Through this book, we are embarking on a huge task of implementing a technology masterpiece for your enterprise. In this journey, you will not only have to learn many new tools and technologies but also have to know a good amount of jargon and theoretical stuff. This will surely help you in your journey to reach the ultimate goal of creating the masterpiece, namely Data lake.

This part of the book aims at preparing you for a tough road ahead so that you are quite clear in the head as to what you want to achieve. The concept of a Data lake has evolved over time in enterprises, starting with concepts of data warehouse which contained data for long term retention and stored differently for reporting and historic needs. Then the concept of data mart came into existence which would expose small sets of data with enterprise relevant attributes. Data lake evolved with these concepts as a central data repository for an enterprise that could capture data as is, produce processed data, and serve the most relevant enterprise information.

The topic or technology of Data lake is not new, but very few enterprises have implemented a fully functional Data lake in their organization. Through this book, we want enterprises to start thinking seriously on investing in a Data lake. Also, with the help of you engineers, we want to give the top management in your organization a glimpse of what can be achieved by creating a Data lake which can then be used to implement a use case more relevant to your own enterprise.

So, fasten your seatbelt, hold on tight, and let's start the journey!

Rest assured that after completing this book, you will help your enterprise (small or big) to think and model their business in a data-centric approach, using Data lake as its technical nucleus.

The intent of this chapter is to give the reader insight into data, big data, and some of the important details in connection with data. The chapter gives some important textbook-based definitions, which need to be understood in depth so that the reader is convinced about how data is relevant to an enterprise. The reader would also have grasped the main crux of the difference between data and big data. The chapter soon delves into the types of data in depth and where we can find in an enterprise.

The latter part of the chapter tries to enlighten the user with the current state of enterprises with regard to data management and also tries to give a high-level glimpse on what enterprises are looking to transform themselves into, with data at the core. The whole book is based on a real-life example, and the last section is dedicated to explaining this example in more detail. The example is detailed in such a manner that the reader would get a good amount of concepts implemented in the form of this example.