All Things Data

It has become universal for any kind of business to explore software development solutions that are effortlessly efficient yet unique, and gets the job done. Today, companies after companies are discovering no-code development and are embracing no-code platforms as a shortcut and expediting the process of their app development with little to no coding at all. Let's find more about Low-Code and No-Code Development Environments.

Everyone has seen or heard of superintelligent AI, usually in the form of menacing robots. Luckily, those are mostly great fantasies by imaginative writers rather than a reflection of current reality. Today we venture into the things that AI can actually create. From the lowly meme to writing code and possibly creating other AI, let's find out how intelligent AI can actually (currently) be.

So much of law is opinion based that you may think that there is no way that AI could do an adequate job of automating some of the work. Fortunately, the legal and judiciary practices are very paper (document ) heavy, which lends itself superbly to NLP with AI. Today we'll explore exactly how the use of AI and NLP has changed the legal world and what may be to come.

Recently Data for Good and 1000ml decided to combine their expertise to respond to a sustainable housing challenge driven by the Canadian government. The innovative solution was put together with Data for Good volunteers with the help of AI experts at 1000ml and was delivered in 6 weeks.

Natural Language Processing with the help of Machine Learning is the current win-win combination used to detect fraud and misinterpreted information. One of the biggest challenges of the free and anonymous internet that we have constant access to and basically drives our life is “Fraud”.

How can you create efficient supply chain management? This is an open question for many suppliers, distributors, manufacturers, and retailers. Today, amid shifting supply chain market dynamics, changing ways of working, increasingly volatile demand, businesses are wondering how to make their supply chain less vulnerable to disruption. Machine learning holds the answer to many well-known as well as emerging supply chain challenges.

Contracting is a common activity, but it is one that few companies do efficiently or effectively. In fact, it has been estimated that inefficient contracting causes firms to lose between 5% to 40% of the value on a given deal. Recent technological developments like artificial intelligence (AI) are now helping companies overcome many of the challenges to contracting.

It seems as if the AI can be elusive when you don't have millions to spend on the type of talent that your small business would need to achieve big milestones. Fortunately, there are a myriad of ways in which your smaller organization can use AI; from customer service right through to sophisticated Document AI and Contract Management Systems, and much much more.

Organizations are constantly looking for an edge to win out against competition and the current state-of-the-art is to use AI. Becoming an AI organization is not for the faint of heart; let us guide you as to how you could quickly, safely and easily get your organization into the age of AI.

That's right, All Things Data is back! Of all the possible sources of business value that exist in your organization, the documents themselves tend to be the forgotten clue. With the amazing developments in machine learning, AI, and NLP, the time is now to gain a true understanding of your business through its documents, agreements, invoices, emails, intranets, etc... Really, any content whatsover.

How much does it cost your team in hours and dollars when one of your data jobs fails and you're running a report with inaccurate data? How do you REALLY know if all your daily data has been loaded properly? How long would it take to audit and fix? Simply put, what happens when your data breaks? This week on All Things Data we speak with Barr Moses the Founder and CEO of Monte Carlo. They've just closed a $16m round to solve data reliability through the concept of data down time. Barr walks us through her time at the Israel Defense Force and her journey to the Bay area through Standford, Bain,working her way up through Gainsight and starting a company. This week we'll cover: - What the inspiration was to start Monte Carlo - How the IDF help shaped her thinking - Why is data reliability important? - What is data downtime and why now? - Leveraging customer success as a super power - Hubspot's data jingle!

Clearbanc is making waves in the VC world with their novel funding model and use of machine learning. We thought it was interesting to speak to Susan Shu Chang to see how data science is applied in the startup funding world. We'll also be chatting about her journey from an Economics/Math major to RL (reinforcement learning) through her passion for gaming and how time management and prioritization has led her to get on the speaking circuit, writing a book, teaching, continue gaming and learning all while working full time!

If you're interested in how digitally native companies use marketing analytics at scale, this episode is for you. Peter Cheung, the Director of Performance Marketing and Analytics at Mejuri stops by this week to talk about how Mejuri's marketing team uses data to continually grow their community of fiercely loyal customers during COVID-19 and beyond. Peter gives us a peek under the hood on what he's looking for in a data marketer, why insourcing is right for them and how he thinks a data marketing team should be built.

