Big Data Lesson 6 – Big Data in Business

Big data for business

  • Predictive marketing

Big data is used to predict major life events like graduating or getting married, having a child, they do that by looking at the consumer behavior by monitoring the type of websites they visit. For a real-life example check this link ( how target found out the girl was pregnant)


  • Looking at consumer behavior.

By looking how often you log into their website, they can check what type of items you are looking.

Real life example:

I was looking to buy a mac book air on Amazon, then I changed my mind and I was watching youtube all the ads in the google ads were about mac laptops from Amazon

Another example: I wanted to buy some books about Data mining, but for some reason, I postponed buying it, next week I got an email from Amazon of all the highly rated Data mining books, I ended up buying 2, and they were really good.

  • Using Demographics

Demographics like age- marital status – home address- websites you visit

  • Predicting trends:

The edited retail company won an award for using big data in predicting fashion trends, so they can actually tell the retailers what most popular colors, styles, brands when they are going to be popular which will help them in pricing them


Introduction to Big Data Lesson 5

Lecture 5


  • What is Variety in Big data?
  • What is Structured data and Unstructured data and Multistructred data?



Variety point to the many sources and types of data both structured and unstructured.We used to store data from sources like spreadsheets and databases. Now data comes in the form of emails, photos, videos, monitoring devices, PDFs, audio, etc. This variety of unstructured data creates problems for storage, mining and analyzing.

Structured data: refers to a data which are contained in relational databases and spreadsheets.

Unstructured data: is all those data that can’t be so readily classified and fit into a neat box: photos and graphic images, videos, streaming instrument data, webpages, PDF files, PowerPoint presentations, emails, blog entries,tweets, wikis and word processing documents

Multi-structured data refers to a variety of data formats and types and can be derived from interactions between people and machines, such as web applications or social networks. A great example is web log data, which includes a combination of text and visual images along with structured data like form or transactional information







Introduction to Big Data Lesson 4

Velocity, in Big data means that data is being generated very fast, it also, refers to the speed of storing data and analyzing it, usually, the data used to get generated by people, but now we have social media, a security cameras at airports, sensors, smartphones, smart wearable devices like Apple watch and Samsung GEAR, The flow of data is huge and continuous.This real-time data can help researchers and businesses make valuable decisions that provide strategic competitive advantages and ROI (Return on investment).

You can see the speed of data being generated in real time by visiting the website:


Introduction to Big Data Lesson 3

Lecture 3


  • What is Volume in Big data?


  • Volume

Volume refers to a data that is too big to work on a regular computer, As we can see a huge growth in the data storage as the data is now more than text data (as it used to be on the World wide web aka web 1.0). We can find data in the format of videos, music and large images (which are taken from our smartphones and most of the new smartphones got high megapixel cameras) on our social media channels. It is very common to have Terabytes and Petabytes of the storage system for the tech companies (Google – Amazon – Microsoft). As the database grows the applications and architecture built to support the data needs to be reevaluated quite often. One the main reasons of a having a big volume are that the data are being generated not only by humans but also by machines too.The big volume indeed represents Big Data.






Introduction to Big Data Lesson 2


  • Application of Big Data for Consumers


  • Apple Siri and Google Now

When you ask Siri or Google Now for the nearest restaurant it uses your GPS location and process a massive amount of data (Big data) so it can give you an accurate recommendation


  • Spotify or Soundcloud

an on-demand music service, uses Hadoop big data analytics, to collect data from its millions of users worldwide and then uses the analyzed data to give informed music recommendations to individual users.

  • Amazon Recommendation

When you search for a book on amazon and then you scroll down, you will see some recommendation from amazon, suggesting you to buy the following book, it uses big data to show you similar books according to the book you are checking out.

  • Netflix

When you watch a specific type of movie of a TV show, from your watching list Netflix will recommend you to other similar shows to watch

Introduction to Big Data Lesson 1



  • What is Big Data?
  • Why big data? ( reasons of having big data)
  • 3 Vs of Big Data ( Volume- Velocity- Variety)


What is Big Data ? ( Arabic)

(البيانات الضخمة )

هي عبارة عن مجموعة البيانات الضخمة جداً والمعقدة لدرجة أنه يُصبح من الصعب معالجتها باستخدام أداة واحدة فقط من أدوات إدارة قواعد البيانات أو باستخدام تطبيقات معالجة البيانات التقليدية

  • What is big data and 3 Vs of Big Data ? (English)

Big data is similar to Regular data but in a high volume ( very big in size),and it’s getting generated in high velocity( very  fast) and its more than one type of data ( variety), so big data is in a simple terms a data that cant be fit in a regular computer and needs special type of storage and new ways of techniques to manage it ( it can’t be stored in a regular databases like Access or oracle)

  • Why Big Data?
    • Increase of storage capacities (like cloud computing – virtual drives – USB with gigabyte and terabyte of storage)
    • Increase of processing power (availability of Supercomputer- and smart computer like IBM Watson)
    • Availability of data (usually the data used to get generated by people , but now machines generates data as well , like in airports cameras are connected to software’s for facial recognition, in supermarkets previously very few who used to pay with ATM, now almost most of the people owns master card, growth of E-commerce like Amazon and Ebay..etc)