The Data Standard

Every business aims to be data-driven, but not all of them succeed in that effort. In order to be able to truly derive insights from the data that an organization collects, there are certain foundational capabilities that they need to have the capacity for. In this episode, she shares her thoughts on the core elements that are necessary for every business to be data-driven, how she is helping companies incorporate those capabilities into their structure and the ongoing support that she is providing through a network of mastermind groups. This is a great conversation about the initial steps that every group should be thinking of as they start down the road to making data-informed decisions.Archana Ganapathihttps://www.linkedin.com/in/archanaganapathi/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/

You put in the time learning the skills, you took the right approach to your job applications, and now you’ve found yourself with a job in data science. That’s great! But now that you’ve got that job, how do you keep it and excel at it? How can you prove your value as a great data scientist?That’s a question that isn’t always as easy as it sounds. Having the skills is key, but a successful data scientist also needs to know how those skills can be applied to produce a meaningful business impact — one that justifies the high salaries data scientists command.Your analysis has to be good. But more importantly, it has to bolster your company’s bottom line.At larger companies, making this happen is often pretty straightforward. A big company is likely to have an established data science process and a team that you fit into, with clearly defined goals that management knows will generate a return on their data science investment.But at smaller companies, it can be considerably more difficult. You may be the company’s first data science hire, and there may not be a clear vision for how your role will help the company succeed. You might be tasked with “finding opportunities” and left to your own devices.This kind of freedom can be a blessing, but it can also be a curse if you’re not sure where you can make an impact. And it can be really difficult to handle when it’s combined with the impostor syndrome that often comes when stepping into a new role at a new company.Don’t despair, though — you can do this!Ragini Okhandiarhttps://www.linkedin.com/in/ragini-okhandiar/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/

The world has dramatically changed in just a few weeks. As companies around the world shift to remote work, how do we navigate this crisis? The Data Standard talks to Mark about how we communicate with our friends, family, and coworkers during a time when Zoom and Slack are our primary tools for understanding each other.Mark Connollyhttps://www.linkedin.com/in/mconnolly1993/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/

Discussing almost coining Machine Ethics, Big Data and social sciences not having the answer to AI ethics, prima facie duties, and robots, everything is going to have to have some ethics and AI as the continuation of humanity into space. This month we’re chatting with Robert Moss about responsible AI, defining AI ethic terms and collaboration, where does the interest in AI ethics comes from within organizations, how is it ethical for AI is related to good business outcomes, the connection of ethics and risk, and much more.Robert Mosshttps://www.linkedin.com/in/robertlmoss/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/

Catherine and Roberto discussed a range of topics including:The quantitative finance landscape.The challenges in identifying and using alternative data sources.Applications of machine learning in finance, including deep learning and reinforcement learning.New natural language models and their applications in finance.Model Explainability and Model Risk Management.Artificial General Intelligence.Roberto Strepparavahttps://www.linkedin.com/in/streppa/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/

The COVID-19 pandemic disrupted supply chains and brought economies around the world to a standstill. In turn, businesses need access to accurate, timely data more than ever before. As a result, the demand for data analytics is skyrocketing as businesses try to navigate an uncertain future. However, the sudden surge in demand comes with its own set of challenges.How the COVID-19 pandemic is affecting the data industry and how enterprises can prepare for the data challenges to come in 2021 and beyond.Andrew Custagehttps://www.linkedin.com/in/andrew-custage-8934381b/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/

What do data scientists do? Data science is about infrastructure, testing, using machine learning for decision making, and data products. Data science is being used in numerous fields, but it’s not all about deep learning or the search for artificial general intelligence. In fact, the skills needed include communication and storytelling. But data science is becoming more specialized, and with that the skills data scientists need are evolving. In addition, ethics is becoming a bigger and bigger challenge. Eric goes over his experience, sharing interview mistakes to avoid, tips on getting your foot in the door for jobs, and what it’s like to enter the data science industry full time. This is a great place to look if you’re about to graduate from your data science program.Eric Federhttps://www.linkedin.com/in/efederThe Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/

We are living now in a volatile, uncertain, complex, and ambiguous world. And, to sustain and succeed as a business in this environment, a winning data and analytics strategy is key. With the enterprises becoming data companies globally, there is a clear shift in the analytics paradigms today. We want to infuse AI across the value chain, but can we truly ignore the fundamentals of data management? Garbage in is garbage out after all. How can organizations create a data and analytics strategy to future-proof their data management landscape?Austin Kronzhttps://www.linkedin.com/in/austinkronz/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/

As the world reacts and evolves to our current market conditions—namely, massive disruption—organizations are forced to accelerate at an even greater pace. Implementing a winning data strategy has been realized as a business imperative to drive transformation through reduced costs, increased revenue, mitigated risk, and improved experience. Having a strong data strategy aligns to each of these core areas because ultimately, it’s an enabler of them.Dave Melillohttps://www.linkedin.com/in/davemelillojr/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/

Today, many of us spend our workdays online, in one-on-one and group meetings.  Here are some tips to help you make your presence known and have a positive impact, especially during large group meetings:Be visible.  Turn your camera on to simulate in-person attendance.Prepare.  Know the meeting’s purpose and agenda, complete assigned prework, review relevant notes from prior discussions, and write down ideas you’ll contribute and questions you’ll ask.Use active listening skills to test your understanding of new or complex ideas – you’ll help yourself and others.Using statements like, “Robin, what are your thoughts about this approach?” is a good way to invite others to contribute.Support ideas offered by colleagues, especially those who have a hard time being heard and valued over the voices of the favored.Summarize key discussion points and action items.  This is a helpful end-of-meeting strategy, and it can also be an effective way to refocus the discussion or transition to a new topic.David Coxhttps://www.linkedin.com/in/coxdavidj/The Data Standardhttps://datastandard.io/https://www.linkedin.com/company/the-data-standard/