Viyaleta Apgar, Senior Manager of Analytics Solutions at Indeed.com, joins the hosts to discuss the importance of structured data analysis and understanding the dataset before analysis. They also touch on risk tolerance calibration, building data fluency, and the role of circumstances and luck in success. Last call recommendations include exploring the Zoom app marketplace and joining the Test and Learned Community.
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Quick takeaways
Understanding stakeholder needs and goals is crucial for effective data analysis.
Data fluency requires thorough exploration and familiarity with the dataset to identify biases and uncover insights.
Building empathy and strong relationships with stakeholders is essential for collaboration and impactful analyses.
Deep dives
The importance of understanding stakeholder needs
In this podcast episode, the importance of understanding stakeholder needs in data analysis is emphasized. The discussion highlights the significance of taking the time to really grasp what stakeholders are asking for and what their goals are. By diving deeper into their requirements and clarifying assumptions, analysts can provide better insights and recommendations, reducing the need for multiple iterations and improving overall accuracy. It is suggested that the role of the analyst goes beyond simply executing requests, but rather involves building a deeper partnership with stakeholders, ensuring effective communication and managing decision-making risks.
The value of data fluency
The conversation also touches on the value of data fluency and the need for analysts to have a comprehensive understanding of the data they are working with. By thoroughly exploring and familiarizing themselves with the dataset, analysts can make more informed decisions, identify potential biases, and uncover hidden patterns or insights. The ability to ask critical questions, challenge assumptions, and communicate effectively with stakeholders is crucial in ensuring data fluency and delivering meaningful analyses.
The role of empathy and emotional intelligence
The podcast underscores the importance of empathy and emotional intelligence in the analyst role. Building strong relationships with stakeholders and creating a sense of partnership requires not only technical skills, but also the ability to understand and empathize with their perspectives, needs, and limitations. By approaching interactions with curiosity, actively listening, and asking probing questions, analysts can foster collaboration and gain a deeper understanding of stakeholder requirements, leading to more impactful analyses and recommendations.
The power of reframing and change management
The discussion highlights the power of reframing the analyst-stakeholder relationship from stakeholders to business partners. This shift in mindset and language sets the stage for a more collaborative and mutually beneficial partnership, enabling analysts to have open conversations with stakeholders in order to uncover the true goals and objectives behind their requests. The process of change management is emphasized, as analysts navigate and guide stakeholders through the discovery process, challenge assumptions, and establish effective communication strategies to successfully implement analytical solutions.
The interplay between analysis, exploration, and decision-making
Lastly, the podcast delves into the dynamic interplay between analysis, exploration, and decision-making. It explains that analysis is not just about generating insights, but also about understanding the context and implications of those insights. The importance of considering data quality, assumptions, and the level of risk associated with decision-making is highlighted. By involving stakeholders in the analysis process, clarifying assumptions, and fostering a culture of shared responsibility, analysts can ensure that recommendations are grounded in accurate insights and promote informed decision-making.
Seemingly straightforward data sets are seldom as simple as they initially appear. And, many an analysis has been tripped up by erroneous assumptions about either the data itself or about the business context in which that data exists. On this episode, Michael, Val, and Tim sat down with Viyaleta Apgar, Senior Manager of Analytics Solutions at Indeed.com, to discuss some antidotes to this very problem! Her structured approach to data discovery asks the analyst to outline what they know and don’t know, as well as how any biases or assumptions might impact their results before they dive into Exploratory Data Analysis (EDA). To Viyaleta, this isn’t just theory! She also shared stories of how she’s put this into practice with her business partners (NOT her stakeholders!) at Indeed.com. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
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