Sr Data Scientist at Tucows, Kenny Kwan joins us this week to chat about why it's best to be a generalist when you're starting your data career. This week we'll cover why it's important to be able to get data yourself, what does it mean to have "communication skills" (hint, it involves cannolis ) and how to advocate for yourself and your projects. Kenny takes us through his story from leaving the Dominican Republic to pursue his PhD in the US and ending up as a data scientist in Toronto. Also, he's finally able become a Raptors fan this year because Kawhi isn't around.

Sr Data Scientist at Shopify, Fernando Nogueira joins us this week to chat about what it's like to work a large data driven organization and his path to getting there. We go through what it's like to be the first at Freshbooks in their growth stage, ChatKit as the first data resource on a 5 person team and then transitioning to large data science group. Fernando gives us a peek under the hood at how Shopify uses data and is built to last. We also cover marketing analytics, why it's important to work on your development skills and how he almost becoming quant twice!

As an All Things Data Special Episode we combined forces with Dave Mathias from the Data Able Podcast to chat about Data Education. We cover: - Where to start and where not to start your data journey - Where you should be focusing your learning - The spectrum of learning opportunities and how they fit into your data journey - How does your domain experience fit into the equation - Honing your craft with challenges like the 14 day Data Challenge from Tableau

Sr Machine Learning Engineering at Snap Travel, Joey Sham joins the All Things Data podcast to tell us what he's up to in his day to day as a machine learning engineer, how he made the transition from Physics to developer to data science, how Snap Travel uses NLP & BERT to help people find hotels and flights and how to hustle to get your first data science job.

Lead Data Scientist at Sunlife Financial, Jennifer Nguyen joins that all things data podcast to talk about how she uses data science in the insurance industry, how a web development project got her career started, what she's learning to become a better practitioner and advice for anyone looking to get in the field.

Apparently there are tens of thousands of Data/ML/AI jobs out there, but why isn't everyone you know getting hired and working in the field? This week Jansen and Victor discuss: - How technology markets evolve - New talent vs mature talent (and the talent rush) - How exits and large companies drive innovation and talent pathways - What a transition looks like from school to the work force now and in the future

What are the things you need to consider from a data perspective when you build a product? This week Victor and Jansen discuss some common pitfalls and risks they've seen over the years when building out products. They'll cover: - Data first thinking - Data as your product - Building MVP's - Codeless development - When to bring data people to the table

We've been keeping all your DM's from LinkedIn, email and our meetup slack and complied it into our AMA. This week we cover questions like: - What value does AI/ML bring to an organization? - I'm a CEO of a company, we need an AI strategy, our competitors are purporting to be AI driven. Where should I start? - What's the surrounding Hype of AI and what's the reality? - Why is there a race to AI now? Is it really something companies should be chasing - When do you think the data science hiring blitz will end? - I'm looking to break into the world of data science, should I be studying deep learning (sounds like a hot topic), or should I be studying the traditional ML techniques?

A data scientist is more than just scikit-learn and SQL. This episode Jansen and Victor discuss the knowledge and tools that a data scientist should posses to be the real deal. Why: - CI/CD - GIT - Containerization - Testing and more Are important tools and concepts to have in order to be a successful practitioner.

How do you transform an organization that isn't digitally native? This week Victor and Jansen discuss what it takes to enable legacy organizations to adopt AI. They'll be unpacking: - Boardroom discussions - Executive sponsorship - Team structures - Project ideation

With COVID-19 still growing globally, physical distancing and contact tracing is our best bet to reducing the spread until a vaccine or treatment is available. This week Victor and Jansen dive in to contact tracing tech, how it works and the adoption curve to make it impactful. We'll be covering: - The Apple / Google tech - Bluetooth and wifi options - Other methods that may or may not be socially acceptable - Thoughts on how to maximize adoption

What does it take to become a global AI Super Power? In this episode explore what countries are doing to win the AI race. Jansen and Victor unpack: Education Government policy How the private sector plays in the equation Which countries are investing and which aren't What skills are needed and who needs them

Co-Operative education aka Co-Op. What is it, why is it important and who are the players? After speaking with leaders in education, industry and government for the last 3 months we thought we would share our experiences with helping people find their first job. Our journey led us to really deep into co-operative education.

