November 2022
Beginner to intermediate
44 pages
55m
English
Overview
Storing data and making it accessible for real-time analysis is a huge challenge for organizations today. In 2020 alone, 64.2 billion GB of data was created or replicated, and it continues to grow. With this report, data engineers, architects, and software engineers will learn how to do deep analysis and automate business decisions while keeping your analytical capabilities timely.
Author Christopher Gardner takes you through current practices for extracting data for analysis and uncovers the opportunities and benefits of making that data extraction and analysis continuous. By the end of this report, you’ll know how to use new and innovative tools against your data to make real-time decisions. And you’ll understand how to examine the impact of real-time analytics on your business.
- Learn the four requirements of real-time analytics: latency, freshness, throughput, and concurrency
- Determine where delays between data collection and actionable analytics occur
- Understand the reasons for real-time analytics and identify the tools you need to reach a faster, more dynamic level
- Examine changes in data storage and software while learning methodologies for overcoming delays in existing database architecture
- Explore case studies that show how companies use columnar data, sharding, and bitmap indexing to store and analyze data
Fast and fresh data can make the difference between a successful transaction and a missed opportunity. The report shows you how.
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