Big Data Reviews

  • Top Quants on Big Data and Disruption

    Sandy Rattray, chief investment officer of Man Group, and Heidi Ridley, chief executive officer of AXA Rosenberg Investment Managers, discuss how big data is disrupting investing with Bloomberg's Katia Porzecanski at the Bloomberg Invest Summit in New York.
  • Lecture: Mathematics of Big Data and Machine Learning

    MIT RES.LL-005 D4M: Signal Processing on Databases, Fall 2012
    View the complete course:
    Instructor: Jeremy Kepner

    Jeremy Kepner talked about his newly released book, "Mathematics of Big Data," which serves as the motivational material for the D4M course.

    License: Creative Commons BY-NC-SA
    More information at
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  • Big Data Success In Practice: The Biggest Mistakes To Avoid Across The Top 5 Use Cases

    Bernard Marr, internationally best-selling business author, keynote speaker and strategic advisor to companies and governments.

    Big Data comes with big promises to change our world and fuel an AI revolution and even a 4th industrial revolution. In order for these promises to be realised companies must to deliver successful big data projects. In his keynote address Bernard Marr will explore the top 5 big data use cases in organisations and identify some of the biggest mistakes data science teams must avoid as well as key criteria for success. Bernard will do this by looking at a series of real word examples in which he will also touch on key trends including data democratisation and self-service BI, data privacy and GDPR, edge and fog computing, digital twin technology as well as IoT and deep learning AI. Bernard Marr is a bestselling author, keynote speaker, strategic performance consultant, and analytics, KPI & Big Data guru. He has worked with and advised many of the world's best-known organisations. LinkedIn has recently ranked Bernard as one of the top 10 Business Influencers in the world (in fact, No 5 - just behind Bill Gates and Richard Branson). He writes on the topic of data and analytics for various publications including Forbes, HuffPost, and LinkedIn Pulse. His blogs and SlideShare presentation of the topic have millions of readers.
  • Big Data Analytics using Python and Apache Spark | Machine Learning Tutorial

    Apache Spark is the most active Apache project, and it is pushing back Map Reduce. It is fast, general purpose and supports multiple programming languages, data sources and management systems. More and more organizations are adapting Apache Spark to build big data solutions through batch, interactive and stream processing paradigms. The demand for trained professionals in Spark is going through the roof. Being a new technology, there aren't enough training sources to provide easy guidance on building end-to-end solutions.

