Need to collect any data Hamess the growing and changing nature of data
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The three V's
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New big data thinking: All data has value
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Two Approaches to getting value out of data: Top-Down + Bottoms-Up
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Data Warehousing Uses A Top-Down Approach
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The data lake' Uses A Bottoms-Up Approach
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Exactly what is a data lake?
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Traditional Approaches Current state of a data warehouse
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Data Analysis Paradigm Shift
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What is Hadoop?
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Hortonworks Data Platform (HDP) 3.0
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The real cost of Hadoop
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Modem Data Warehouse
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Data Lake with DW use cases Data Lake Staging & preparation
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HUB & SPOKE ARCHITECTURE FOR BI
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Federated Querying
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Benefits of the cloud
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Talking points when using the cloud for DW
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DW SCALABILITY SPIDER CHART
27
Summary
Description:
Explore the intricacies of big data architectures and data lakes in this comprehensive conference talk. Delve into four common patterns in big data production implementations, comparing top-down and bottom-up approaches to analytics. Learn how to effectively combine data lakes with traditional RDBMS data warehouses. Gain insights into the characteristics and benefits of data lakes, while understanding the importance of maintaining proper data governance. Discover strategies to prevent your data lake from becoming a data swamp, and explore topics such as enterprise data warehouse augmentation, data hub architectures, and the evolution of business analytics processes. Examine the concept of data value in the context of big data thinking, and understand the shift in data analysis paradigms. Investigate Hadoop and its applications, including the Hortonworks Data Platform. Compare traditional data warehousing approaches with modern data lake implementations, and explore use cases for integrating both systems. Learn about federated querying, cloud benefits for data warehousing, and scalability considerations in this informative presentation on cutting-edge big data solutions.
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