Introduction to Business Analytics
- Description
- Curriculum
- FAQ
- Reviews
This is a non-technical program; no coding background is required.
This course introduces big data analytics, statistics, and data-driven decision-making for all business professionals, including those without prior analytics knowledge.
Analytical skills are essential in any business. There is a growing need for employees across all areas to know how to read, interpret, and present data in a way that can be understood across all functions and inform decision-making. Analytics is listed in 2024 as one of the top 10 skills requested by employers and recruiters. Almost every company in the world uses data to make better decisions.
This comprehensive course offers a detailed overview of the field of business and marketing analytics and data science. The course materials cover a wide range of topics, including data mining, predictive modeling, business intelligence, and machine learning. By studying these topics, you will gain an in-depth understanding of how data can be used to inform business decisions. Additionally, you will learn about tools and techniques such as statistical analysis, data visualization, and data storytelling to effectively communicate insights to stakeholders. By the end of the course, you will have the skills and knowledge needed to make data-driven decisions that can drive business growth and success.
It introduces the different analytics methodologies and how they are used. It is not intended to prepare learners to perform analytics themselves but to learn what analytics can do. If you are curious about the different analytics techniques and the possibilities they offer, this course is for you.
The course lasts around 4 hours and includes quizzes, assignments, and a final test you must pass to get the certificate.
-
2
Definition of AnalyticsIn this lecture, you will know where the definition of analytics and that is a vast domain with many methods.
-
3
History of Analytics
Analytics started thousands of years ago and has evolved quickly in the last decades.
-
4
Analytics Buzz Words
Big Data, AI, NLP; You heard these nearly everyday but what do they actually mean?
-
5
Module 1 QuizzA quick knowledge quiz after the introductory module
-
9
Business Intelligence
An effective Business Intelligence system serves as a mechanism to identify key patterns and trends producing actionable Information
-
10
Dashboard "Escape Room" - Learning to navigate dashboards -
11
Data analysis
Data analysis is important in a company to understand problems confronting an organisation, and to examine data in meaningful ways
-
12
Market Research
Market research can identify how consumers and potential clients view your business. It answers the why customers do what they do
-
13
Statistics
Statistics for business allows managers to analyze past performance, predict future outcomes and respond to changes in consumer demand.
-
14
Econometrics
Econometrics is the integration of statistics and economic events to provide numerical values to the parameters of economic relationships.
-
15
Descriptive Analytics Quiz
Test your knowledge after the lectures.
-
16
Predictive Models
Predictive Analytics offers an unprecedented opportunity to identify future trends and allows businesses to act upon them
-
17
Data Mining
Data mining is used to discover patterns and relationships in large amounts of data in order to help make facilitate analysis and decision making
-
18
Text Analytics
The purpose of Text Analytics is to create structured data out of free text content (unstructured)
-
19
Predictive Analytics Quiz
-
20
Computer vision
Ever wondered how autonomous vehicles work? The base of the magic is computer vision algorithms.
-
21
Operations research
There are operational problems that are common to many businesses. Providing with solutions based on that is the role of Operations Research
-
22
Signal processing
Digital Signal Processing has many daily yet unknown applications.
-
23
Image processing
Image processing is efficiently used in computer vision, medical imaging, meteorology, astronomy and other related fields.
-
24
Natural language processing
Natural language processing helps computers communicate with humans. For example, NLP makes it possible for machines to read a text, hear speech, understand it, and conclude which parts are important.
-
25
Metaheuristics
Some problems are too complex to solve, even using lots of data. An informed decision could work faster than a very accurate but slow one. This is the field of Metaheuristics.
-
26
Prescriptive Analytics - Quiz
-
27
Data Architecture
Data architecture is a fundamental part to align business goals with the data strategy.
-
28
Data Quality
Data quality drives better decision-making across a company. The more high-quality data you have, the more faith you can have in your decisions.
-
29
Master Data
Master data is the core data that is essential to operate a business
-
30
Data Privacy
Data Privacy enables us to create limits and protect ourselves from unwarranted intrusion in our lives, it allows us to decide how we want to interact with the society around us
-
31
Data Management Quiz
-
32
Data-Analytics Life cycle
The Data Analytics Life cycle defines stages, analytics methods and best practices. From data generation to data-driven decisions and actions.
-
33
Data Creation - How data is generated
By the end of this year 2020, every human on the planet will be creating 1.7 megabytes of information each second. In this lesson, we cover how data is generated.
-
34
Data Creation - What is a source system?
Source systems or systems of record are those powering the applications of a company.
In this lecture, you will discover how they work.
-
35
Data Creation - How is data extracted from Source Systems?
-
36
Data Creation - Data Replication
-
37
Data Storage - What is a Data Warehouse?
With the amount of data that is generated every day by a business, a place to store it and access it for reporting and intelligence becomes essential. This lecture is about Data Warehouses.
-
38
Data Storage - Different DWH technologies
A few years ago building a data warehouse was a long and costly exercise. Today you can build one in hours.
-
39
Data Storage - The concept of ETL/ELT
Extracting data from source systems and transforming it so that it can be analyzed is the role of ELT
-
40
Data Storage - Databases & Data modelling
Databases are the epicentre of business analytics. Connecting them to improve data coverage is called Data Modelling.
-
41
Data Use- SQL Language
SQL is used to communicate with a database. Analysts can update or retrieve data from a database.
-
42
Data Use- Python
Python is a flexible programming language. In this chapter, we cover how is it used for data analytics.
-
43
Data Use- R
With so much data to analyze the scientific community put together R, a programming language specifically designed to do analytics
-
44
Data Reporting - Data Visualization
By using visual components like charts, diagrams, and maps, data visualization tools provide an easy way to see and understand trends, outliers, and patterns in data.
-
45
Data Reporting - Ad-Hoc Analysis
An ad-hoc analysis is a business report or data analysis created when they need it, to solve a specific business problem.
-
46
Data Reporting - Executive Reporting
Executive reporting is a primary monitoring tool for a company's performance, tailored to the needs of executives.
-
47
Data-Analytics Life Cycle Quiz
What have you learn today?
