Data Analysis - The Web of Data


 Data Analysis

Data Analysis

Glean useful information to make informed decisions.

(1). Data Analytics Process

○ Data Categorizing:

Data can be distributed by a range of different categories such as age, population, income etc.

○ Data Soliciting:

Data can be solicited through various sources, networks, personnel, and references from the community.

○ Data Organizing:

Data organization can take place on a spreadsheet or other type of software that is effective in taking analytical data.

○ Data Cleaning:

Cleaning the data helps to correct or exclude any mistakes before the data goes to a data analyst for analysis.

Data Analytics Process

(2). Classification of Analytics

○ Descriptive: What is happening?:
  • Correct Data
  • Effective Exploratory data analysis
○ Diagnostic: Why is it happening?:
  • Finding the causes
  • Seaparating all the patterns
○ Predictive: What is likely to happen?:
  • Choosing the right algorithmBuilding the right business strategies
○ Prescriptive: What did I need to do?:
  • Using the advance analytics
  • Recommended actions
○ Cognitive Analysis:
  • Neurological and Behavioral analysis

(3). Data Analytics Techniques

○ Quantitative Data Analysis:
  • Regression Analysis

Examines relationships between two variables

  • Hypothesis Analysis

Tests whether a hypothesis is true

○ Qualititative Data Analysis:
  • Content Analysis

Measure content changes over time and across media

  • Discourse Analysis

Explore conversations in their social context

Data Analytics Techniques

(4). Data Analysis Tools

  • R and PythonMicrosoft Excel
  • Power BI
  • Tableau
  • RapidMiner
  • Apache Spark
  • QlikView
  • Talend
  • Splunk
  • SAS Business Objects
  • Sisense
Data Analysis Tools

(5). Data Analytics Applications

  • Customer Insight
  • Smarter Healthcare
  • Science & Research
  • Business Insights
  • Traffic Control
  • Retail Solutions
  • Finance
  • Sports Performance
  • Risk Management
  • Homeland security