Second, given the rapid pace of development of the AI landscape, no single company is capable of creating a walled garden expressive enough to capture the state-of-the-art. “First, the number of data assets an enterprise has to govern increases exponentially because many data sources used in AI are machine-generated instead of human-generated. For AI-specific governance concerns like provenance and bias, these traditional data governance platforms fall short. Efficiency depends on workloads fitting into this “walled garden,” and the rise of machine learning and LLMs is making this approach insufficient, says Databricks. Databricks says data governance technologies have traditionally relied on enforcing control at a narrow layer, such as in SQL-based access control for cloud data warehouses. The current AI gold rush is creating governance challenges. It simplifies data visibility and transparency, helping organizations understand their data, which is essential in the age of LLMs and to address concerns about their biases,” the company wrote in a blog post. “ Okera solves data privacy and governance challenges across the spectrum of data and AI. Additionally, its investment arm, Databricks Ventures, announced it has invested in data security specialist Immuta. The company has entered into a definitive agreement to acquire the data governance firm Okera for an undisclosed amount. Databricks is bolstering the data governance capabilities of its lakehouse platform with a new acquisition and investment.
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