    Section 1: Introduction
    Lecture 1
    About the course
    Lecture 2
    About V2 Maestros
    Lecture 3
    Resource Bundle
    Section 2: Overview
    Lecture 4
    Hadoop Overview
    Lecture 5
    HDFS Architecture
    Lecture 6
    Map Reduce - How it works
    Lecture 7
    Map Reduce - Example
    Lecture 8
    Hadoop Stack
    Lecture 9
    What is Spark?
    Lecture 10
    Spark Architecture - Part 1
    Lecture 11
    Spark Architecture - Part 2
    Lecture 12
    Installing Spark and Setting up for Python
    Quiz 1
    Hadoop and Spark Architecture
    5 questions
    Section 3: Programming with Spark
    Lecture 13
    Spark Transformations
    Lecture 14
    Spark Actions
    Lecture 15
    Advanced Spark Programming
    Lecture 16
    Python - Spark Programming examples 1
    Lecture 17
    Python - Spark Programming Examples 2
    Quiz 2
    Data Engineering with Spark
    5 questions
    Lecture 18
    PRACTICE Exercise : Spark Operations
    Section 4: Spark SQL
    Lecture 19
    Spark SQL Overview
    Lecture 20
    Python - Spark SQL Examples
    Quiz 3
    Spark SQL
    2 questions
    Lecture 21
    PRACTICE Exercise : Spark SQL
    Section 5: Spark Streaming
    Lecture 22
    Streaming with Apache Spark
    Lecture 23
    Python - Spark Streaming examples
    Quiz 4
    Spark Streaming
    3 questions
    Section 6: Real time Data Science
    Lecture 24
    Basic Elements of Data Science
    Lecture 25
    The Dataset
    Lecture 26
    Learning from relationships
    Lecture 27
    Modeling and Prediction
    Lecture 28
    Data Science Use Cases
    Lecture 29
    Types of Analytics
    Lecture 30
    Types of Learning
    Lecture 31
    Doing Data Science in real time with Spark
    Quiz 5
    Spark Data Science
    5 questions
    Section 7: Machine Learning with Spark
    Lecture 32
    Spark Machine Learning
    Lecture 33
    Analyzing Results and Errors
    Lecture 34
    Linear Regression
    Lecture 35
    Spark Use Case : Linear Regression
    Lecture 36
    Decision Trees
    Lecture 37
    Spark Use Case : Decision Trees Classification
    Lecture 38
    Principal Component Analysis
    Lecture 39
    Random Forests Classification
    Lecture 40
    Python Use Case : Random Forests & PCA
    Lecture 41
    Text Preprocessing with TF-IDF
    Lecture 42
    Naive Bayes Classification
    Lecture 43
    Spark Use Case : Naive Bayes & TF-IDF
    Lecture 44
    K-Means Clustering
    Lecture 45
    Spark Use Case : K-Means
    Lecture 46
    Recommendation Engines
    Lecture 47
    Spark Use Case : Collaborative Filtering
    Lecture 48
    Real Time Twitter Data Sentiment Analysis
    Quiz 6
    Spark Machine Learning Algorithms
    4 questions
    Lecture 49
    PRACTICE Exercise : Spark Clustering
    Lecture 50
    PRACTICE Exercise : Spark Classification
    Section 8: Conclusion
    Lecture 51
    Closing Remarks
    Lecture 52
    BONUS Lecture : Other courses you should check out
  • El Big Data en 3 minutos

    En este tutorial ilustrado te explicamos en tres minutos como funciona el Big Data.
  • Why Big Data Analytics is the Best Career Path? Become a big Data Engineer in 2018

    Check out my latest Video:
    Why Big Data Analytics is the Best Career Path? Become a big Data Engineer in 2018.

    Why Big Data Analytics is the Best Career Path?

    Hello guys my name is Daniel and you are watching beginner tuts and in this video, we are going to talk about why big data analytics is the best career path? If you’re looking for an amazing career option in information technology and don’t know anything about this industry, then this video can help you become a big data analytics engineer. The Average salary of a big data engineer is 100,000 annually… That’s right guys. 100 grand a year. Now you must be wondering, what the heck is big data??

    Big data is a term for data sets that are so large or complex that traditional data processing application software is too weak to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating and information privacy.

    The Great White is considered to be the King of the Ocean. This is because the great White is on top of its game. Imagine if you could be on top of the game in the ocean of Big Data!

    Big Data is everywhere and there is almost an urgent need to collect and preserve whatever data is being generated, for the fear of missing out on something important. There is a huge amount of data floating around. What we do with it is all that matters right now. This is why Big Data Analytics is in the frontiers of IT. Big Data Analytics has become crucial as it aids in improving business, decision makings and providing the biggest edge over the competitors. This applies for organizations as well as professionals in the Analytics domain. For professionals, who are skilled in Big Data Analytics, there is an ocean of opportunities out there.


    Why Big Data Analytics is the Best Career move?
    If you are still not convinced by the fact that Big Data Analytics is one of the hottest skills, here are 5 more reasons for you to see the big picture.

    1. Soaring Demand for Analytics Professionals:
    Jeanne Harris, senior executive at Accenture Institute for High Performance, has stressed the significance of analytics professionals by saying, “…data is useless without the skill to analyze it.” There are more job opportunities in Big Data management and Analytics than there were last year and many IT professionals are prepared to invest time and money for the training.

