Intelligent Data Exploration

Virtualitics

Data exploration is the foundation of all your data-driven initiatives. And as those initiatives expand to include AI, data professionals need to get smarter about how they explore their data. If you care about making the most of your data, this podcast is for you.Sponsored and hosted by Virtualitics. read less
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Episodes

Why Self-Service Analytics is the IKEA of Data Exploration
Nov 1 2023
Why Self-Service Analytics is the IKEA of Data Exploration
Furnishing a home can be a daunting task, especially if you’re living in a place with a few funny angles and oddly shaped nooks. IKEA, the furniture retailer known for their DIY kits, can provide you with some great easy-to-assemble pieces to fill your space, but for unique layouts, prefab furniture isn’t always going to be a perfect fit. These are the times when bringing in a custom or niche-focused solution delivers the perfect fit. When you finally have all your furniture, the result will be a blend of unique and off-the-shelf pieces that all work beautifully together.Similarly, every organization functions better when they have the right mix of IKEA-like DIY data analytics tools, such as self-service BI software, and custom solutions like AI-guided analytics that are capable of exploring complex data and discovering insight hiding in unusual places.Data exploration requires more than one toolThe applications used every day to run businesses create and capture thousands of data points every second. As a result, there is a deep treasure trove of information buried in these systems…but not a lot of resources or skills to analyze it all.Fortunately, there has been a ton of innovation in the BI technology space, making it easier for data consumers to now create their own reports and dashboards. This means they can get answers to some of their recurring questions without waiting for an inundated data scientist or analyst to find space in their project queue. In other words, they’ve now got their very own IKEA of business analytics at their fingertips.What’s also great about self-serve analytics is that it allows consumers to create their own reports within the boundaries set by experts. When data analysts are freed from creating and maintaining BI dashboards and spreadsheets for data consumers, they’re able to use their time and skills towards putting the correct guardrails in the self-serve software. This will minimize problems that come from using the wrong data, but it does limit the scope of inquiry…and that means some insights go unseen.This leads us to the custom solution that complements self-serve data work: AI-guided analytics. Platforms like Virtualitics give analysts the ability to dive deeper into data and find insights that will set your business apart. Deep exploration of complex data does require advanced analytic skills, but by leveraging AI-powered Intelligent Exploration solutions, data analysts can become stronger strategic advisors.
CDAO Insights: Do Transformative Applications of Generative AI in Financial Services Exist?
Oct 18 2023
CDAO Insights: Do Transformative Applications of Generative AI in Financial Services Exist?
Early this month I moderated the panel “The Implications and Opportunities of Generative AI in FS'' at Corinium’s CDAO event in Boston with David Dietrich (VP, Advanced Analytics and Governance at Fidelity Investments) and Jake Katz (Head of RMBS Research and Data Science at the London Stock Exchange Group). This was a lively discussion with a really engaged audience and it really highlighted for me the squeeze that Data and Analytics leaders are facing right now between their business leaders demand to hop on the GenAI train and finding a practical application for it. Data science insiders have known about GenAI for a while but the launch of ChatGPT at the end of 2022 brought awareness of it into the public consciousness, including that of senior management. Where before AI seemed ephemeral and complicated, ChatGPT made it tangible and easy. It also made AI seem a little bit like magic. As David noted, this led leaders to demand this technology, dedicating significant resources to integrate it into a broad set of applications. But do leaders really understand how GenAI and large language models (LLMs) work and what they’re asking for?The consensus from the audience was a resounding ‘No’. It’s tempting to shrug at this situation–this is just the latest in a long line of new technologies that seem to get everyone excited and distracted. No doubt the hype will settle down, right? Indeed, CCS Insight predicts that this is exactly what will happen in 2024 as the cost to deploy GenAI and LLMs safely and responsibly overshadows the value of the realistic applications of the technology in many situations. Are there Generative AI Applications in Financial Services?Does this mean that GenAI has no potential use cases in FinServ? Not at all. It’s proving its mettle with use cases in customer support, content