CONCEPT/FRAMEWORK BIG DATA ANALYTICS ACTIVITIES

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1 Manajemen Bisnis Telekomunikasi & Informatika Mata Kuliah: Big Data And Data Analytics Oleh: Tim Dosen CONCEPT/FRAMEWORK BIG DATA ANALYTICS ACTIVITIES

2 Telkom University Outline Fakultas Ekonomi dan Bisnis o o o o Review Data Analytics & Big Data (last week topics) Understanding Data Activity / Storytelling Based on Data Type (Model Based) Asking the Questions to Data 2 Creating the great business leaders

3 Telkom University Fakultas Ekonomi dan Bisnis Definitions Analytics: the systematic computational analysis of data or statistics (Google Definition) the method of logical analysis (Merriam Webster) Analysis of data is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decisionmaking. Data science is an interdisciplinary field about processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured, [1][2] which is a continuation of some of the data analysis fields such as statistics, data mining, and predictive analytics (From Wikipedia, by many references) and many more.. 1. Dhar, V. (2013). "Data science and prediction". Communications of the ACM. 56 (12): 64. doi: / Jeff Leek ( ). "The key word in "Data Science" is not Data, it is Science". Simply Statistics. 3 Creating the great business leaders

4 Telkom University Fakultas Ekonomi dan Bisnis Data Science Based on aforementioned definitions, we can conclude that Data Analytics includes: Data engineering Scientific Method Math Statistics Data Engineering may includes: Data Gathering Data Mining Data Transformation Data Cleansing etc. Ref: many sources 4 Creating the great business leaders

5 Telkom University Recall Fakultas Ekonomi dan Bisnis Our approach to Big Data 5 Creating the great business leaders

6 Telkom University Fakultas Ekonomi dan Bisnis Big Data Approach Framework Some people prefer 3Vs, 6Vs or 7Vs even 12Vs to explain big data. But the original bigness measurement metrics are volume, velocity, and variety. For example 7Vs: 1. Volume 2. Velocity 3. Variety 4. Variability 5. Veracity 6. Visualitazion 7. Value 6 Creating the great business leaders

7 Telkom University Fakultas Ekonomi dan Bisnis 7 Creating the great business leaders

8 Data Telkom University Analytics Workflow Data Set Data Analytics Methods Knowledge 8 Creating the great business leaders

9 Big Telkom Data University Analytics Constructors 9 Creating the great business leaders

10 Telkom University Fakultas Ekonomi dan Bisnis UNDERSTANDING DATA : High Dimensional Data Dimension / Attributes / Properties Name Address Occupation Age Blood Type Marital.. Sex Agus Jl. Mawar 1 Artist 30 A Married.. Male Andry Jl. Kucing 50 Lawyer 32 O Married.. Male Beatrice Jl. Raya 27 Student 21 O Single.. Female Ben Jl. Diponegoro 12 Driver 37 AB Married.. Male Zorro Jl. Dago 34 Student 18 B Single... Male High Dimensional Data, add up complexity problem to Big Data Analytics Curse : High space searching, Summarization, Reduction (PCA) Blessing : Comprehensive data knowledge High Dimensonal Data Analysis : Curse and Blessing of Dimensionality Donoho (2000) 10 Creating the great business leaders

11 UNDERSTANDING Telkom University DATA : Network vs Non Network Data Name Sex Age Number of Friend Agus Cecep Dita Rina Agus Agus Male 25 2 Cecep Male 23 3 Dita Sex 21 2 Rina Sex 22 1 Non Network Data Cecep Dita Rina Network Data Agus Dita Cecep Rina 11 Creating the great business leaders

12 Telkom University Fakultas Ekonomi dan Bisnis UNDERSTANDING DATA : Structured vs UnStructured Data 12 Creating the great business leaders

13 Telkom University Fakultas Ekonomi dan Bisnis 13 Creating the great business leaders

14 Telkom University Fakultas Ekonomi dan Bisnis Characteristics Stuctured Data Well defined content Easily understood Stored in RDBMS Easy to enter, store, and analyze Example: Data in database table (customer data, sales data, sensor data) Unstructured Data Structure not obvious Process data to understand RDBMS not a good fit Difficult and costly to analyze Example: , video files, audio files, web pages, presentations, social media feeds 14 Creating the great business leaders

