Business intelligence career master plan launch and advance your BI career with proven techniques and actionable insights /

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Chavez, Eduardo (Autor), Moncada, Danny (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham : Packt Publishing, Limited, 2023.
Temas:
Business intelligence > Vocational guidance.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • Cover
  • Title Page
  • Copyright
  • Dedication
  • Foreword
  • Contributors
  • Preface
  • Chapter 1: Breaking into the BI World
  • Where to start?
  • BI roles
  • Problem solving
  • Specific industry knowledge and subject matter expertise
  • Communication skills
  • Statistical analysis
  • Technical knowledge
  • Business acumen
  • Keep up with innovation
  • Potential entrances to the BI world
  • BI roadmap
  • ETL developers
  • Data architects
  • Data modelers
  • BI developers
  • Data scientists
  • Technology solutions stack
  • Non-technical data analysis
  • Case 1
  • Case 2
  • Case 3
  • Case 4
  • Case 5
  • Summary
  • Chapter 2: How to Become Proficient in Analyzing Data
  • Building a taxonomy of your data sources
  • How to use a BI tool to explore data
  • Understanding your data needs
  • Summary
  • Chapter 3: How to Talk Data
  • Presenting data
  • Know your audience
  • Choose the right visualization
  • Keep it simple
  • Use color and formatting effectively
  • Provide context
  • Tell a story
  • High-level dashboards
  • Operational reports
  • Talking to stakeholders
  • Data visualization taxonomy
  • Bar charts
  • Line charts
  • Pie charts
  • Scatter plots
  • Area charts
  • Heat maps
  • Bubble charts
  • Gauge charts
  • Tree maps
  • Box plots
  • Advanced data visualizations
  • Sankey diagrams
  • Bullet charts
  • Taxonomy diagrams
  • Pareto diagrams
  • Decision tree for picking a visualization
  • Storytelling
  • Summary
  • Chapter 4: How To Crack the BI Interview Process
  • Finding the right interview
  • Building a business problem and data solutions matrix
  • Potential business cases and solutions
  • Teamwork
  • Customer service
  • Adaptability
  • Time management
  • Communication
  • Motivation and values
  • A hypothetical BI interview process and what to expect
  • General business intelligence interview questions
  • Scenario-based BI questions
  • Business case study questions
  • SQL business intelligence interview questions
  • Database design business intelligence questions
  • Python business intelligence interview questions
  • Summary
  • Chapter 5: Business Intelligence Landscape
  • The current landscape and the most effective technologies to study
  • Collecting data
  • Storing data
  • Cleaning and preparing data
  • Analyzing data with BI tools
  • Focusing on user experience
  • The use of AI
  • BI developer versus BI architect versus data engineer versus data modeler versus business analyst
  • Business acumen
  • Increased productivity
  • Automation
  • Templating
  • Standardization
  • Monitoring systems
  • Efficient team management
  • Summary
  • Chapter 6: Improving Data Proficiency or Subject Matter Expertise
  • Data proficiency
  • Concluding thoughts
  • Subject matter expertise
  • Concluding thoughts
  • Data behavior in different business units
  • Data behavior in marketing
  • Data behavior in sales
  • Data behavior in finance and accounting
  • Data behavior in operations

Ejemplares similares