Summary: Bia

Read the summary and the most important questions on BIA

• 1 Week 1

• 1.1 Lecture 01: Setting the Stage

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• What is clickstream data?

  The "journey" you follow when browsing through the internet, and clicking from page to page.

• What is descriptive analytics?

  Focus on 'What happend'
  Dashboards, excel sheets, past data.

• What are examples of predictive analytics?

  Describing trends
  Regression Analysis

• What does a Business Analyst typically do?

  Uses BI tools and applications to understand and improve business conditions and business processes.
  

  • Descriptive analytics

• What does a Data Scientist typically do?

  Use advanced algorithms and interactive exploration tools to uncover non-obvious patterns in data.
  

  • Predictive and Prescriptive analytics
  • Has a multidisciplinary background

• What is the role of a Data Architect?

  • IT specialists that design and manage data systems.
  • Sets policies for how data is stored and accessed
  • Coordinates various data sources
  • Integrates new data technologies into existing IT infrastructure   

• What is the role of a Data Engineer?

  • Build system that collect, manage and convert raw data into usable information
  • Make data accessible so that it can be used to evaluate and optimize organizational performance.

• How do organisations use big data in practice?

  Improving existing business models by using
  

  • New data (sensors, social media)
  • New insight (outlier detection, big data techniques)
  • New action (faster response to change in sentiments)

  
  Innovate the business model
  

  • Data monetization by wrapping: (enriching core products with data)
  • Data monetization by selling (offering info for sale)
  • Data monetization by bartering ( trading info)
  • Digital Transformation (becoming active in new industries)

   

• 1.2.1 Data Driven Business Models - Hartmann et al.

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• What are data driven business models?

  Business Models supporting data related-ventures to capture value.

• What are the six clusters of Data Driven Business Models?

  1. Free data collector and aggregator
  2. Analytics as a service
  3. Data generation and analysis
  4. Free data knowledge and discovery
  5. Data aggregation as a service
  6. Multi-source data mash up and analysis