• Self-service Analytics for Democratized Data Access • Enable users to ask the GenBI tools, in plain language, to conduct advanced analytics and build reports without the need to learn special programming languages specific to a traditional data analytics tool. • Empower users at all levels within CalSTRS to access and interpret data, without the need to rely on technical developers to transform data and build charts from scratch. • Automation for Improved Efficiency • Automate repetitive tasks to reduce the need for manual data analysis and interpretation, allowing business stakeholders to focus on essential/ strategic work, instead of cleansing/transforming data. • Auto-generate insights and recommendations, revealing meaningful patterns or insights leading to faster decision-making. • Advanced Analytics for Predictive Capabilities • Leverage machine learning and artificial intelligence to generate predictive insights to anticipate future trends and opportunities. • Process larger volumes of complex data, enabling analysis of previously inaccessible insights. • Data Decoupling for Increased Data Security • Decouple data from public-facing AI solutions like ChatGPT to protect privacy and mitigate data security concerns with sharing sensitive/confidential data with a public Large Language Model (LLM). • Avoid challenges associated with uploading large amounts of organizational data to a public LLM.
