Table of Contents

• Data Science and Big Data
  • SQL and Databases
  • NoSQL and NewSQL
  • Machine Learning solutions
  • Data Science Analytics Blogs
  • Data collection and processing is growing in sports
  • Google Analytics
  • Python analytics
    • Anaconda Analytics
    • Apache Zeppelin
  • Big Data
    • Awesome Lists
    • Big Data Blogs
    • Big Bang Data
    • Internet of things
    • Data Visualization
      • Tableau
    • Apache Spark
    • Apache Hadoop
      • Cloudera Docker image
    • Apache Storm and Kite SDK Morphlines
    • Pentaho Data Integration and Business Analytics Platforms

Big Data Landscape 2016 (version 3.0)

The future of #BigData is open source https://t.co/mxYQGTfLyP via @DataconomyMedia pic.twitter.com/epJeSG1iHk

— Paul Denham (@PaulTDenham) 26 de junio de 2016

https://t.co/L3fUiplTHq

— RedHatSpain (@RedHatSpain) 28 de junio de 2016

Data Science and Big Data¶

• Data is beautiful 'subreddit'
• datasciencecentral.com: 24 Data Science, R, Python, Excel, and Machine Learning Cheat Sheets
• visualcapitalist.com: All of the World’s Money and Markets in One Visualization
• civisanalytics.com: Machine Learning. Workflows in Python: Getting data ready to build models
  • civisanalytics.com: Machine Learning. Workflows in Python: Curating Features and Thinking Scientifically about Algorithms
• redash.io Open Source Data Collaboration Platform Connect to any data source, visualize your data and share it with anyone!
• Beginner tips to becoming a data analyst
• ZDNet Top 2016 Data Trends: 5 data-to-decisions trends to know for 2016. Apache Spark, real-time, cloud BI & analytics, IoT, and self-service were the trends to watch in 2015, and they'll continue to make waves in 2016.
• Top 20 Python Machine Learning Open Source Projects
• Top 10 Machine Learning Projects on Github
• Data scientists have the hottest job in America
• datasciencecentral.com: 20 short tutorials all data scientists should read (and practice)
• expansion.com: Qué debes estudiar para ser un experto en 'big data'
• The Best Business Intelligence Software According to G2 Crowd Winter 2016 Rankings 🌟🌟🌟

Top Machine Learning Twitter influencers one should follow https://t.co/BOWwefvwam

— Machine Learning (@ML_toparticles) 2 de marzo de 2016

Top 10 iPython Notebook Tutorials for Data Science and Machine Learning https://t.co/VhIIxpjWXw pic.twitter.com/iiDy5EBJW7

— Machine Learning (@ML_toparticles) 22 de abril de 2016

Moving Streaming Analytics Out of the Data Center https://t.co/cUM2LB7y6s

via #MVB @MarkLochbihler pic.twitter.com/gOwqMxcQxc

— DZone (@DZone) 12 de junio de 2016

New Machine Learning Cheat Sheet by Emily Barry https://t.co/gHrB4ZHVuD pic.twitter.com/d35YArL4Ah

— Machine Learning (@ML_toparticles) 20 de junio de 2016

https://t.co/JqRbbmNnxV

— RedHatSpain (@RedHatSpain) 28 de junio de 2016

10 Great Data Science, Machine / Deep Learning, IoT, AI, Stats, Python and R Resources https://t.co/yGqf4xPw83 pic.twitter.com/R5YVHOZ13m

— Machine Learning (@ML_toparticles) 30 de junio de 2016

How Olympic athletes use machine learning and data analysis to reach peak performance levels https://t.co/BXWxOVPTBM

— inafevDevOps (@inafevDevOps) 4 de agosto de 2016

SQL and Databases¶

• SQL and Databases

NoSQL and NewSQL¶

• NoSQL and NewSQL

Machine Learning solutions¶

• TensorFlow
• Microsoft opens up its deep-learning toolkit on GitHub

Data Science Analytics Blogs¶

• analyticsvidhya.com
• datasciencecentral.com
• pythonforsocialscientists.org
• leifengtechblog.wordpress.com

