The rise of the modern data stack has revolutionized how businesses run around the world. Many companies now rely heavily on data analytics and machine learning to gain critical insights and to build better products. This has led to an explosion of tools and platforms that help these organizations gather, store, and process an increasing amount of data. However, as data teams grow larger and the data ecosystem becomes more complex, new challenges have emerged that prevent the successful adoption of analytics, data science, and machine learning. These challenges include issues related to discoverability, interpretability, observability, and governance.

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Pardhu Gunnam

Making world's data actionable!

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