What if you got measured on all the good and bad things you did in your day to day life? How would we do it? Do we have the data? This week Victor and Jansen delve into creating a social credit system. We answer: - What data would we need? - Is it a violation of privacy? - Who owns the data and who gets access to it? - How is China currently doing it? We also reference The Information Trade: How Big Tech Conquers Countries, Challenges Our Rights, and Transforms Our World by Alexis Wichowski

Smart cities... What makes them smart? What's all the hype surrounding them? Why are governments pushing hard for these initiatives. This week Victor and Jansen unpack the city of the future. We'll cover: - Surveillance - Transportation - Smart Grids - Stories of smart city initiatives Bonus points if you know what episode art is!

We've been keeping all your DM's from LinkedIn, email and our meetup slack and complied it into our first ever AMA. This week we answers questions like: - What's next in technology? - How do you measure impact of a data science project? - What are our favourite thing about our jobs? - What should you do to make the next step in your career? - Our opinion AI making AI

Can data cure all? Probably not.... but it definitely can boost outcomes. From cancer detection, chronic illness management and patient experience, data is the key to unlocking breakthroughs and service improvements across the sector. This week Victor and Jansen discuss: - The social determinants of health - Wait times - Electronic health records - Connected hospitals - Drug discovery

Is retail as we know it dead? COVID-19, Data, AI and Technology is accelerating change in the retail experience. This week on the All Things Data Podcast Jansen and Victor discuss the future of retail: - Amazon Go - The rise of Phygital retail - Malls - Flu tracking? - New ways retailers are using your data for a better experience

When do I get my raise / promotion / secondment? Find out data is changing the way companies evaluate, compensate and measure their employees. (Hint: it's not the dreaded annual review) This week Jansen and Victor discuss the shift in the way HR operates, the death of the annual review and how we measure workplace productivity.

This week we look at how data has changed the world of sports. From team building, player evaluation and gaining that competitive edge, data is helping professional sports team look at the game differently. Victor and Jansen discuss the rise of the 3 pointer in the NBA, Moneyball in the MLB and F1 tuning to explore how a few numbers can change it all.

One of the big reason we're able to unlock AI is because of the amount of data we have in the world today. The Machine Learning models we build use this reference data to predict outcomes, this is why it's called training data. This week Victor and Jansen unpack: - How we use data to predict outcomes - Caveats and watch outs about the data we choose - The cost of training and resources - Transfer learning and how we can leverage pretrained models

Critics worry that AI will take jobs away, but like all technology, it's about how we implement it. Will it be a world where it's humans vs machines or will it be humans + machines? This week Victor and Jansen unpack the lanes, the tasks and uses cases humans and AI excel at. They'll also cover the implications on the job market and how AI will affect work as we know it (spoiler: we'll be OK).

As the saying goes, if it’s free, you are the product This week Victor and Jansen discuss how your personal data is being used in the wild. We'll be covering: - What data is being gathered - The tech behind data collection - What your data is being used for - Examples of the good, the bad and the downright scary uses of your personal data

The world is on lock down with the current COVID-19 crisis.... There is a lot of data floating around from different organization, governments and news which is hard to interpret, combine and answer questions. This is your chance to make a difference as a data practitioner! This week Victor and Jansen discuss: - The Data For Good not for profit organization - The inner workings of a data-thon and what you need to start your own - Types of data projects you could do to help your community We've got available data teams at 1000ML to help, reach out and let us know how to.

In this week's episode we tackle the subject of What is required to land your first Data job. Victor interviews Jansen on the intricacies of what it is like to start off in the world of data and try to get work in an environment that is radically changing as a result of remote work and now Covid-19 Part of our business is largely built on getting people employed in the world of Data. Most of our candidates we have come from a world of knowing how to study, take tests and write exams; in a very discrete fashion which does not lend itself well to the world of work. So we wanted to acknowledge and discuss what we are observing currently in the data hiring world and what employers like us are looking for in candidates.

Data Science is more than just Jupyter notebooks, it's: Machine Learning... It's the ML in 1000ML. Data Engeineering Model Tuning Infrastructure And a whole lot more This week Victor and Jansen discuss: - What is a model? - Data *'s aka Data People - Life beyond Notebooks - Data infrastructure - What it takes to productionize a model. - The business value of data science

This episode we'll be unpacking some the of the hype around AI. We'll be covering: - Terms (and the marketing take over) like machine learning, deep learning and artificial intelligence. - Do you need a PhD to work in the data field - Where do these projects start at a company - The glue people and the foundation of a data team - Data unicorns, should you do it?

Our inaugural episode of the All Things Data Podcast. Hiring and retaining top talent is hard! We'll be covering hiring and retaining data talent in a super competitive market and our experiences growing out some of the world's top data teams.