Operationalizing your Analytics - Challenges and Best Practices

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Presented by

Sripathi Jagannathan, Head of Data Engineering; Edward Biton, Principal Architect; Alejandro Iparraguirre, Product Engineer

About this talk

Data-driven organizations, like yours, should harness the full potential of Modern Business Intelligence platforms to unearth previously inaccessible insights. Why is this important? Because this will allow you to capitalize on all your data assets, be it first generation on-premise data warehouses, to next-generation centralized data lakes on the cloud, to the latest decentralized analytics with Data Fabric and Data Meshes. But a note of caution. Your teams need to be forearmed to successfully tackle the complexity associated with the data engineering pipeline, especially at the scale of modern analytical workloads. The data practitioners at UST Global have worked with global customers to overcome this complexity and operationalize analytics at scale. This has helped us gain some unique insights. One of our findings has been that our NextGen OLAP for Big Data platform reduces the TCO of analytics by up to 50%! In this webinar, we will discuss: - Challenges we observe in operationalizing analytics at scale – Frictions in your ingestion to insights journey - Generating real-time insights from structured data streams - Amplifying productivity through OLAP for petabyte scale through visual data engineering - Transforming data proliferation challenges to opportunities Join us at this session, as we share more learnings from our engagements.

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