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Business Intelligence Career Master Plan

Business Intelligence Career Master Plan

By : Chavez, Moncada
4.8 (12)
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Business Intelligence Career Master Plan

Business Intelligence Career Master Plan

4.8 (12)
By: Chavez, Moncada

Overview of this book

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.
Table of Contents (12 chapters)
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Data science

The field of BI has made immense progress in the past few decades. BI tools such as data warehousing, data mining, analytics, and reporting enable organizations to make better decisions by providing them with valuable insights into their operations. However, in recent years, there has been a growing sense of disillusionment among users, who are beginning to realize that despite the advances in BI, many important questions remain unanswered. The need to move beyond BI (BBI) is becoming increasingly evident.

BBI is a concept that encompasses a variety of different approaches to data analysis beyond conventional BI tools. These approaches include but are not limited to AI, ML, deep learning (DL), and predictive modeling. These are data analysis paradigms that go beyond traditional BI, which is primarily focused on the descriptive analysis of historical data. BBI, on the other hand, enables predictive or prescriptive analytics, which can help organizations to make forecasts...

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