics (WIA) Network Growing Data Read the full episode summary here: #SheLeads Ep 12 Enjoy the last episode of our #SheLeads Series! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

We are joined by Disha Goenka Das, Director of Marketing at Twitter APAC to discuss the modern CMO's job. Disha has had a great career in marketing and has experience in several areas like sales, operations, product management and product marketing. She describes herself as endlessly curious and always wanting to explore the world. Creating marketing strategies and campaigns purely for customer delight is her happy place. She acknowledges technology is moving at a dramatic pace, and marketing is one of the most technology-dependent business functions, so she advises all marketing professionals to make a disciplined effort in staying up to date with the new technologies coming along. Quotes: "If I had to give advice to anyone who is in marketing I would say that marketing and technology are moving at a dramatic pace, it’s moving at a faster pace than any of us ever predicted. Keeping ourselves up to date requires structured learning and working. Whether you are a CMO today or you are a marketing manager you have to make sure that there is a disciplined effort in learning the new tech that is coming as we move along. That is one thing that will be critical for marketing professionals to succeed going forward." "The other advice I would give for any young marketing professionals starting out in marketing right now is, looking back from my experience, try to spend some time in sales to try to understand the end customer and figuring out what they really care about. Also, on the product side to understand, for example, how engineering makes product decisions. I truly believe it makes you a better marketer. Whether you can do that through rotation programs or spend a year or two in these roles, it is going to be super critical for understanding the business’ core." "I feel CMOs need to be both analytical and creative. Exceptionally successful CMOs who are at the leading edge of technology, deeply first understand the questions that they’re trying to answer, work with data to figure out how to answer it and most importantly, how do they use that information and data to bring it to life in a way that is truly beneficial. That balance is something important and I don’t see it going away despite how much AI and ML comes into the world." Thanks to our sponsors: Shine Solutions Group Talent Insights SAS Women in Analytics (WIA) Network Growing Data Read the full episode summary here: #SheLeads Ep 11 Enjoy the eleventh episode of our #SheLeads Series! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Kate Carruthers, Chief Data & Insights Officer at the University of New South Wales joins us for an episode that discusses the results of a survey shared by She Loves Data across their community regarding women's expectations about their careers, given the challenges of the past year. To start us off, Kate shares how her change-ready attitude has allowed her to seize new opportunities and learn new things. Though it might be intimidating, she encourages others to step up and say ‘yes’ to challenges. The pandemic of 2020 changed the nature of work forever, affecting millions of careers. Sadly, more women were hit harder. For this reason, She Loves Data reached out to their community and asked professional women about their worries, challenges and aspirations regarding work. Her advice for women listening is to find a community of people like them and groups that support them. Surrounding yourself with others may provide helpful and valuable perspectives that you might have not yet considered. Quotes: "I got my start in IT by being in the kitchen of the National Trust and making a comment about the network to the executive director and she said, you seem like you know what you’re doing, you should be in charge, and I said, sure." "I say yes a lot. When new opportunities come up I have a tendency to say yes because I’m very change-ready. I’m at the front-end of that change curve, I’m not one of the people at the back end of the change curve. I think that’s so important because it gives you the opportunity to try, and you might fail but you might not. I’ve succeeded more than I’ve failed, on average." "Getting everybody together because in the modern world it's much more complex and no one person has the solution to the problems. It needs to be a collaborative effort and if you don't bring people together you don’t get the best solutions. You don’t get that diversity of thinking from the different perspectives, and that brings better and richer solutions." "I was suddenly responsible for all computer systems in the organization and I had no idea of what I was doing, but I got up to speed and I really had an amazing opportunity and I took it." Thanks to our sponsors: Shine Solutions Group Talent Insights SAS Women in Analytics (WIA) Network Growing Data Read the full episode summary here: #SheLeads Ep 10 Enjoy the tenth episode of our #SheLeads Series! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

