Description

Business Intelligence Certificate

Program Overview:

Knowing how to make decisions based off data is crucial for any business seeking success. By the end of this business intelligence certificate course, you will be able to not only understand big data and user-driven events but also interpret machine learning and apply it all in order to create successful product features as well as strategic solutions for businesses.

This course is designed to help you understand how to use data science techniques to identify business problems and find solutions. You will learn how to obtain and clean data, build models, and evaluate results. By the end of the course, you will be able to apply your knowledge in the workplace and make changes that lead to strategic success.

Students will learn to understand data and data governance and gain the capacity to use quantitative methods and the output from data analytics to make more data-informed decisions. The programme is ideal for managers interested in the basics of data analytics, how to work with data analytics specialists and how to frame business problems in such a way to arrive at informed decisions efficiently.

---

What will I learn?

• Clearly communicate to important decision-makers why your data should drive the decisions being made.

• Understand the basics of Big Data, Data Science and Machine Learning, as well as how to put them into practice in a web tech setting.

• Use data analysis, cleansing, and visualisation to develop data-driven products that resolve strategic business issues.

• Look at the data trends from the tools and figure out how you should change your approach.

• Analyze the drivers and strategies for data analytics and its impact on business decision making, and understand how businesses operate in today’s landscape.

• Demonstrate an understanding of the current data governance landscape and how it is impacted by changing business needs.

• Show a strong understanding of newer data analytics methods, comprehending their inputs and outputs. Also, be able to tell the difference between successful and unsuccessful output of various data analytic techniques.

• Be able to use quantitative methods for framing business problems and using the output of data analytics techniques in order to make informed business decisions.

The program includes training on the following topics:

• Big data – What it is, the challenges and opportunities
• Framing the business problem
• Data governance
• Data analytics
• Making decisions with data
• Data Acquisition and Cleaning
• Exploratory Data Analysis
• Statistical Modelling
• Machine Learning
• Communicating Results
• Ethical and Organizational Issues in Data Analytics

---

Course Outline:

Big data – What it is, the challenges and opportunities:

In this modules, students will learn about big data, its challenges and opportunities.

Framing the business problem:

In this module, students will learn how to frame business problems in order to make informed decisions with data analytics.

Data governance:

This module will cover the basics of data governance and how it is changing with the rise of big data.

Data analytics:

This module covers the different types of data analytics, their inputs and outputs. Students will also learn how to use quantitative methods for framing business problems and using the output of data analytics techniques in order to make informed business decisions.

Making decisions with data:

This module covers how to use data analytics to support decision making in businesses. Topics include data-driven product development, statistical modelling and machine learning.

Communicating results:

In this module, students will learn how to communicate their findings to stakeholders in a way that is clear and persuasive.

Ethical and organizational issues in data analytics:

This module covers ethical considerations when working with data, as well as the organizational implications of data analytics.

This course is designed for anyone who wants to understand how to use data science techniques to identify business problems and find solutions. The course covers the basics of data science, including data acquisition and cleaning, exploratory data analysis, statistical modelling, machine learning, and communicating results. By the end of the course, you will be able to apply your knowledge in the workplace and make changes that lead to strategic success.

Course Length: 8 weeks

Workload: 6-10 hours per week (Self-paced).

Effort: Medium

Prerequisites: There are no formal prerequisites for this course. However, students should have some basic knowledge of statistics and programming.

Course Format: The course is delivered through a mix of online video lectures, readings, quizzes, and assignments.

---

Glossary:

Big data: Big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate.

Data analytics: Data analytics is the science of examining raw data in order to draw conclusions about that information.

Data governance: Data governance is the process of ensuring that the right people have access to the right data at the right time.

Machine learning: Machine learning is a type of artificial intelligence that allows computers to learn from data without being explicitly programmed.

Statistical modelling: Statistical modelling is a mathematical technique used to identify relationships between variables in order to make predictions about future events.

Business intelligence and analytics:

Business intelligence (BI) is a term that refers to the various ways businesses use data to make informed decisions. Business analytics is a subset of BI that focuses on the statistical analysis of data to identify trends and Patterns.

Power BI:

Power BI is a cloud-based business intelligence service from Microsoft. It provides users with self-service tools for data visualization and analysis.

Data management:

Data management is the process of collecting, storing, and processing data. Data professionals, such as data analysts and database administrators, are responsible for managing data.

Data professionals:

Data professionals are individuals who work with data in some capacity. This includes roles such as data analyst, database administrator, and data scientist.

Business analyst:

A business analyst is a professional who uses data to help businesses make informed decisions. Business analysts typically have a background in business or economics and use their skills to understand how businesses operate.

Business intelligence certifications:

There are several certifications that businesses can use to ensure that their employees have the necessary skills to work with data. These certifications include the Certified Business Intelligence Professional (CBIP) and Certified Analytics Professional (CAP).

Data visualizations:

Data visualizations are graphical representations of data. They can be used to communicate complex information in a easy-to-understand format.

Data analyst:

A data analyst is a person who analyses data to understand trends and patterns. Data analysts typically have a background in statistics or computer science.

Visual analytics:

Visual analytics is the process of using data visualizations to gain insights into data. It can be used to identify trends, outliers, and Patterns.

Business processes:

Business processes are the set of activities that a business undertakes to achieve its goals. These processes can be divided into four categories: operational, managerial, analytical, and strategic.

Certification exam:

A certification exam is a test that individuals take in order to earn a credential that attests to their knowledge or skills. Business intelligence certifications exams include the Certified Business Intelligence Professional (CBIP) and Certified Analytics Professional (CAP).

Business insights:

Business insights are actionable information that businesses can use to make informed decisions. Insights can be generated through data analysis, business intelligence, and market research.

Business analytics:

Business analytics is the process of using data to gain insights into business performance. Business analytics can be used to identify trends, optimize processes, and make predictions about future events.

Data models:

A data model is a graphical representation of the relationships between data. Data models can be used to understand complex information and make predictions about future events.

Data foundations exam:

The Data Foundations Exam is an entry-level exam for individuals who want to become certified in business intelligence. The exam covers basic concepts in data management, data analysis, and data visualization.

Data analysis tools:

There are many different tools that data analysts can use to analyze data. Some common tools include Excel, Tableau, and R.

Data integration:

Data integration is the process of combining data from multiple sources into a single dataset. Data integration can be used to clean and enrich data, as well as to identify trends and patterns.

Data repositories:

A data repository is a location where data is stored. Data repositories can be either local or cloud-based. Common types of data repositories include databases and data warehouses.

Data processes:

Data processes are the set of activities that are carried out in order to transform raw data into insights. Data processes typically involve cleaning, filtering, and analyzing data.