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Introduction to Big Data, Data Science and Predictive Analytics


Data science, big data and predictive analytics are often misunderstood. The goal of this talk is to provide an overview of a typical big data pipeline, and provide a gentle introduction to the discipline of data science and predictive analytics. We will discuss at high level how some of the common machine learning algorithms are used by major big data companies to gain actionable insights, improve customer experience and gain competitive advantage in their respective industries.


• Provide an end to end overview of a big data pipeline.
• Understand how queries, page views, clicks and other forms of user interaction are used in a big data pipeline to gather actionable insights.
• View some examples of how Amazon, Google, FB and other big data companies may be using data science
• Discuss some examples from online search, advertising, retail, insurance, social networks, entertainment, education, healthcare, telecommunication and law enforcement.
• Provide a high level overview of some of the common data mining tasks like regression, classification, clustering, association analysis and outlier detection. This will be a very high level overview of these techniques without getting into the technical details.
• Understand descriptive, predictive and prescriptive analytics methods and when, where and how they are useful
• Discuss the various challenges in big data related tasks

Who Should Attend:

Anybody with an interest in understanding the bigger picture of big data and data science.

About The Presentator:

Raja has worked in various research and development roles at Microsoft Online Services Division. During his tenure, he worked on various cutting edge techniques that deal with various problems in paid search marketplace, online advertising, relevance in online retrieval, data mining at large scale, predictive analytics and online experimentation.

At Microsoft, Raja has been a regular speaker at various tech-talks and tutorials. He delivered a lecture series titled ‘Introduction to Machine Learning’ that has been a recommended resource for new Microsoft OSD employees for many years. He has also given talks on predictive modeling, R programming, online experimentation and A/B testing, relevance in online systems and online advertising. Raja has published his work on object detection, DNA classification, face detection and texture classification in peer reviewed journals and conferences. He has also served as reviewer for various journals and conferences in machine learning, data mining, artificial intelligence and large scale online systems. In 2013, Raja quit Microsoft after catching the entrepreneurship bug. He is currently working on his startup.

Most recently, Raja has been working on creating a high quality predictive analytics training program that includes classroom training and a mentor guided participation in a Kaggle competition. Details of this workshop can be found here:

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  • Sean S.

    Very helpful stuff. I am most interested in discussion of how the market is addressing the dearth of data professionals in the marketplace. What pathways are employers most interested in for people in various stages of life: Students, professionals with some database experience, SQL gurus with little or no predictive analytic background, statisticians with little database background, etc. Either companies are willing to grow people or all but the already-christened need to find an accredited program.

    June 30, 2014

    • Raja I.

      We have been working on bridging the talent gap. Data science is a very hands-on skill and we think that online and most other courses cannot teach practicial data science. We just finished offering our workshop on 'Hands-on Predictive analytics Using R' and ready to offer the next one:­ . The idea is to get attendees to start with no background in R or predictive modeling and enable them to participate in a Kaggle competition at the end of the workshop. Here is some of the attendees from the past:­ . This is an intense two day training followed by three weeks of participation in a Kaggle competition supervised by some of the best data scientists in the industry:­

      July 1, 2014

    • Chris

      I am new in Seattle and applying for jobs as a data analyst. I have some (but not extensive) experience with stats, sql, R, python from years working in a scientific setting at a university. If anyone is interested in my resume please let me know. I am doing interviews now, so I would have to move somewhat quickly. Thanks again!

      July 7, 2014

  • Ed H.

    I see that the next "Hands on Predictive Analytics Using R" workshop is being offered on August 5 - 6. That doesn't fit my schedule. Is there one planned after that?

    1 · July 1, 2014

    • Raja I.

      At this point, nothing is planned for Bellevue after August. We have few coming in Silicon Valley in August and September. I am hoping we can offer something in Bellevue in late September or early October.

      July 1, 2014

  • Raja I.

    Thank you all who attended. I will share the slides with Tom for upload.

    June 28, 2014

  • Michele

    I really liked the exploration of what a 'data scientist' is (from the speaker's viewpoint), which includes expertise in the technology, analytics, and optimization. Thank you Tom and Raja!

    June 28, 2014

  • steve j

    Thanks for hosting Tom & Raja for presenting. Is there a way to get a copy of the foils?

    June 28, 2014

  • amit

    Thanks for great presentation, can we get the ppt slides?

    2 · June 27, 2014

  • Tim F.

    Great content, just went a little long for the time allotted..

    June 27, 2014

  • Hsuan-hua C.

    looking forward to meeting everyone!

    June 5, 2014

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