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Applying customization techniques like prompt engineering, retrieval augmented generation (RAG), and fine-tuning to LLMs involves massive data processing and engineering costs that can quickly spiral out of control depending on the level of specialization needed for a specific task. In fact, business spending on AI rose to $13.8
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Achieving this advantage is dependent on their ability to capture, connect, integrate, and convert data into insight for business decisions and processes. This is the goal of a “data-driven” organization. We call this the “ Bad Data Tax ”.
To overcome these issues, Orca decided to build a data lake. A data lake is a centralized data repository that enables organizations to store and manage large volumes of structured and unstructureddata, eliminating data silos and facilitating advanced analytics and ML on the entire data.
This capability has become increasingly more critical as organizations incorporate more unstructureddata into their data warehouses. This democratization is driving a seismic shift in data literacy throughout organizations, significantly changing how data is valued across every part of the enterprise.
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