September 17, 2020
A leading challenge facing music rights organizations is the proliferation of transactional streaming data. Due to the popularity of music streaming and the accompanying globalization of music, CMOs are facing the task of matching an unprecedented volume of data. Processing and matching this data places consistent pressures on internal teams, budgets and onsite servers and applications. With a predicted 1.15 billion paid streaming users globally by 2030, the volume of data will continue to increase in scale (Goldman Sachs, 2019).
The Matching Engine is built by design to address the transactional data challenges faced by CMOs. Modern cloud technologies ensure CMOs can cost effectively manage and process complex large volumes of streaming data.
In our upcoming webinar, we’ll cover how customers that are switching to modern cloud-based platforms are improving scalability, productivity and business outcomes by unlocking insights with Azure Databricks and Azure Machine Learning.
This Webinar will cover:
1. You will learn why Spark is the ideal analytics engine to build highly scalable and reliable pipelines for analytics.
2. A glance into the Apache Spark and Databricks
3. An overview of the key challenges enterprises face with big data and ML
4. How the Databricks Unified Data Analytics Platform solves these challenges to more easily tap into the power of machine learning to accelerate innovation.
5. A use case talk by Spanish Point and their implementation of Databricks
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