We are joined by Celine Le Cotonnec, Chief Data & Innovation Officer at Bank of Singapore and Shameek Kundu, Chief Data Officer at Standard Chartered Bank. They share with us their perspective on what the function and goal of the Chief Data Officer is. From Shameek’s experience, the function of the Chief Data Officer role varies by industry, maturity of the organization with respect to data and sometimes even by geographic location. Celine refers to a study that shows a successful data transformation is 20% about tech, 50% about the people’s mindset and 30% process reengineering wherever you are implementing some type of data product. For her, one key aspect of the CDO role is how you manage the people to achieve transformation within the organization. Quotes: "Many banks that have built some kind of credit model, even with traditional analytics, have seen their models crumble with Covid-19." "In any successful data transformation; 20% is about the tech, 50% is about people and their mindset and 30% is about process change." "If you want to detect financial crime, absolutely the holy grail of AI, in order to detect something like financial crime, at least in supervised learning, you need to know that a transaction was financial crime. But all we can do is detect potential financial crime, then we go and report it to a regulator and we never hear back." Thanks to our sponsors: Shine Solutions Group Talent Insights SAS Women in Analytics (WIA) Network Growing Data Read the full episode summary here: #SheLeads Ep 9 Enjoy the ninth episode of our #SheLeads Series! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

In this episode we have Figen Ulgen, Head of Data & Analytics at Woolworths NZ and Angela Kim, Head of Analytics & AI at Teachers Health joining us for a conversation around soft skills and their relevance in the world of data. Figen gives soft skills the same importance as technical skills, given that both of them are necessary for individuals to reach success. Soft skills may come naturally for some people, but even those who struggle can learn them. It may not come automatically, but it is definitely possible to improve. Angela encourages organizations to provide training for their teams in this area, to help them understand each other and their differences better, and also to learn from each other. Quotes: "If you don't have the communication skills or the ability to try and see things from their perspective, I think it is pretty difficult to get to the actual analytics part." "We need to be able to socially well coordinate relationships because it is adding another dimension to the workplace." Thanks to our sponsors: Shine Solutions Group Talent Insights SAS Women in Analytics (WIA) Network Growing Data Read the full episode summary here: #SheLeads Ep 8 Enjoy the eighth episode of our #SheLeads Series! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

On our 7th episode we are joined by two very talented women, Siew Choo Soh, Managing Director & Group Head of Consumer Banking and Big Data/AI Technology at DBS Bank and Terisa Roberts, Director and Global Lead: Risk Modelling and Decisioning at SAS. Siew Choo shares with us DBS’s mindset around innovation. For them, the use of technology does not equate to innovation. They don’t have a designated innovation department, just a small innovation team whose job is not to innovate, it’s rather helping other people across the bank to innovate. They provide resources to enable everyone to be able to innovate by empowering the individuals and teams to be curious. Terisa draws attention to a recent study by Deloitte, showing that firms who invest in diversity and innovation are 8 times more likely to achieve their business outcomes. She also mentions that in Risk Management, they monitor the algorithms they’re using in society and how these algorithms can discriminate against certain groups. Whenever they are faced with these challenges, a diverse team is in charge of identifying and remediating these biases. Quotes: "Their job is not to innovate, their job is to help other people across the bank to innovate." "You have to introduce bias to unbias your algorithm, because the algorithm has been trained by biased data." "Because of historical biases that were present in the training data that the algorithms learned from, that was perpetuated. A diverse team would have been able to stop that bias from becoming operational in the way decisions are made within that firm." "To make them understand each other from the different background they have, whether from cultural perspective or job experience perspective, can sometimes be quite a challenge, but I would say that once you manage to go through that initial phase you’ll see that it will help you get the best results, if you have a very diverse group of people." Thanks to our sponsors: Shine Solutions Group Talent Insights SAS Women in Analytics (WIA) Network Growing Data Read the full episode summary here: #SheLeads Ep 7 Enjoy the seventh episode of our #SheLeads Series! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

