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Data Analysis:Unveiling
Insights
By Ananthu.A.Ghosh
Introduction to Data Analysis
• Data analysis is the process of inspecting ,cleansing ,transforming , and
modeling data with goal of discovering useful information, informing
conclusions, and supporting decision-making.
Why Data Analysis Matters ?
• Informed Decision Making
• Performance Evaluation and Optimization
• Risk Management
• Cost-Efficiency and Resource Allocation
• Customer Insights and Satisfaction
• MarketTrends and Competition Analysis
• Predictive Analysis and Forecasting
• Compliance and Regulation Adherence
• Innovation and Research
• Real-Time Decision Support
Types of Data Analysis
• Descriptive Analysis
• Diagnostic Analysis
• Exploratory Analysis
• Inferential Analysis
• Predictive Analysis
• Prescriptive Analysis
• Causal Analysis
• Time Series Analysis
• Text Analysis
• Spatial Analysis
• Qualitative Analysis
• Quantitative Analysis
• Big Data Analysis
• MetaAnalysis
• Sentiment Analysis
Data Collection Methods
• Data collection is a fundamental step in the data analysis process .The method
chosen for data collection greatly impacts the quality and relevance of the data
.Here are some common data collection methods used in data analysis.
• They are surveys and questionnaires,interviews,observational
studies,experiments,case studies,focus groups,diaries and logs,sensors data
collection,web scraping,document analysis,audio and video
recordings,census,social media and online data collection ,mail and email surveys.
Data AnalysisTechniques:
Data mining
Using automated methods to discover
patterns , trends, and insights from
large datasets, often employing
techniques from machine learning and
statistics.
Network Analysis:
Analyzing relationship and connections
in a network to understand the
structure and dynamics of networks,
often used in social network analysis.
Case Studies
NASA:Mars Rover
Mission:
NASA’s mars rover mission involve
extensive data analusis to interpret the
scientific data sent by rovers.Analysis of
soil sample,rock composition, and
atmospheric data has provided valuable
insights into mars geological and
environment history.
THANKYOU !...........
Presentation by Ananthu.A.Ghosh

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Data Analysis by Ananthu.A.Ghosh.pptx

  • 2. Introduction to Data Analysis • Data analysis is the process of inspecting ,cleansing ,transforming , and modeling data with goal of discovering useful information, informing conclusions, and supporting decision-making.
  • 3. Why Data Analysis Matters ? • Informed Decision Making • Performance Evaluation and Optimization • Risk Management • Cost-Efficiency and Resource Allocation • Customer Insights and Satisfaction • MarketTrends and Competition Analysis • Predictive Analysis and Forecasting • Compliance and Regulation Adherence • Innovation and Research • Real-Time Decision Support
  • 4. Types of Data Analysis • Descriptive Analysis • Diagnostic Analysis • Exploratory Analysis • Inferential Analysis • Predictive Analysis • Prescriptive Analysis • Causal Analysis • Time Series Analysis • Text Analysis • Spatial Analysis • Qualitative Analysis • Quantitative Analysis • Big Data Analysis • MetaAnalysis • Sentiment Analysis
  • 5. Data Collection Methods • Data collection is a fundamental step in the data analysis process .The method chosen for data collection greatly impacts the quality and relevance of the data .Here are some common data collection methods used in data analysis. • They are surveys and questionnaires,interviews,observational studies,experiments,case studies,focus groups,diaries and logs,sensors data collection,web scraping,document analysis,audio and video recordings,census,social media and online data collection ,mail and email surveys.
  • 6. Data AnalysisTechniques: Data mining Using automated methods to discover patterns , trends, and insights from large datasets, often employing techniques from machine learning and statistics.
  • 7. Network Analysis: Analyzing relationship and connections in a network to understand the structure and dynamics of networks, often used in social network analysis.
  • 8. Case Studies NASA:Mars Rover Mission: NASA’s mars rover mission involve extensive data analusis to interpret the scientific data sent by rovers.Analysis of soil sample,rock composition, and atmospheric data has provided valuable insights into mars geological and environment history.