Every person and every organization in the world manages data, whether they realize it or not. Data is used to describe the world around us and can be used for almost any purpose, from analyzing consumer habits in order to recommend the latest products and services to fighting disease, climate change, and serious organized crime. Ultimately, we manage data in order to derive value from it, whether personal or business value, and many organizations around the world have traditionally invested in tools and technologies to help them process their data faster and more efficiently in order to deliver actionable insights.
But we now live in a highly interconnected world driven by mass data creation and consumption, where data is no longer rows and columns restricted to a spreadsheet but an organic and evolving asset in its own right. With this realization comes major challenges for organizations as we enter the intelligence-driven fourth industrial revolution—how do we manage the sheer amount of data being created every second in all of its various formats (think not only spreadsheets and databases, but also social media posts, images, videos, music, online forums and articles, computer log files, and more)? And once we know how to manage all of this data, how do we know what questions to ask of it in order to derive real personal or business value?
The focus of this book is to help us answer those questions in a hands-on manner starting from first principles. We introduce the latest cutting-edge technologies (the big data ecosystem, including Apache Spark) that can be used to manage and process big data. We then explore advanced classes of algorithms (machine learning, deep learning, natural language processing, and cognitive computing) that can be applied to the big data ecosystem to help us uncover previously hidden relationships in order to understand what the data is telling us so that we may ultimately solve real-world challenges.