Data collection and processing is growing in sports¶

• reddit: Are there any good resources for Python and Proffesional sports data?
  • nba_py - stats.nba.com API for python
  • Pro Football Statistics
  • how data collection and processing is growing in sports. TED talk
• football-data.co.uk

I added a video to a @YouTube playlist https://t.co/znBOF9N3pq Moneyball Trailer 2011 HD

— Mr S Sinclair (@businessbgs01) 29 de febrero de 2016

Google Analytics¶

• Google Analytics para principiantes

Python analytics¶

• PyData, a community for developers and users of Python data tools
• Python for Data Science vs Python for Web Development
• Python for Social Scientists
• analyticsvidhya.com: Cheat Sheet: Data Visualisation in Python
• Distributed Computing on your Cluster with Anaconda (modern open source analytics platform powered by Python) - Webinar 2015
• reddit: 100 Data Science in Python Interview Questions and Answers

Anaconda Analytics¶

• Anaconda Analytics

Apache Zeppelin¶

• Apache Zeppelin. A web-based notebook that enables interactive data analytics. Very cool for data exploration and data science

Big Data¶

• gettopical.com: Bit Data latest news
• whatsthebigdata.com: History of Databases (Infographic)
• Big data is simply another name for complicated business intelligence: New visualization tools like Tableau, Clearstory, and Domo aims to unlock enterprise data for a broader audience than before
• thevarguy.com: Explaining the Big Data Productivity Gap The slow adoption and lack of productivity associated with Hadoop and other big data technologies likely stems from poor planning and lack of big data training and expertise, among other factors.
• dzone.com The DZone Guide to Big Data, Business Intelligence and Analytics, 2015 Edition
• Don't use Hadoop - your data isn't that big
• OpenRefine, a power tool for working with messy data
• stratebi - Apache Storm: Introduccion
• stratebi - Instalación de Storm
• stratebi - youtube- Introducción al Big Data Open Source: Map reduce, Hive, Pentaho..
• HP Big Data Reference Architecture for Apache Spark based on RHEL
• datanami.com: Top 33 Big Data Predictions for 2016
• zdnet.com: Big Data Predictions for 2016
• dzone.com: Learning Big Data Tools in 2016
• dzone.com: Taming the Data Variety Beast
• javacodegeeks.com: Top 10 Big Data Trends in 2016 for Financial Services
• datanami.com: Is 2016 the Beginning of the End for Big Data?
• washingtonpost.com: FTC warns companies that ‘big data’ comes with the potential for big problems
• crn.com: Tech 10: Big Developments in Big Data from 2015
• devx.com: The Big Data Skills Employers Want Most in 2016
  • What Are the Most-Wanted Data Science Skills for 2016?
• talend.com: How To Turn Any Big Data Project Into a Success (And Key Pitfalls To Avoid)
• Forbes: Big Data Facts: How Many Companies Are Really Making Money From Their Data?
• centurylink.com: Data Lakes: Hadoop Vs. In-Memory Databases
• medium.com: Big Data is not the same as Lots of Data 🌟🌟

#Bigdata. El poder de convertir datos en decisiones https://t.co/T3yhz2MdMH #ebook

— A un clic de las TIC (@AunCLICdelasTIC) 19 de marzo de 2016

#BigData permitirá prever dónde y cuándo se producirán los atascos y hacer una gestión dinámica del tráfico https://t.co/mexCV6BQKp @Dgtes

— A un clic de las TIC (@AunCLICdelasTIC) 20 de marzo de 2016

Which Big Data technologies are the most in demand and promise the most growth potential? https://t.co/f33PTzBXNL pic.twitter.com/VFLcOFA66H