In this episode we have Vidyarth Eluppai Srivatsan, Director of Marketing Technology at The Coca-Cola Company and Pavel Bulowski, Chief Marketing Officer at Meiro and Co-Founder of She Loves Data. Vidyarth describes the Director of Marketing Technology position as a bridge between the roles of Chief Data Officer, Chief Marketing Officer and Chief Information Officer. It’s about going across the marketing, digital or technology to bridge the knowledge gaps and come up with both the strategy and execution. Data’s importance in marketing has soared. Currently, there are over 8000 AI and automation platforms available for marketers to take advantage of, so it can be tricky to know which ones are worth our attention and money. Pavel emphasizes the importance of thinking of them as strategic purchases and looking for the ones that offer capabilities that will help differentiate ourselves from the competition. Quotes: "Often when I work with people on my team who have that one very linear trajectory in their career, they are good at what they do but they don’t see a bigger picture. That’s what I can bring to the table, synthesize across the board a little bit more." "This role is a bridge between all those roles, CDO, CMO, CIO, that deal with marketing. There is a definite knowledge gap. We can’t expect all of these functions to know everything about how the fundamental layer that connects each of these buckets to really come through, and that to me is the central role of anyone who heads up the domain of marketing technology. So regardless of where this role sits, this particular person has to think about going across the marketing, digital or technology to bridge the gaps and really come up with both the strategy and the execution of the angles. That in essence is what the role entails, the definition of the structure will vary across companies but the purpose is to bridge the knowledge gap between these departments." "It’s a bit of a blindside because you can’t drive businesses by data, I think that’s a bit of a misconception. Business has to be driven by business, you need to have business objectives.In my mind it’s business driven and informed by data, but not data-driven on its own. When people put it out, a bit out of context and into the open it often feels like there are a bunch of data scientists who are able to find these whole new insights and directions for a company, and it is not necessarily so straight forward. Often, data analysts don’t have the business context. I think over the next couple of years it’s going to go back and we are going to hear more of business reasoning in marketing again, supported by data, of course." Thanks to our sponsors: Shine Solutions Group Talent Insights SAS Women in Analytics (WIA) Network Growing Data Read the full episode summary here: #SheLeads Ep 6 Enjoy the sixth episode of our #SheLeads Series! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

With AI determining many system-led decisions, from who gets a job, a loan or business opportunity, the need to ensure diversity and inclusivity in the creation of algorithmic rules becomes more important. In our fifth episode, we have Glenda Crisp, Chief Data Officer at National Australia Bank. She started her career in tech as a programmer in a bank in Canada and then went on to get an MBA. Before being recruited by NAB, she worked at TD Bank in Toronto. As the Chief Data Officer at National Australia Bank, both her business and technological side come together. Diversity is a key topic at NAB. They have 6 pillars of inclusion that they target, which are: Gender Balance, NABility and Neurodiversity, NAB Pride, Cultural Inclusion, African Inclusion and Indigenous. When it comes to bias you have to actively look for it and manage it, given that AI learns from data, historical data is a result of human decisions and humans are biased. NAB has an ethical framework for the use of data, machine learning and AI.  Quotes: "Nothing moves faster than technology [so] pay attention to the big themes that are going on across industries." "We can’t just ask AI to be more fair but we actually need to prescribe math that is fair." "The one thing I always say to young women when I get the chance is ‘please do not become complacent.’" Thanks to our sponsors: Shine Solutions Group Talent Insights SAS Women in Analytics (WIA) Network Growing Data Read the full episode summary here: #SheLeads Ep 5 Enjoy the fifth episode of our #SheLeads Series! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

In this episode, we have Virginia Wheway Vice President of Data & Analytics at Koala and Jan Sheppard, Chief Data Officer at the Tertiary Education Commission in New Zealand. Diversity is a broad area, and it includes gender, age, ethnicity, etc. Fostering diversity in an organization starts with the recruiting and hiring process.To make sure you hire the right people for the job you need to establish what you need or want for that role before you start recruiting, and then take out all your biases that might come into play. Diverse teams need leaders who are brave and ready to get outside their comfort zones, stay tuned to learn their tips on how to foster diversity in your team! Quotes: "In another company I was at before, the machine learning people have been repurposed to design dashboards." "The sorts of people I hire are not so rigid that they will only do one thing." "The real skills that are shining through and that people need are flexibility and adaptability because covid has made us in many ways. We need people who are adaptable and also understand the business." "Especially when appealing to women, it takes a different description. A lot of job descriptions across the board use male language, very direct and definite language. There are a lot of lessons to take out of this, but certainly how we advertise ourselves and how we build our relationships." Thanks to our sponsors: Shine Solutions Group Talent Insights SAS Women in Analytics (WIA) Network Growing Data Read the full episode summary here: #SheLeads Ep 4 Enjoy the fourth episode of our #SheLeads Series! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

