Book Image

Learn MongoDB 4.x

By : Doug Bierer
Book Image

Learn MongoDB 4.x

By: Doug Bierer

Overview of this book

When it comes to managing a high volume of unstructured and non-relational datasets, MongoDB is the defacto database management system (DBMS) for DBAs and data architects. This updated book includes the latest release and covers every feature in MongoDB 4.x, while helping you get hands-on with building a MongoDB database app. You’ll get to grips with MongoDB 4.x concepts such as indexes, database design, data modeling, authentication, and aggregation. As you progress, you’ll cover tasks such as performing routine operations when developing a dynamic database-driven website. Using examples, you’ll learn how to work with queries and regular database operations. The book will not only guide you through design and implementation, but also help you monitor operations to achieve optimal performance and secure your MongoDB database systems. You’ll also be introduced to advanced techniques such as aggregation, map-reduce, complex queries, and generating ad hoc financial reports on the fly. Later, the book shows you how to work with multiple collections as well as embedded arrays and documents, before finally exploring key topics such as replication, sharding, and security using practical examples. By the end of this book, you’ll be well-versed with MongoDB 4.x and be able to perform development and administrative tasks associated with this NoSQL database.
Table of Contents (22 chapters)
Section 1: Essentials
Section 2: Building a Database-Driven Web Application
Section 3: Digging Deeper
Section 4: Replication, Sharding, and Security in a Financial Environment
Working with Complex Documents Across Collections

Performing risk analysis through revenue trends

The last category we will cover here is that of revenue trends. These reports are used by management to make decisions on where to invest money in marketing, as well as where to cut funds from non-productive initiatives. Revenue trend reports can be based on actual historic data, projections of future data, or a combination of the two. When generating revenue trends for the future, it's a good idea to first plot a graph of the actual historic data. You can then apply the graph to predict the future revenue.

The further back you go in historic data, the more accurate your projection will be.

When analyzing historic data in order to predict future data, be careful to spot and avoid anomalies. These are factors that are one-time events that have a significant impact on a particular trend, but that cannot be counted on in the future. An example might be a worldwide pandemic. This would obviously cause a significant drop in bookings for...