Blogs / Tutorials
Introduction to Hadoop
Hadoop is a complete ecosystem of open source projects that provides a framework for dealing with Big Data. Here is a simple explanation of Hadoop using interesting examples.
Introduction to MapReduce
After the introductory series, here is a simple explanation of MapReduce, a programming model used to process large data sets.
Hadoop beyond traditional MapReduce: simplified
After acquiring basic knowledge of Hadoop and MapReduce, it's time to move on to advanced concepts. This article covers topics like the hadoop extended system, apache pig, hive, impala, sqoop, flume, hive and other related concepts.
Trick your elephant into doing data manipulations (using MapReduce)
This article highlights MapReduce applications with HDFS using several useful tips and tricks to perform big data calculations faster..
Complete Beginner's Guide to MongoDB
Here's a complete beginner's guide to learning MongoDB. The main intention of this article is to explain the working process of MongoDB and its related components in the simplest way possible..
Get Mongo-ed in NoSQL manager, R & Python
Once you have read about the basics of MongoDB, this should be your immediate step to learn about using MongoDB in R, Python and NoSQL. Its ability to effortlessly integrate with third-party technologies makes MongoDB one of the best options in the Big Data industry..
Learn Cloud Computing in R
This article explains the concept of cloud computing in R Programming and R studio using a step-by-step methodology. What's more, you will also learn about the benefits of using R in the cloud compared to traditional desktop or client architecture / local server.
Impresionante Big Data – GitHub repository
Here is a github repository with all the necessary resources to master big data technologies. Appears to be a comprehensive resource guide for big data, but nevertheless, makes sure you don't get lost in this rich list of resources and that you stay focused on what you want to learn.
SparkR Learning Path
Here is a resource to start learning sparkR, an R library to take advantage of Apache Spark technology.
Comprehensive introduction to Apache Spark
Here's a comprehensive article covering everything from distributed computing basics to learning how to use Apache Spark technology for massive gains in terms of speed and scalability..
The best of YouTube videos
Learn Big Data Analytics using the best YouTube videos, TED Talks and other resources
Training and certifications:
- Big Data University: Big Data University is a cloud-based online education site that offers free and paid courses taught by a group of professionals and educators who have extensive experience with Hadoop., Big Data y DB2. Their goal is to make Big Data education freely available to all, so that it can lead to knowledge and discoveries in varied fields, like healthcare and the environment. Most courses include lab classes that you can take in the cloud, on VMWare images or locally installing required software. Completely free of charge, students obtain a certificate by passing the final exam.
- Cloudera: Cloudera provides a world-recognized certification for Big Data. Cloudera certifies true specialists who have demonstrated their skills to perform at the highest level in both traditional exams and practical challenges with live data sets..
- Coursera: Do you need to understand big data and how it will affect your business? This specialization is for you. Gain an understanding of the insights that big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. No previous programming experience required!! You will be guided through the basics of using Hadoop with MapReduce, Spark, Pig y Hive. By following the code provided, you will experience how predictive modeling can be done and take advantage of graph analysis to model problems. This specialization will prepare you to ask the right questions about the data, communicate effectively with data scientists and perform basic exploration of large and complex data sets.