generation, and even coming up with potential business ideas. These are all areas that offer a lot of efficiency gains and are worth exploring. But that still leaves a lot of the business that’s not currently seeing gains. And this leads me to my next point. What’s happening to all the other data-based initiatives and AI use cases while resources are diverted to GenAI? They’re stalling; and they were struggling to begin with (a CIO.com report says that only 53% of projects were seeing results). I could see in the room the frustration with an audience pressured to take away their attention from problems that could be solved with applications of other, more practical forms of AI. Managing up is never easy, but I think senior leaders need to hear that GenAI, while exciting, is not the answer to every business challenge. But CDAOs have good ideas that could be valuable ideas, and it’s time to turn their attention back to solutions that make sense.Download the eBook Three steps to solving your biggest business challenges with data + AI to see where your data can take you.
Interview with Ana Garcia: Data Literacy and Change Management
Jun 6 2023
Interview with Ana Garcia: Data Literacy and Change Management
The latest episode of the Intelligent Exploration Podcast features Ana Garcia, Director of Data Science and Analytics at ZipRecruiter, as she reflects on the changing landscape of business decision-making as she sees teams shift from relying on presentation decks and bar graphs to developing interest in data-driven solutions, dashboards, and predictive models.Transcript:Caitlin Bigsby: Hi, and welcome to the Intelligent Exploration Podcast. I'm joined today by Anna Garcia. Can you tell us a little bit about yourself and your background and how you got to where you are today and working with analytics and AI?Ana Garcia: Sure. I'm originally from Brazil and I did most of my career in Latin America, in Brazil, and in Mexico. And I started working back then with Microsoft Access and traditional databases in a consortium firm. Eventually one thing led to another sooner was MBI and traditional analytics and all the way into machine learning model, causal inference. And basically, what I do today, I am a director of Data Science at ZipRecruiter. ZipRecruiter is a jobs marketplace, so we connect job seekers and employers. And what I do there is manage a series of teams that support our product teams by doing product analytics, calls of inference, experimentation, and design to help us build and improve these products. Before that I was also at Uber and Lyft who had fantastic data science benches and I learned a lot. So this is a little bit about.Caitlin Bigsby: Me that is great. Also, Zip Recruiter is also known for advertising on podcasts. That's where I first heard of them.Ana Garcia: We'll get an ad from them soon. Yeah.Caitlin Bigsby: So you and I met before and we had a little chat about areas of interest. And one of the things that came up was data literacy at organizations and how important increasing data literacy is for the creation of and the adoption of AI and analytics in general. What do we mean when we talk about data literacy? What does that mean to you and who do you think needs it most?Ana Garcia: Yeah, absolutely. So when I started working many years ago, the typical business general manager or person would be very excited about PowerPoint decks and presentations and bar graphs and things like that. But they would also typically ask a consulting firm or maybe a specific department to build them for them. And then there was a slow turnaround time, but eventually they would get those graphs and reports and they would read these reports and make calls, right? So that was the typical business flow. And I think nowadays you have these businesses talking about the importance of making fast decisions, of moving fast and using data. And now these business people, they are interested in data solutions, they are interested in dashboards, they are interested in models, they are interested in predictions. So when I started, it was not super common to have a business executive asking for a model to predict or to infer the best price or asking questions like, we did this change in the product, did it increase sales or not?Caitlin Bigsby: Right.Ana Garcia: Typically they would just look at a bar graph and make a decision. Nowadays you get very exciting data requests from your business partners. So I want to see the data, I want to deep dive in the data, I want the raw data. I want to do the SQL myself. I actually want a model for this. I want artificial intelligence applied for this. Can we build a machine learning model?Caitlin Bigsby: Right?Ana Garcia: So I think it is very exciting to see that change happen. But in order for that change to happen, you need to educate people on what are these tools, what is the data world, what are the challenges of working with data? And I think data gives us so much power, and with great powers come great responsibilities. And it's ex