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Rav Ahuja

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.

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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.

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What's inside

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.
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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.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Excellent for beginners new to the field of business intelligence (BI) and its applications in modern business
Teaches key concepts, components, and the benefits and challenges of implementing BI solutions
Provides insights into career opportunities and roles available in the BI arena and the skills and qualifications required
Covers a wide range of topics, including data ecosystems, BI analytics landscape, data repositories, and the extract, transform, and load (ETL) process
Delves into the role of statistical analysis in mining and visualizing data to identify patterns and trends
Offers practical exposure with hands-on activities and a final project that enables you to apply your knowledge in real-world scenarios

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Business Intelligence (BI) Essentials with these activities:
Review statistics and probability concepts
Refresh your statistics and probability knowledge to build a stronger foundation for data analytics.
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  • Review basic statistical concepts (mean, median, mode, standard deviation).
  • Review basic probability concepts (probability distributions, Bayes' theorem).
  • Practice solving statistical and probability problems.
Participate in a data analytics study group
Engage in collaborative learning and knowledge sharing with peers by participating in a data analytics study group.
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  • Find a study group or organize your own.
  • Set regular meeting times.
  • Discuss course materials, case studies, or projects.
  • Provide feedback and support to group members.
Solve data analytics practice problems
Reinforce your understanding of data analytics concepts by solving practice problems.
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  • Analyze the data using appropriate techniques.
  • Identify a data analytics problem.
  • Collect and clean the data.
  • Draw conclusions and make recommendations.
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Attend a webinar on advanced data analytics techniques
Expand your knowledge and skills by attending a webinar on advanced data analytics techniques.
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  • Find a relevant webinar.
  • Register for the webinar.
  • Attend the webinar and take notes.
  • Apply the techniques you learn to your own projects.
Create a data visualization dashboard
Enhance your analytical and visualization skills by creating an interactive data visualization dashboard.
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  • Identify a business problem or question.
  • Collect and clean the data.
  • Choose appropriate data visualization techniques.
  • Design and develop the dashboard.
  • Present and explain your dashboard to stakeholders.
Volunteer at a data analytics non-profit organization
Gain practical experience and make a meaningful contribution by volunteering at a data analytics non-profit organization.
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  • Find a suitable non-profit organization.
  • Contact the organization and inquire about volunteer opportunities.
  • Attend volunteer training.
  • Participate in data analytics projects or activities.
Develop a data analytics solution for a real-world problem
Apply your learning by developing a data analytics solution for a real-world problem.
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  • Identify a problem or opportunity.
  • Gather and clean the data.
  • Analyze the data and develop insights.
  • Design and implement a solution.
  • Evaluate the results.
Build a data analytics portfolio
Showcase your data analytics skills and expertise by building a portfolio of your work.
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  • Select your best data analytics projects.
  • Create case studies that highlight the problem, solution, and results.
  • Develop a website or online portfolio to showcase your work.
  • Share your portfolio with potential employers or clients.