    The job trend graph for Big Data Analytics, from, proves that there is a growing trend for it and as a result there is a steady increase in the number of job opportunities.

    The current demand for qualified data professionals is just the beginning. Srikanth, the Bangalore-based cofounder and CEO of CA headquartered Fractal Analytics states: “In the next few years, the size of the analytics market will evolve to at least one-thirds of the global IT market from the current one-tenths”.

    Technology professionals who are experienced in Analytics are in high demand as organizations are looking for ways to exploit the power of Big Data. The number of job postings related to Analytics in Indeed and Dice has increased substantially over the last 12 months. Other job sites are showing similar patterns as well. This apparent surge is due to the increased number of organizations implementing Analytics and thereby looking for Analytics professionals.

    In a study by QuinStreet Inc., it was found that the trend of implementing Big Data Analytics is zooming and is considered to be a high priority among U.S. businesses. A majority of the organizations are in the process of implementing it or actively planning to add this feature within the next two years.

    2. Huge Job Opportunities & Meeting the Skill Gap:
    The demand for Analytics skill is going up steadily but there is a huge deficit on the supply side. This is happening globally and is not restricted to any part of geography. In spite of Big Data Analytics being a ‘Hot’ job, there is still a large number of unfilled jobs across the globe due to shortage of required skill. A McKinsey Global Institute study states that the US will face a shortage of about 190,000 data scientists and 1.5 million managers and analysts who can understand and make decisions using Big Data by 2018.

    According to Srikanth, co-founder and CEO of Fractal Analytics, there are two types of talent deficits: Data Scientists, who can perform analytics and Analytics Consultant, who can understand and use data. The talent supply for these job title, especially Data Scientists is extremely scarce and the demand is huge.

    3. Salary Aspects:
    Strong demand for Data Analytics skills is boosting the wages for qualified professionals and making Big Data pay big bucks for the right skill. This phenomenon is being seen globally where countries like Australia and the U.K are witnessing this ‘Moolah Marathon’.
  • #CHUMELxHBO | Big Data

    Disfruta del programa completo de Chumel con Chumel Torres en HBO GO

    No te pierdas el análisis más irreverente de los últimos acontecimientos de América Latina y el mundo, porque lo que tú piensas de las noticias, es lo que vas a escuchar aquí… ¡sin pelos en la lengua!

    Chumel con Chumel Torres llegará a las pantallas de la latinoamérica simultáneamente por HBO y HBO GO todos los viernes a las 23 hrs MX.

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  • What Is Big Data? & How Big Data Is Changing The World!

    In this video, we’ll be discussing big data – more specifically, what big data is, the exponential rate of growth of data, how we can utilize the vast quantities of data being generated as well as the
    implications of linked data on big data.

    - Starting off we'll look at, how data has been used as a tool from the origins of human evolution, starting at the hunter-gatherer age and leading up to the present information age. Afterwards, we'll look into many statistics demonstrating the exponential rate of growth and future growth of data.

    - Following that we'll discuss, what exactly big data is and delving deeper into the types of data, structured and unstructured and how they will be analyzed both by humans and machine learning (AI). We'll also discuss the next evolution of data,
    linked data, and how it will change the world and the web!

    - To conclude we'll briefly overview the role cloud computing will play with big data!

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  • The human insights missing from big data | Tricia Wang

    Why do so many companies make bad decisions, even with access to unprecedented amounts of data? With stories from Nokia to Netflix to the oracles of ancient Greece, Tricia Wang demystifies big data and identifies its pitfalls, suggesting that we focus instead on "thick data" -- precious, unquantifiable insights from actual people -- to make the right business decisions and thrive in the unknown.

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  • O que é Big Data - Conceitos básicos

    O que é Big Data

    Neste vídeo vamos apresentar o conceito de Big Data, explicando suas aplicações, características e importância tecnológica.

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