High Level / Case Study
Friday, April 16, 2021
Digital transformation is being affected in nearly every industry but accomplishing true transformation requires not only technological advancement but reformation of culture and processes to embrace that transformation. At the core of digital transformation is a shift toward data-driven decisioning and action. The tools and capabilities that are produced by data scientists can be very powerful, but without the data translator, without someone to link projects to business initiatives and strategies, achieving enterprise transformation and AI adoption is impossible.
Constantly questioning whether the value of the work you do as a data professional really justifies the salary they're paying you? That concern is more than valid, but what if I told you that there is a proven process for making triple sure that your data projects result in business success for your company? In this brief session, you’ll learn how to build an analytics strategy framework from the ground up. If you’re in the conception/kick-off phase of a data project, and are wanting to develop an evergreen strategy for analytics, data management or even machine learning products, this session will show you how to get started doing that right away. This session is for data professionals who want a head-start on creating data strategies; whether that be an AI strategy or just a general data strategy - this session will help you craft a strategic framework so you can start taking measures to ensure that your data projects produce greater business ROI.
What you’ll get:
- A Clear Understanding Of The Value And Necessity For An Evergreen Analytics Strategy Framework: To create an evergreen analytics strategy framework, you first need to understand what it is and how it’s beneficial, so I’ll break that down for you.
- Steps That Go Into Creating Your Own Evergreen Analytics Strategy Framework: You’ll come away with all the steps and ingredients that go into creating an evergreen analytics strategy framework.
- A Proven Data Strategy Framework You Can Use Starting Today: Bypass all the hard work of developing your own framework, and just use mine. I’ll be providing that to you for free in this brief session.
You might have heard that there are only three things that matter - execution, execution, and execution. But how do you bridge the gap between strategy and execution?
We all make decisions. All the time. Especially leaders.
We all want those decisions to be “evidence-based” and are investing resources and efforts in building the data infrastructure, teams, and functionality of our organizations. But how can data and data scientists inform not only the company’s direction and strategy, but also support its execution?
In this talk, I will present two quick case studies that demonstrate how data can lead to successful execution. The first of which is a past case in which a reliable causal analysis was instrumental to setting the direction of a young mental health startup and securing a 45 million dollar investment in its Series C. The second is a present example of a social impact organization setting its course to reach diverse audiences supporting people who learn and think differently in all areas of life and shape the world for difference.
Every business is dependent on several processes to deliver value. In this presentation we will see how to use AI that can learn and trigger actions that will help organizations optimize their processes.
Why Can’t My Data Scientists and the Business Stakeholders Understand Each Other? Bridging the Gap Between the Business and Data ScienceJoin on Crowdcast
Businesses are hungry to transform into data driven organizations. However, despite hiring top data science talent, businesses often encounter challenges implementing data science solutions. This talk will give concrete advice about how executives can structure their organizations to reduce the frustration and failure that often comes with data science projects. Executives and managers will come away with concrete practices they can adopt to make their own data science projects succeed.
How Intuit, Jaguar Land Rover, Xandr and Unitedhealth Group Are Driving Business Outcomes With Graph Database & AIJoin on Crowdcast
The COVID-19 pandemic has accelerated the pace of digital transformation across all industries. Organizations are looking for ways to accelerate their analytics, AI and machine learning projects to increase revenue, manage risks and improve customer experience. Join us to learn about the three core capabilities necessary to drive the business outcomes:
- Connect internal and external datasets and pipelines with a distributed Graph Database - UnitedHealth Group is connecting 200+ sources to deliver a real-time customer 360 to improve quality of care for 50 million members; Xandr(part of AT&T) is connecting multiple data pipelines to build an identity graph for entity resolution to power the next-generation AdTech platform.
- Analyze connected data for never-before insights with Advanced Analytics - Jaguar Land Rover has accelerated supply chain planning from three weeks to 45 minutes, reduced supplier risk by 35% and is driving 3 times the business value from their data. NewDay, a leading specialist financial services provider and one of the largest issuers of credit cards in the UK uses advanced graph analytics to prevent and preempt financial fraud.
- Learn from the connected data with In-Database Machine Learning - Intuit has built an AI-based customer 360 with in-database machine learning for entity resolution, personalized recommendations and fraud detection. It is driving their transformation into an AI-driven expert platform. 7 out of the top 10 banks are driving real-time fraud detection and credit risk assessment with in-database machine learning.