Business Intelligence Career Master Plan 1st Edition by Eduardo Chavez, Danny Moncada ISBN 9781801079693 1801079692

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Product details:
ISBN 10: 1801079692
ISBN 13: 9781801079693
Author: Eduardo Chavez, Danny Moncada

Navigating the challenging path of a business intelligence career requires you to consider your expertise, interests, and skills. Business Intelligence Career Master Plan explores key skills like stacks, coursework, certifications, and interview advice, enabling you to make informed decisions about your BI journey. You’ll start by assessing the different roles in BI and matching your skills and career with the tech stack. You’ll then learn to build taxonomy and a data story using visualization types. Additionally, you’ll explore the fundamentals of programming, frontend development, backend development, software development lifecycle, and project management, giving you a broad view of the end-to-end BI process. With the help of the author’s expert advice, you’ll be able to identify what subjects and areas of study are crucial and would add significant value to your skill set. By the end of this book, you’ll be well-equipped to make an informed decision on which of the myriad paths to choose in your business intelligence journey based on your skill set and interests.

Business Intelligence Career Master Plan 1st Edition Table of contents:

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

Data behavior in human resources

Data behavior in academia

Analytical thinking and problem-solving techniques

Problem-solving

Leveraging online tools for problem-solving

Web (Google) search

Stack Overflow

AI chatbots (ChatGPT/Bard)

Summary

Chapter 7: Business Intelligence Education

Academic programs, training courses, certifications, and books

Academic programs

Training courses and certificates

Data architecture books

Data modeling books

Data analysis and visualization books

Summary

Chapter 8: Beyond Business Intelligence

Business analytics

Cross-pillar reporting

Measuring your BI success

Executive briefing books

Customer-focused processes

Automation

BA final thoughts

Data science

Data exploration

Summary

Chapter 9: Hands-On Data Wrangling and Data Visualization

Technical requirements

Data analysis using Python

Data wrangling and visualization with Python

Step 1 – loading the dataset

Step 2 – an initial exploration of the dataset

Step 3 – remove duplicate rows

Step 4 – cleaning and transforming data

Step 5 – saving the cleaned dataset

Step 6 – load the cleaned dataset

Step 7 – creating visualizations to summarize the data

Tableau for data visualization

Tableau dashboard hands-on

Summary

Conclusion

Index

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Tags: Eduardo Chavez, Danny Moncada, Business Intelligence, Career Master Plan