When lockdowns started, people around the world, especially women, found themselves juggling with their personal and professional lives. In this episode we have Kathryn Gulifa, Chief Data & Analytics Officer at Worksafe Victoria, and Stuti Sharma, Director of Data Science at Visa who share with us the challenges they faced while trying to cope with the new normal. Stuart Garland, Director at Talent Insights Group gives us the recruiters’ perspective on the covid impact and tells us employees are not the only ones adapting to changes, employers are doing so as well. Some of them are beginning to realise remote work can be productive and perhaps there is an opportunity for some work from home to offer employees flexibility post covid-19. Quotes: "I was trying to balance full time work while caring for a 2 year old and a 6 month old. Which I found, honestly, really challenging and had many ups and downs from the mental health perspective, both trying to understand my place in the world having just returned from work and joining back into an organization that was facing a very different economic situation and different priorities than when I left." "I had my laptop setup on the dining table and it was always there, even over the weekends. I think it was mostly self-inflicted, I would find myself working late in the night and then I realized that it was not sustainable. This thing was not ending anytime soon, and I made a conscious effort to draw a line between my office hours and time with my family." "I have a team member that says it’s not working from home, it’s living at work." Thanks to our sponsors: Shine Solutions Group Talent Insights SAS Women in Analytics (WIA) Network Growing Data Read the full episode summary here: #SheLeads Ep 3 Enjoy the third episode of our #SheLeads Series! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Anu Madgavkar is a partner at McKinsey Global Institute and she’s done important research on Covid-19’s effect on gender inequality and the future of women at work. Anu talks about the diversity dividend and the compelling statistics supporting it. A study from +1000 companies around the world, found that organizations in the top quartile in terms of diversity in C-suite executives are 25% more likely to outperform in terms of profitability and long-term value creation. This holds true for gender and ethnic diversity. Also, companies in the bottom quartile are 29%  more likely to underperform, resulting in lower profitability or average value creation. Quotes: "I started focusing more on this notion that there’s a really leaky pipeline and a lot of women do dropout, and as you start thinking about that and navigating your own journey through that I think I got a lot more interested in why does this matter to the world at large, to economies and to women around the world." "Looking out 10 years I would say that the pace at which automation is changing the inherent work that we are all doing, that is going to accelerate and that is going to affect all people in the workforce." "Both automation as well as the trend towards more alternative work arrangements will both likely accelerate post-covid." "It’s a period of great innovation and experimentation and I think we really need to embrace this time to be more aggressive and experiment with more gender-friendly ways of support, both on the government policies side as well as the business side." Thanks to our sponsors: Shine Solutions Group Talent Insights SAS Women in Analytics (WIA) Network Growing Data Read the full episode summary here: #SheLeads Ep 2 Enjoy the second episode of our #SheLeads Series! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Data Futurology podcast host, Felipe Flores interviews She Loves Data co-founders Jana Marlé-Zizková and Pavel Bulowski, who share how they found a philanthropic niche in data literacy while pushing for more diverse and inclusive workforces. What started as a data workshop for a roomful of friends and friends of friends, has grown into a 21k+ community in 14 (and growing) city chapters around the world. Listen to inspiring stories from them and their members. Jana and Pavel both have abundant experience in the analytics field and also co-founded Meiro, a Customer Data Platform that allows organizations to harness user data. Jana was recently recognized as part of Singapore’s 100 Women in Tech. More than just a non-profit, She Loves Data is a community and a movement with the goal of encouraging women across Asia, ANZ, Africa, Europe and the USA to embrace tech and strengthen their data and digital literacy to future-proof their careers. Quotes: "There are only like 25% of women in this field. How about going out there and inspiring women to look at data as a possible future career." "You are changing people’s complete life trajectory by lowering the barriers to entry into something that they can find their passion and interest in." "It’s never late to change your career, it’s never late to learn about tech and data because it can help you for your future career, your jobs and maybe make your life more meaningful." Thanks to our sponsors: Shine Solutions Group Talent Insights SAS Women in Analytics (WIA) Network Growing Data Read the full episode summary here: https://www.sheleads-datafuturology.com/episodes/event-one-bkj8b Enjoy the first episode in our #SheLeads Series! --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