15 UNDERSTANDING Telkom University DATA : SQL vs NoSQL *NoSQL: Not only SQL SQL NoSQL 15 Creating the great business leaders

16 Telkom University Fakultas Ekonomi dan Bisnis 16 Creating the great business leaders

17 Telkom University Fakultas Ekonomi dan Bisnis 17 Creating the great business leaders

18 Telkom University Fakultas Ekonomi dan Bisnis MODELLING FRAMEWORK 18 Creating the great business leaders

19 Case Studies : Data Analytics Common Roles Telkom University 1. Estimation 5. Association 2. Predictions 4. Clustering 3. Classification 19 Creating the great business leaders

20 1. Estimation Telkom University Estimate Pizza Time Delivery Customer Number of Order (O) Number of Traffic Light (TL) Distance (D) Delivery Time (T) Learning with Estimation Methods (Regresi Linier) Label Delivery Time (T) = 0.48O TL + 0.5D Knowledge 20 Creating the great business leaders

21 Output/Pola/Model/Knowledge Telkom University 1. Formula/Function (Rumus atau Fungsi Regresi) DELIVERY TIME = DISTANCE TRAFFIC LIGHT ORDER 2. Decision Tree (Pohon Keputusan) 3. Correlation and Association 4. Rule (Aturan) IF ipk>3.5 THEN lulus cum laude 5. Cluster (Klaster) 21 Creating the great business leaders

22 2. Telkom Prediction University Label Predict Stock Price Stock price data set in a form of time series (rentet waktu) model Learning with Prediction(Neural Network) 22 Creating the great business leaders

23 2. Telkom Prediction University Predict Stock Price Knowledge in a form of Neural Network Model Prediction Plot 23 Creating the great business leaders

24 3. Telkom Classification University Student Number Sex National Final Score Classify Student Graduation Time School Origin IPS1 IPS2 IPS3 IPS 4... Graduation Status L 28 SMAN On Time P 27 SMA DK Late P 24 SMAN Late L 26.4 SMAN On Time L 23.4 SMAN On Time Label Learning with Classification Methods(C4.5) 24 Creating the great business leaders

25 3. Telkom Classification University Classify Student Graduation Time Knowledge in a form of Decision Tree Model 25 Creating the great business leaders

26 3. Telkom Classification University Golf Playing Time Recommendation Input Output (Rules) If outlook = sunny and humidity = high then play = no If outlook = rainy and windy = true then play = no If outlook = overcast then play = yes If humidity = normal then play = yes If none of the above then play = yes 26 Creating the great business leaders

27 3. Telkom Classification University Golf Playing Time Recommendation Output Decision Tree 27 Creating the great business leaders

28 3. Telkom Classification University Contact Lens Recommendation Input Output 28 Creating the great business leaders

29 4. Telkom Clustering University Finding Iris Flower Cluster Input Dataset without Label Learning with Clustering Methods (K-Means) 29 Creating the great business leaders

30 Telkom University Fakultas Ekonomi dan Bisnis 4. Clustering Finding Iris Flower Cluster Output (Distance Plot) 30 Creating the great business leaders

31 5. Telkom Association University Association Product Sold Learning with Association Method (FP-Growth) 31 Creating the great business leaders

32 5. Telkom Association University Association Product Sold Output (Association Rules) 32 Creating the great business leaders

33 Telkom University Fakultas Ekonomi dan Bisnis 5. Association association rule algorithm objective is to find some attributes which has shown up together Example, on Thursday night, 1000 customer has bought 200 orang membeli Soap, where from 200 who bought soap, 50 among them bought Fanta In association rule, we have If buy Soap, then buy Fanta, with support value = 200/1000 = 20% and confidence value= 50/200 = 25% Some association rule algorithm are : A priori algorithm, FP-Growth algorithm, GRI algorithm 33 Creating the great business leaders

34 Telkom University Assignment (in The Class) o Find a Case Study of Big Data Implementation / Application for Business or others o State the objective, problems, solution idea o State the methodology used (explain) o State the model, measurement, accuracy 34 Creating the great business leaders

35 Telkom University Assignment (at home) o Find a Case Study of Big Data Implementation / Application for Business or others o State the objective, problems, solution idea o State the methodology used (explain) o State the model, measurement, accuracy, evaluation o Learn Big Data online free course ( 35 Creating the great business leaders

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