Curiosity, communication, and a passion for problem-solving are all important skills to cultivate for any data professionals considering a career in consulting.
Data-driven decision making has become much more pervasive throughout all of consulting, increasing the need for every role to increase their data literacy.
Domain expertise is something that grows over time, but in consulting, you close that gap by learning through exposure to different industries and by working side-by-side with the clients who have the domain expertise needed to complete a project.
One thing I've found that has changed over the last several years in consulting is that we've become much more accustomed to working with data in everything we do and across every role. So it's not just the analytics practices or the AI practitioners, but it's the broader sort of consulting landscape. That’s because we’ve begun to think about where we are driving decisions from, which has led the industry toward data-driven decision-making to the point that it’s basically baked into almost all parts of consulting.
The time pressure in consulting is much different than in other organizations. There's always a, a timeline that one is working against, but working with data in a consulting firm is usually dependent on whether we actually have the data and how long it takes for us to get the data so we can begin working on an initial hypothesis, impacting the timeline significantly. start working on a, at least an initial hypothesis. A lot of time also gets spent on data cleaning and building sort of a single source of truth that the team can utilize to get the job done right.
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Make Your A/B Testing More Effective and Efficient
Anjali Mehra, Senior Director of Product Analytics at DocuSign, discusses the role of A/B testing in data experimentation and how it can impact an organization. They cover DocuSign's analytics goals, A/B testing mech