Career center

Learners who complete Business Intelligence (BI) Essentials will develop knowledge and skills that may be useful to these careers:
Business Intelligence Analyst
Business Intelligence Analysts collect, analyze, interpret, and present data to help businesses make informed decisions. They may also develop and implement reporting systems and dashboards to track and measure business performance. This course provides a foundation in the key concepts and components of BI, as well as the skills and qualifications needed to succeed in this role.
Data Analyst
Data Analysts use data to solve business problems and improve decision-making. They may work with data from a variety of sources, including databases, spreadsheets, and social media. This course provides a foundation in the key concepts and components of BI, as well as the skills and qualifications needed to succeed in this role.
Data Scientist
Data Scientists use data to develop predictive models and identify trends. They may work with data from a variety of sources, including databases, spreadsheets, and social media. This course provides a foundation in the key concepts and components of BI, as well as the skills and qualifications needed to succeed in this role.
Data Engineer
Data Engineers design, build, and maintain data pipelines and infrastructure. They may work with a variety of data sources, including databases, data warehouses, and data lakes. This course provides a foundation in the key concepts and components of BI, as well as the skills and qualifications needed to succeed in this role.
Database Administrator
Database Administrators ensure that databases are running smoothly and efficiently. They may also be responsible for designing, implementing, and maintaining database security measures. This course provides a foundation in the key concepts and components of BI, as well as the skills and qualifications needed to succeed in this role.
Web Developer
Web Developers design and develop websites and web applications. They may also be responsible for testing, debugging, and deploying websites. This course provides a foundation in the key concepts and components of BI, as well as the skills and qualifications needed to succeed in this role.
Software Engineer
Software Engineers design, develop, and maintain software applications. They may also be responsible for testing, debugging, and deploying software. This course provides a foundation in the key concepts and components of BI, as well as the skills and qualifications needed to succeed in this role.
Information Security Analyst
Information Security Analysts protect computer systems and networks from unauthorized access, use, disclosure, disruption, modification, or destruction. They may also be responsible for developing and implementing security policies and procedures. This course provides a foundation in the key concepts and components of BI, as well as the skills and qualifications needed to succeed in this role.
Trainer
Trainers develop and deliver training programs to help employees learn new skills and improve their performance. They may also work with businesses to develop and implement training and development plans. This course provides a foundation in the key concepts and components of BI, as well as the skills and qualifications needed to succeed in this role.
Business Analyst
Business Analysts help businesses understand their needs and develop solutions to improve their operations. They may work with a variety of stakeholders, including customers, employees, and managers. This course provides a foundation in the key concepts and components of BI, as well as the skills and qualifications needed to succeed in this role.
Operations Research Analyst
Operations Research Analysts use mathematical and statistical techniques to solve problems in a variety of industries, including manufacturing, logistics, and healthcare. They may also work with businesses to develop and implement operational plans and strategies. This course provides a foundation in the key concepts and components of BI, as well as the skills and qualifications needed to succeed in this role.
Financial Analyst
Financial Analysts analyze financial data to make recommendations about investments and other financial decisions. They may also work with businesses to develop financial plans and strategies. This course provides a foundation in the key concepts and components of BI, as well as the skills and qualifications needed to succeed in this role.
Marketing Analyst
Marketing Analysts analyze marketing data to understand the effectiveness of marketing campaigns and make recommendations for improvements. They may also work with businesses to develop marketing plans and strategies. This course provides a foundation in the key concepts and components of BI, as well as the skills and qualifications needed to succeed in this role.
Technical Writer
Technical Writers create and maintain technical documentation, such as user manuals, white papers, and training materials. They may also work with businesses to develop and implement technical communication plans and strategies. This course provides a foundation in the key concepts and components of BI, as well as the skills and qualifications needed to succeed in this role.
Project Manager
Project Managers plan, organize, and execute projects. They may also be responsible for managing project budgets and schedules. This course provides a foundation in the key concepts and components of BI, as well as the skills and qualifications needed to succeed in this role.

Reading list

We've selected nine books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Business Intelligence (BI) Essentials.
Practical guide to machine learning for business users. It covers the basics of machine learning, as well as how to use machine learning to solve business problems.
Practical guide to data visualization. It covers the basics of data visualization, as well as how to use data visualization to communicate insights from data.
Beginner-friendly introduction to Power BI, a popular business intelligence software. It covers the basics of Power BI, as well as how to use Power BI to create dashboards and visualizations.
Practical guide to using Python for data analysis. It covers the basics of Python, as well as how to use Python to manipulate, clean, and analyze data.
Practical guide to using R for data science. It covers the basics of R, as well as how to use R to manipulate, clean, and analyze data.
Beginner-friendly introduction to big data. It covers the basics of big data, as well as how to use big data to improve business decision-making.
Comprehensive guide to Hadoop, a popular big data platform. It covers all the major features of Hadoop, including data storage, data processing, and data analytics.
Practical guide to data analytics. It covers the basics of data analytics, as well as how to use data analytics to solve business problems.

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