The Data Standard

Everybody comes into Data Science from a different background. Some studied maths, some took stats classes, some came from finance, etc.Ruben's story is especially unique in that way – for many years he used to be a Chemical Engineer!What prompted him to make the transition? His MBA. Yes! Ruben found a way to structure his MBA in a way that leads him to an ultra-successful career in Data. And he hasn't looked back since.We talked about how his company has transformed throughout the pandemic, how to set up and promote self-serve analytics systems, how to keep your workflow under control, and the importance of mentors in Data Science.Ruben Kogelhttps://www.linkedin.com/in/rkogelThe Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/

Sometimes having a seat at the table in the workplace isn’t enough. Today’s guest reflects on her career trajectory and what’s helped her to find her voice, build confidence, and overcome nagging feelings of self-doubt, including great bosses, professional coaching, setting expectations, and running marathons.Ashley Odomhttps://www.linkedin.com/in/ashleymodom/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/

The past few months certainly haven’t been easy for small businesses. Many had to shut their doors due to the coronavirus pandemic. While some may never reopen, others are ramping up their business — and hoping they don’t have to shut down again. This podcast will focus on small businesses and what we can do during the corona virus crisis. It will focus on what to do if we can’t get aid right away, the mindset you should have as a small business towards marketing, management, sales, and more.Alka Guptahttps://www.linkedin.com/in/alkaakgupta/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/

Rapid technological advances in digitization and data and analytics have been reshaping the business landscape, supercharging performance, and enabling the emergence of new business innovations and new forms of competition. At the same time, the technology itself continues to evolve, bringing new waves of advances in robotics, analytics, and artificial intelligence (AI), and especially machine learning. Together they amount to a step change in technical capabilities that could have profound implications for business, for the economy, and more broadly, for society.Blake Treuhttps://www.linkedin.com/in/blake-treu/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/

Although the term “data scientist” has a nebulous definition at best, there are a few characteristics that seem to unite us: we are curious, we like finding nuggets of information buried within a mass of data, we like solving hard problems, we are technically inclined. There are tons of fantastic programs offering master’s degrees in data science and analytics, and these programs teach statistics, data mining, machine learning. But what if you need to build an actual product that is used by people? Does knowing the mathematics of back propagation help you?To our knowledge, most data scientists are not trained in product development. Yet, products that are underpinned by machine learning are becoming essential tools for many businesses, particularly in the retail and eCommerce space. Building data products requires data scientists, but as a whole, we are…not really great at building them. How can we contribute our talents to this process without derailing it and making our product development leadership roll their eyes and cringe?David Herberichhttps://www.linkedin.com/mwlite/in/david-herberich-62685618The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/

The COVID-19 pandemic has been raging for several months now and will likely continue for months to come. Amid this ongoing crisis, people need resources to stay as safe as they can for as long as they can. Data science and its related technologies are enabling such actions, playing an essential role in global safety.Times of hardship often serve as proving grounds for systems that people have boasted about in calmer days. The COVID-19 pandemic is no exception, and data science has more than proved its value. Data, and more importantly, the way people use it, is shaping and refining approaches to COVID-19 safety.Gavin Smarthttps://www.linkedin.com/in/gavin-smart-8687a485/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/

Everyone is suddenly a remote worker. In the wake of COVID-19, many employers are sending staff home as the coronavirus spreads around the globe, while others are forced to stay at home under quarantine.Are you prepared? How will you cope? You may even be secretly excited by the prospect. Either way, you need a plan.Kish Khemanihttps://www.linkedin.com/in/kishkhemani/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/

Coping with quarantine due to the coronavirus, the new-to humans virus that causes respiratory infection and can lead to serious or fatal health complications has been challenging for just about everyone. In the midst of a global pandemic, it’s hard to figure out ways to deal with the new lifestyle of sheltering in place or going out to do essential work. We cover everything about data and affordable housing to make you a smarter, more successful data-driven pro. Even if you’re new and data curious, you’re going to love it!Ty Tuckerhttps://www.linkedin.com/in/tyhtucker/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/

Out of the three billion pairs of DNA molecules that make up the human genome, only 0.1% are unique to each person. To find patterns useful to medical research in such a vast sea of data, researchers can benefit from tools that cut through the noise. Fortunately, these are the same problems that big data has been trying to solve for almost a decade. Biotechnology, broadly encompassing technological applications using biological systems, finds itself in similar conditions to those that allowed big data to emerge. As the volume and variety of medical data grow, it becomes more advantageous to refine it into information that can be used to make decisions.  Because of the vast quantity of patient data now readily available, ML has now become a valuable tool to model the behavior of drugs and find potential applications for existing and new molecules. Big data is not just in the future of the pharmaceutical industry, it is shaping its present.Data science and AI have a growing role in drug discovery and development. We speak with a leader in data science for health care, Neal Zundell, to learn more.Neal Zundellhttps://www.linkedin.com/in/nealzundellThe Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/

Artificial intelligence and machine learning (AI/ML) have spectacular potential to provide transformational insights. However, it’s often difficult to scale AI/ML models to the enterprise. In this episode, Nandan Thor, discusses the emerging discipline of AI modeling.Nandan Thorhttps://www.linkedin.com/in/nandan-thor-205374128/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/