DataAnalysis

LinkedIn 2011-11 technology active
Also known as: DataAnalyticsDataScienceBusinessIntelligence

What It Is

The process of inspecting, cleaning, transforming, and modeling data to discover useful information, draw conclusions, and support decision-making. Became one of the most in-demand professional skills of the 2010s-2020s.

Data Analyst vs Data Scientist

Data Analyst:

  • Interpret existing data
  • Create dashboards and reports
  • SQL and Excel proficiency
  • Answer business questions
  • Communicate findings to stakeholders

Data Scientist:

  • Build predictive models
  • Machine learning expertise
  • Programming (Python, R)
  • Statistics and mathematics
  • Answer questions not yet asked

Boundary blurred in practice; many “data scientist” jobs were actually analyst roles.

Essential Skills

Technical:

  • SQL (querying databases)
  • Excel/Google Sheets
  • Python or R programming
  • Data visualization (Tableau, Power BI)
  • Statistical analysis
  • ETL (Extract, Transform, Load)

Business:

  • Domain knowledge
  • Problem-solving
  • Communication (translate technical → business)
  • Critical thinking
  • Asking right questions

Common Tools & Technologies

Business Intelligence:

  • Tableau
  • Power BI (Microsoft)
  • Looker (Google)
  • Qlik

Programming:

  • Python (pandas, numpy, matplotlib)
  • R (tidyverse, ggplot2)
  • Jupyter notebooks

Databases:

  • SQL (MySQL, PostgreSQL, SQL Server)
  • NoSQL (MongoDB, Redis)
  • Cloud warehouses (Snowflake, BigQuery, Redshift)

The Analytics Maturity Model

Level 1 - Descriptive: What happened?
Level 2 - Diagnostic: Why did it happen?
Level 3 - Predictive: What will happen?
Level 4 - Prescriptive: What should we do?

Most organizations struggled to move past Level 1.

Data-Driven Culture

“Data-driven decision making” became corporate mantra:

  • A/B testing everything
  • Metrics dashboards
  • OKRs and KPIs
  • Attribution modeling
  • Experimentation platforms

But also led to analysis paralysis and ignoring qualitative insights.

Career Growth

Data analysis career paths:

  1. Junior Data Analyst
  2. Data Analyst
  3. Senior Data Analyst
  4. Analytics Manager
  5. Director of Analytics
  6. VP Data/Chief Data Officer

Alternatively: specialize (Marketing Analytics, Financial Analytics, Product Analytics)

Sources

Explore #DataAnalysis

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