Two Words
Data & Analysis
Data : oil, Electricity, everywhere, every time, even now.
Analysis : Answer how and Why ?
Analysis :
Data analysis is the process of collecting, modeling, and analyzing data to extract insights that support decision-making. There are several methods and techniques to perform analysis depending on the industry and the aim of the investigation
Why Is Data Analysis Important?
Informed decision-making:
Reduce costs| Increase Profits
Target Customers Better
DA is a Process
Identify-Collect-Clean-Analyze-Interpret or Infer- Act
(ICCAIA)
Types of DA
1.Descriptive: What ?-Data to Valuable Insights
2.Exploratory: How ?-To generate Hypothesis to solve specific 3.Problems
4.Diagnostic : Why ? - To tackle and to cure
5.Predictive : What if ? - Future Projection
6.Prescriptive : IF-?.Then-This :
Top DA Methods
1. Cluster Analysis: Similar elements - Grouping Data
2. Cohort Analysis : Historical data to examine and compare -Google Analytics:
3. Regression Analysis - y=mx+c
4. Factor Analysis : Dimension Reduction
5. Neural Networks : Mimic Human Brain to find solutions
6. Data Mining: Identify patterns, Dependencies, realations, Trends
7. Text Analysis : Actional Insights with Relevant Data
8. TimeSeries Analysis : Data Collected over a specified period of time.
9. Decison Trees: To support smart and strategic Decisions
10. Conjoint Analysis : How individuals value different attributes of a product or Service
Top 17 Data Analysis Techniques:
Collaborate your needs
Establish your questions
Data democratization
Think of data governance
Clean your data
Set your KPIs
Omit useless data
Build a data management roadmap
Integrate technology
Answer your questions
Visualize your data
Interpretation of data
Consider autonomous technology
Build a narrative
Share the load
Data Analysis tools
Refine your process constantly
Quality Criteria For Data Analysis
Internal Validity
External Validity
Reliability
Objectivity
Application of DA:
Academics: Universities and academic institutions can perform data analysis to measure student performance and gather insights on how certain behaviors can further improve education.
Human Resources: Organizations can use data analysis to offer a great experience to their employees and ensure an excellent work environment. They can also utilize the data to find out the best resources whose skill set matches the organizational goals
Communication is very Important
Qualitative
Stephen Few - 8 Types of Quantitative Messages out of DA:
1. Time Series : Line Chart
2. Ranking : Bar Chart
3. Part-to-Whole : Pie Chart
4. Deviation: Bar Comparison : Actual Vs Variation
5. Frequency Distribuition : Histogram
6. Correlation: Scatter Plot
7. Nominal Comparison : bar Chart
8. Geographical : Cartogram
Quantitative
mean, median, mode, Standard deviation, chi-square, eigen vector
Free software for data analysis
Notable free software for data analysis include:
DevInfo – A database system endorsed by the United Nations Development Group for monitoring and analyzing human development.[149]
ELKI – Data mining framework in Java with data mining oriented visualization functions.
KNIME – The Konstanz Information Miner, a user friendly and comprehensive data analytics framework.
Orange – A visual programming tool featuring interactive data visualization and methods for statistical data analysis, data mining, and machine learning.
Pandas – Python library for data analysis.
PAW – FORTRAN/C data analysis framework developed at CERN.
R – A programming language and software environment for statistical computing and graphics.[150]
ROOT – C++ data analysis framework developed at CERN.
SciPy – Python library for data analysis.
Julia - A programming language well-suited for numerical analysis and computational science.
