Title

AWS re:Invent 2023 - Data readiness for deriving business insight with analytics and AI/ML (SMB206)

Summary

• Subhash Venga, leader of the solutions architecture team for US Commercial, discusses building a data-driven strategy for analytics and business intelligence.
• Emphasizes the importance of data and the challenges organizations face in leveraging it for competitive advantage, citing a Gartner study that shows a majority of company data remains unused and organizations rank low on maturity scales for extracting insights.
• Stresses the need for a practical data strategy, especially with the advent of technologies like generative AI, and highlights common challenges such as data quality, siloed sources, and integration with application strategies.
• Advocates for starting with business outcomes when creating a data strategy, using visual mapping to prioritize data elements, and addressing data black holes by capturing data from all workflows and processes.
• Recommends proactive data reconciliation exercises, challenging the single source of truth, and integrating data and application teams.
• Suggests being open to different tools, ensuring APIs are used for data integration, and deprecating unused data and reports.
• Underlines the importance of a data-driven culture, with executive sponsorship, a single-threaded owner for data initiatives, IT accountability and inclusiveness, governance, and education to ensure decisions are made based on data.
• Offers AWS resources such as Gain Insights, Data-Driven Everything workshops, and the AWS for data portal to assist in creating data strategies.
• Provides the keyword "readiness" for the SMB mobile treasure hunt.

Insights

• The staggering amount of data produced today is not being effectively utilized by organizations, with 97% of data going untapped, indicating a significant opportunity for businesses to gain a competitive edge by improving their data strategies.
• The talk highlights a disconnect between data collection and the ability to extract actionable insights, suggesting that while companies are investing in data capture, they are not effectively translating this into business intelligence.
• The emphasis on starting with business outcomes rather than data sources when formulating a data strategy suggests a shift in approach from a technology-first to a business-first perspective.
• The concept of visual mapping to prioritize data elements based on business functions and questions indicates a practical, user-centric approach to data strategy that can help organizations focus on what truly matters for decision-making.
• The discussion on data black holes and the importance of capturing data from all workflows underscores the need for comprehensive data capture mechanisms to ensure no valuable insights are lost.
• The recommendation to challenge the single source of truth and to validate data sources periodically points to a dynamic approach to data management, where continuous verification and questioning are key to maintaining data integrity.
• The talk's focus on the cultural aspect of data readiness implies that technology and processes alone are insufficient for a successful data strategy; organizational mindset and behavior play a critical role.
• AWS's provision of free resources and workshops for data strategy development reflects the company's commitment to supporting businesses in their journey to become more data-driven and suggests that AWS is a valuable partner for organizations looking to leverage analytics and AI/ML.