Book Image

Solutions Architect’s Handbook - Second Edition

By : Saurabh Shrivastava, Neelanjali Srivastav
4 (2)
Book Image

Solutions Architect’s Handbook - Second Edition

4 (2)
By: Saurabh Shrivastava, Neelanjali Srivastav

Overview of this book

Becoming a solutions architect requires a hands-on approach, and this edition of the Solutions Architect's Handbook brings exactly that. This handbook will teach you how to create robust, scalable, and fault-tolerant solutions and next-generation architecture designs in a cloud environment. It will also help you build effective product strategies for your business and implement them from start to finish. This new edition features additional chapters on disruptive technologies, such as Internet of Things (IoT), quantum computing, data engineering, and machine learning. It also includes updated discussions on cloud-native architecture, blockchain data storage, and mainframe modernization with public cloud. The Solutions Architect's Handbook provides an understanding of solution architecture and how it fits into an agile enterprise environment. It will take you through the journey of solution architecture design by providing detailed knowledge of design pillars, advanced design patterns, anti-patterns, and the cloud-native aspects of modern software design. By the end of this handbook, you'll have learned the techniques needed to create efficient architecture designs that meet your business requirements.
Table of Contents (22 chapters)
20
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21
Index

Machine Learning Architecture

In the previous chapter, you learned about ingesting and processing big data and getting insights to understand your business. In the traditional way of running a business, the organization's decision-maker looks at past data and uses their experience to plot the future course of company direction. It's not just about setting up the business vision but also improving the end-user experience by predicting their needs and delighting them or automating day-to-day decision-making activities such as loan approval.

However, with the sheer amount of data availability, now, it's become difficult for the human brain to process all data and predict the future. That's where machine learning (ML) helps us predict future courses of action by looking at a large amount of historical data. Most enterprises are either investing in ML today or planning to do so. It is fast becoming the technology that helps companies differentiate themselves—...