Challenges along the way

Introduction to Data Culture

Joanne Xiong

Content Developer, DataCamp

Challenges exist

  • Building a data culture is essential for business success
  • The process will be challenging!

Kodak

Introduction to Data Culture

Classifying challenges

                    People Challenge

  • The human aspects of an organization
  • Examples:
    • Data silos
    • Data literacy
    • Data ethics

                    Process Challenge

  • The systems, procedures, workflows
  • Examples:
    • Data quality
    • Data privacy
    • Data security
Introduction to Data Culture

People - data silos

  • Occur when information is isolated within teams or departments
  • Hamper collaboration, limit organizational understanding
  • Example:
    • Ford's siloed data storage
  • Solutions:
    • Centralized data team/data management system

Single arrow flow-chart illustrating that robust data culture promotes cross-functional collaboration.

Introduction to Data Culture

People - data silos

  • Occur when information is isolated within teams or departments
  • Hamper collaboration, limit organizational understanding
  • Example:
    • Ford's siloed data storage
  • Solutions:
    • Centralized data team/data management system

Double arrow flow-chart illustrating the mutual relationship between robust data culture and cross-functional collaboration.

Introduction to Data Culture

People - data literacy

  • Reluctance to gain new skills and adapt to changing data trend
  • Failure to invest in long-term commitment
  • Example:
    • Assume all employees have the same level of data literacy
  • Solutions:
    • Customized training program
    • Continuously monitoring and refining
Introduction to Data Culture

People - data ethics

  • Responsible, fair, and transparent data usage
  • Example:
    • Amazon's biased hiring algorithm
  • Solutions:
    • Establish clear ethical guidelines
    • Foster open discussion

A photo of Amazon's office building.

Introduction to Data Culture

Process - data quality

  • Data needs to be:
    • Accurate
    • Reliable
    • Up-to-date
  • Example:
    • Uber's "Greyball" resulted in severe consequences
  • Solutions:
    • Implement data validation process
    • Leverage automated data cleansing tools
Introduction to Data Culture

Process - data privacy & security

  • Extended data usage may lead to overlook of data privacy and data security
  • Protecting sensitive information maintains customer trust and avoid potential breaches
  • Example: 2017 Equifax data breach
  • Solutions:
    • Implement access controls
    • Apply encryption techniques
    • Conduct regular security checks

Equifax office building

1 https://www.wsj.com/articles/equifax-to-add-more-buy-now-pay-later-plans-to-credit-reports-11639915203
Introduction to Data Culture

Let's practice!

Introduction to Data Culture

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