I lived in books more than I lived anywhere else
Let’s see if we can use an analogy here. We all need a shiny new car. One that accelerates to 60mph in 6 seconds. Why not add IoT – automatic alerts while at it too. Voice assistant enabled chargers, anyone?……. No one – Do we have the requisite people, process, and tech for this car …
Winning with AI – it isn’t all about the technology Read More »
How Data-Driven Insights Guide SaaS Transformation and Customer Success At VMware, we uncover the power of data to drive customer success. By applying machine learning and predictive analytics across the customer journey, the VMware Data and Analytics team delivers continuous value with early warning systems, customer health scores, and data-driven insights across industries We use …
VMWorld 2021 – How Data-Driven Insights Guide SaaS Transformation and Customer Success Read More »
The job of a data scientist is to not just build models to predict which customers churn. Or dashboards to show KPIs around it. The job of a data engineering team is not just to enable data from multiple sources. Analytics and Engineering should actually help reduce churn. Completing a task isn’t success. Driving impact …
“Only 22% of companies using machine learning have successfully deployed a model”. says a Deeplearning(dot)ai report What makes it so hard? And what do we need to do to improve the situation? A thread – #1 ML is code using data. Not just code. #2 Output of the models are dependent on the data it …
“With great power there must also come great responsibility” Cheesy though it sounds, Peter Parker principle is on point when it comes to ethics of AI Increased adoption of AI brings with it an increasing responsibility to consider ethical concerns as a strategic priority. A PwC analysis proposes 9 ethical principles for organizations to track. As the …
What differentiates organizations that see value from AI from those who don’t? Is there a ‘playbook’ of core practices that ensure success? McKinsey & Company recently published a global survey on ‘The state of AI’. They mapped it down to 6 sets of practices that differentiates the high performing companies from the rest Strategy Talent …
5 Do’s and Don’ts for data scientists/analytics professionals looking for a new role If you do not know the hiring manager/person who can refer you – please don’t bombard people with ‘Hi’ messages on Linkedin. Do your homework upfront. Research about the company and roles they offer. Check out their careers page to identify open …
5 Do’s and Don’ts for analytics professionals looking for a new role Read More »
So what? I wish people who work with data ask that question more often. Many a time, data scientists focus on first order thinking i.e. we need to build A, B and C. What drives business value though is second order thinking – thinking through how that outcome will help drive tangible business value. #1 …
A few years ago a company launched an intelligent recommendation system for its customer service agents to suggest solutions to customer problems. The project was viewed as a high-profile cost-saver for the company. It took nine months to figure out that the agents weren’t using it,… And it took another six months to figure out …
What is an essential skill for every data scientist Read More »
Recent years progress in artificial intelligence has prompted renewed interest in a question posed by Russell and Norvig : What if we succeed? If and when AI researchers succeed at the goal of designing machines with cross-domain learning and decision-making capabilities that rival those of humans, the consequences for science, technology, and human life are …