This Big Data Tutorial is an entry point to Big Data. In this tutorial, you will learn about the main challenges about Big Data. The following Table of Contents provides an overview.

1 Big Data Technologies: An overview of the technology stack within Big Data and its implications

2 Data Representation: The variety of data and how it is perceived

3 Data Modifications: Transformable and Filterable Data

4 Data Agility: The different needs for data agility with model agility, operational agility, and programming agility

5 Scalable Data: how to process data in an efficient way by scaling it out.

6 Partition Data: how to distribute data in the network

7 Storage performance: why it is so important to size systems right

8 Different storage systems: what are the challenges of storing data in different formats?

9 Data Concurrency: the challenges with parallel processing and consistency

10 Moving data for analysis: sometimes you have to move the data to do effective analysis of it

11 Data Quality: how to achieve data quality and what the data quality measures are all about

There are plenty of Tutorials available on this page in order to learn about Data Science and Data Engineering. If you want to dig much deeper into that, you can visit the project page for Apache Spark or Python.

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