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IBM

Business Intelligence (BI) Essentials

IBM via Coursera

Overview

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This course provides a comprehensive introduction to business intelligence (BI), its key concepts, components, and the benefits and challenges of implementing BI solutions. It also discusses career opportunities and roles available in the BI arena and the skills and qualifications required. You will also gain insight into the data ecosystem, BI analytics landscape, data repositories, and the extract, transform, and load (ETL) process. Additionally, you will be introduced to the role of statistical analysis in mining and visualizing data to identify patterns and trends and how to weave a compelling story with data. The course offers practical exposure with hands-on activities and a final project that enables you to apply your knowledge in real-world scenarios. This specialized program is tailored for individuals interested in pursuing a career as a BI analyst, and no prior data analytics experience or degree is required to take this course.

Syllabus

  • Introduction to Business Intelligence (BI)
    • This module introduces you to the field of BI. You will gain insight into the key concepts of BI, understand its importance in modern business operations, and explore the benefits and challenges associated with implementing BI solutions through various examples. You will also gain insight into how BI, data analytics, data science, and data engineering are different. Additionally, you will learn about the career opportunities and roles in BI and the skills and qualifications to develop a successful career in this field. By the end of the module, you will have a fundamental foundation in BI and be able to apply your knowledge to understand its significance in real-world business scenarios.
  • The Data Ecosystem
    • In this module, you will learn about the different types of data structures, file formats, sources of data, and the languages data professionals use in their day-to-day tasks. You will gain insight into various types of data repositories, such as databases, data warehouses, data marts, data lakes, and data pipelines. In addition, you will learn about the extract, transform, and load (ETL) process, which is used to extract, transform, and load data into data repositories. Finally, the module also provides an overview of big data and big data processing tools such as Apache Hadoop, Hadoop Distributed File System (HDFS), Hive, and Spark.
  • BI Analytics Landscape
    • This module explores the ecosystem of business intelligence (BI) analysts and provides insights into the types of analytics, such as descriptive, diagnostic, predictive, and prescriptive analytics, and understanding their unique contributions to data analysis. You will also learn about the key BI components that make up its process and the relevance of key performance indicators (KPIs) and metrics used in evaluating business performance. Additionally, you will gain insight into different BI technologies and tools used, the differences between these technologies, and how to analyze the business context, processing requirements, and objectives of a BI project to gain a comprehensive understanding of its scope and potential impact. Finally, the module introduces you to the overall BI process and delves into the privacy and security issues and the necessary regulatory compliance.
  • Gathering and Wrangling Data
    • In this module, you will learn how to identify, gather, and import data from disparate sources. You will learn about the tasks involved in wrangling and cleaning data to prepare it for analysis. In addition, you will learn about different tools that can be used for gathering, importing, wrangling, and cleaning data, along with some of their characteristics, strengths, limitations, and applications.
  • Mining and Visualizing Data and Communicating Results
    • In this module, you will learn about the role of statistical analysis in mining and visualizing data. You will also be introduced to various statistical and analytical tools and techniques that can be used to gain a deeper understanding of your data. These tools help you analyze the patterns, trends, and correlations in data. Additionally, you will learn about various types of data visualizations to communicate and tell a compelling story and different tools that can be used for mining and visualizing data, along with some of their characteristics, strengths, limitations, and applications. Finally, the module delves into how you can effectively present the BI insights you have gained.
  • Applying BI Techniques and Final Project
    • In this module, you will identify and apply the right BI techniques and tools to various real-world business scenarios and develop a comprehensive BI project. You will also gain an opportunity to apply your acquired knowledge and skills in a hands-on assignment.

Taught by

Rav Ahuja

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4.8 rating at Coursera based on 102 ratings

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