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A new community for data product leaders is being initiated, focusing on treating analytics and machine learning tools as evolving products designed for utility and usability before realizing business value. The community aims to accelerate learning by integrating the best of UX, human-centered design, and software product management into data product development, welcoming leaders from various disciplines to join and enhance collaboration.
A data strategy is defined as using data to drive business goals and achieve desired outcomes. It involves aligning data usage with business strategies to deliver results. Creating a data strategy is the responsibility of individuals in top management positions who understand the business objectives and can translate them into actionable data-driven strategies, ensuring alignment between data initiatives and business objectives for effective outcomes.
Implementing an effective data strategy is hindered by poor communication and misalignment between technical and business teams. Challenges include misinterpreting business goals, focusing on technology implementations but missing the strategic purpose, and insufficient collaboration between business teams and technical experts. Overcoming these challenges requires understanding business needs, facilitating clear communication, and aligning technical efforts with actual business objectives to achieve meaningful outcomes.
Effective data utilization involves translating technical capabilities into tangible business value. The focus should be on identifying business challenges, addressing them through data insights, and evaluating the impact on revenue, margins, or cost reduction. Aligning data initiatives with revenue targets, margin goals, or cost reduction strategies enables organizations to prioritize use cases that drive business growth and enhance decision-making, emphasizing practical results over technical complexities.
Today I’m chatting with Samir Sharma, CEO of datazuum. Samir is passionate about developing data strategies that drive business outcomes, and shares valuable insights into how problem framing and research can be done effectively from both the data and business side. Samir also provides his definition of a data strategy, and why it can be complicated to uncover whose job it is to create one. Throughout the conversation, Samir and I uncover the value of including different perspectives when implementing a data strategy and discuss solutions to various communication barriers. Of course, dashboards and data products also popped up in this episode as well!
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Listen to the best highlights from the podcasts you love and dive into the full episode