— Forbes Tech News (@ForbesTech) 20 de marzo de 2016

Awesome Lists¶

• Awesome big data

Big Data Blogs¶

• datanami.com
• What's The Big Data?
• DZone Big Data Zone
• Dataconomy.com 🌟
  • Best TED Talks On Why “Data Is Beautiful” 🌟
  • SQL vs. NoSQL- What You Need to Know 🌟
  • Top 10 Big Data Videos on Youtube 🌟🌟🌟
• Data Science Central - the online resource for big data practitioners
• BDAhttp://examples.javacodegeeks.com/enterprise-java/apache-hadoop/apache-hadoop-cluster-setup-example-virtual-machines/N: Big Data Analytics News
• topdata.news: Big Data News
• DataFloq
• KDnuggets: Data Mining, Analytics, Big Data, and Data Science
• smartdatacollective.com
• Becoming a Data Scientist 🌟

Big Bang Data¶

• Big Bang Data

Internet of things¶

• techrepublic.com: Survey: Harnessing the power of big data and IoT

Data Visualization¶

• Nice resource! 384 Data Visualization Tools & Books
• flowingdata.com
• visualinformation.info

Tableau¶

• tableau.com: How to Make Your Own Tableau Application
• Join Multiple Excel Workbooks through Custom SQL Query in Tableau
• dbi.io: Visualización de Datos con Tableau de los resultados de una encuesta (4Q)
• Sample Data Sets

Apache Spark¶

• Tools for Troubleshooting, Installation and Setup of Apache Spark Environments
• mapr.com: Getting Started with Apache Spark – free interactive Spark ebook
• Spark Streaming: What Is It and Who’s Using It?
• Getting Started with Spark (in Python)
• Apache Spark Interview Questions
• PyData Seattle 2015 - youtube: Holden Karau: A brief introduction to Distributed Computing with PySpark
• medium.com: How MapR improves our productivity and simplifies our design
• svds.com Spark 1.6.0: Pivoting Data with DataFrames in SparkSQL
• DZone: Setting Up a Sample Application in HBase, Spark, and HDFS
• Setting Up a Sample Application in HBase, Spark, and HDFS. Learn how to develop apps with the common Hadoop, HBase, Spark stack.
• Introducing Spark Datasets with Spark 1.6
• DZone: Get Started With Spark 1.6 Right Away Here's a short reference to show you where to go and what resources to use setting up the newly released Apache Spark 1.6
• DZone: SMACK Stack Guide (Spark++) [slides]
• Top 30 Spark Interview Questions Asked in Most Interviews 🌟

Apache Hadoop¶

• bigdataanalyticsnews.com: 6 Essential Steps to Successfully Implement Hadoop
• examples.javacodegeeks.com: Apache Hadoop Cluster Setup Example (with Virtual Machines)
• information-age.com: 5 ways to get more out of Hadoop
• datafloq.com: 10 Things to Consider Before Diving Into the Hadoop Data Lake
• 16 for '16: What you must know about Hadoop and Spark right now
• Hadoop Deployment Cheat Sheet 🌟🌟🌟
• DZone: Word Count Program With MapReduce and Java 🌟🌟🌟 An introduction to the basics of MapReduce, along with a tutorial to create a word count app using Hadoop and Java.
• SAP comprará Altiscale para fortalecer su estrategia de Big Data
• unixmen.com: Install Hadoop on multiple nodes using Ubuntu 15.10

Cloudera Docker image¶

• pythian.com: how to deploy a cluster
• Cloudera Docker Container

Apache Storm and Kite SDK Morphlines¶

• Apache Storm is a distributed streaming processing engine
• Kite SDK Morphlines is a configurable ETL engine
• javacodegeeks.com: Apache Storm and Kite SDK Morphlines. Building a configurable ETL distributed application

Pentaho Data Integration and Business Analytics Platforms¶

• Pentaho
• pentaho.com/marketplace