Felipe Flores es director de data science con casi 20 años de experiencia. Felipe ha trabajado en ingeniería de datos / almacenamiento, reportes, inteligencia empresarial, análisis, data science, machine learning e inteligencia artificial. Actualmente es el Director de Data Science en la empresa de Inteligencia Artificial, Honeysuckle Health. Mientras que Day es una experta en data science. Durante 15 años, ha colaborado con corporativos internacionales como Colgate, Gillette, P&G, Walmart y Epworth HealthCare para guiar su estrategia de inteligencia empresarial, de mercadotecnia y decisiones operativas mediante el uso de datos. Le apasiona todo lo que tenga que ver con datos e insights, es experta en técnicas cuantitativas, cualitativas y analíticas y ha trabajado con bases de datos, inteligencia de mercados, reportes de datos, ciencia de datos, pronóstico de ventas para innovaciones, machine learning e inteligencia artificial. En este episodio Felipe y Day nos dan una breve pero integral introducción a que es Data Science. Platican de cómo desarrollar las capacidades de data science en una empresa y la importancia de la cultura para implementar proyectos de datos exitosos. También nos dan tips de como empezar a desarrollar tu Carrera en Data Science entre otros temas fundamentales de Data Science. Temas: [03:20] ¿Qué es Data Futurology y ¿cuál es su objetivo? [07:30] Trayectoria de Felipe Flores [16:30] ¿Qué es Data Science/Ciencia de Datos? [19:45] Tips para desarrollar las capacidades de Data Science en una empresa [24:10] Sugerencias para alguien que empieza su carrera en data science [27:20] Como mantenerse al día en el mundo de data science dado el avance de la tecnología [32:30] Cómo especializarse en data science si mi carrera no está relacionada en data science [34:10] Entendiendo las diferencias de inteligencia artificial, machine learning, deep learning y data science [43:10] Cómo interactúa la Mercadotecnia con Data Science [44:35] El rol de la cultura en una organización para implementar data science [48:00] Tipos de algoritmos [53:50] ¿Qué es la minería de datos? [55:30] Libros recomendados para Data Science Frases: “La idea de un científico de datos es poder mejorar el desempeño de una empresa ocupando datos”. “Data science no es una caja de pandora sino hay una explicación detrás de cada algoritmo”. “El error más común es que la gente espera terminar el proyecto y decirle a un área que le va hacer el trabajo mucho mejor; la gente que tiene que generar el cambio deben colaborar con la gente de data science desde el principio de un proyecto”. “Nadie puede mantenerse al tanto de todo lo que está pasando en data science; es importante entender lo fundamentales de machine learning y estadística y con eso cualquier desarrollo que se de en cualquier área y así cuando necesitas aprende en cualquier área”. “En general el conocimiento depende de la persona cuando uno se quiere exigir y esforzarse; el conocimiento existe lo más importante es practicar poner los conocimientos en práctica”. “Uno puede tener los planes más espectaculares, pero si la cultura no existe nada va a funcionar; la cultura es el ingrediente más importante de data science”. Join Data Futurology on Telegram: https://t.me/datafuturology Únete a Data Futurology Español en Telegram: https://t.me/df_espanol YouTube: https://www.youtube.com/watch?v=WRop1cfFVo8&t=135s  --- Send in a voice message: https://podcasters.spotify.com/pod/show/datafuturology/message

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