Techniques_and_Concepts_of_Big_Data

در این آموزش تصویری با مفاهیم و تکنیک های Big Data آشنا می شوید.

این دوره آموزشی محصول موسسه Lynda است.

سرفصل های دوره:

  • کار با big data
  • چگونه از big data  استفاده می شود؟
  • آشنایی با big data برای مصرف کنندگان
  • آشنایی با big data برای کسب و کار
  • سه جنبه از علم داده
  • انواع مهارتها در علم داده
  • علم داده بدون big data
  • big data بدون علم داده
  • اصول اخلاقی در big data
  • منابع و ساختارهای big data
  • کار با داده های ساخت یافته
  • کار با داده های بدون ساختار
  • ذخیره سازی big data
  • کار با محاسبات ابری: IaaS، PaaS، SaaS به، و DaaS
  • کار با Hadoop
  • آماده سازی داده ها برای تجزیه و تحلیل
  • تجزیه و تحلیل big data
  • نقش Excel در big data
  • و…

عنوان دوره: Techniques and Concepts of Big Data
سطح: مقدماتی
مدت زمان: 2 ساعت و 12 دقیقه
نویسنده: Barton Poulson

توضیحات:

Big data is big news. But what is big data, and how do we use it? Simply put, big data is data that, by virtue of its velocity, volume, or variety (the three Vs), cannot be easily stored or analyzed with traditional methods. Spreadsheets and relational databases just don't cut it with big data. In this course, Barton Poulson tells you the methods that do work, introducing all the techniques and concepts involved in capturing, storing, manipulating, and analyzing big data, including data mining and predictive analytics. He explains big data's relationship to data science, statistics, and programing; its uses in marketing, scientific research, and tools like Amazon's recommendation engine; and the ethical issues that lie behind its use.
Topics include:

    What makes big data "big"
    Understanding how big data impacts consumers, businesses, and research
    Exploring the intersection of data science and big data
    Facing big data's ethical challenges
    Understanding the sources and structures of big data
    Storing big data
    Prepping big data for analysis

    Welcome
        1m 17s 
What Is Big Data?
6m 47s
    The three Vs of big data
        58s 
    Volume
        1m 46s 
    Velocity
        2m 5s 
    Variety
        1m 17s 
   Does big data need all three?
        41s 
2. How Is Big Data used?
14m 35s
    Understanding big data for consumers
        4m 58s 
    Understanding big data for business
        6m 6s 
    Understanding big data for research
        3m 31s 
3. Big Data and Data Science
28m 11s
    Ten ways big data is different from small data
        5m 11s 
    The three facets of data science
        6m 45s 
    Types and skills in data science
        3m 38s 
    Data science without big data
        7m 52s 
    Big data without data science
        4m 45s 
4. Ethics in Big Data
10m 13s
    Challenges with anonymity
        5m 51s 
    Challenges with confidentiality
        4m 22s 
5. Sources and Structures of Big Data
19m 57s
    Human-generated data
        7m 0s 
    Machine-generated data
        4m 20s 
    Structured data
        2m 47s 
    Unstructured data
        5m 50s 
6. Storing Big Data
15m 42s
    Distributed storage and the cloud
        3m 55s 
    Cloud computing: IaaS, PaaS, SaaS, and DaaS
        4m 54s 
    A brief introduction to Hadoop
        6m 53s 
7. Preparing Data for Analysis
11m 45s
    Challenges with data quality
        3m 38s 
   ETL: Extract, transform, load
        3m 26s 
    Additional Vs of big data
        4m 41s 
8. Big Data Analysis
22m 27s
    Monitoring and anomaly detection
        5m 43s 
    Data mining and text analytics
        3m 52s 
    Predictive analytics
        5m 20s 
    Visualization
        4m 17s 
    The role of Excel in big data
        3m 15s 
Conclusion
1m 58s
    Next steps
        1m 58s

حجم فایل: 557MB