Business Analytics

Overview

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Nowadays data is essential in the business environment to be gain a global view of an organization's situation and to be able to make better decisions. Against this background, Big Data is a booming sector in multiple areas that opens up different job opportunities, such as the role of Data Analyst. This course is an introduction to data analytics from a business perspective, focusing on the relevance of basing strategic decision-making on the knowledge provided by data. You will discover the phases of the lifecycle of a data-based project, as well as the importance of ensuring its quality in organizations. You will learn the basics of descriptive and inferential statistics that every data analyst should know. Finally, you will learn some strategies to share information by getting the most out of data visualizations. Our overall goal will be to create an impact on organizations through the generation of more effective dashboards and the use of storytelling from data. Will you join us?

Syllabus

Introduction to Big Data

This module introduces the phenomenon of Big Data. And shows you the importance of data in today's society as well as the main trends in the business environment, focusing on the importance of making data-driven decisions.

Data Analysis

Throughout this module, we will discuss the role, responsibilities and skills needed to be a data analyst. We'll also take a short tour of the infrastructure, analytics, and applications used to capture and analyze data.

Data-Driven Projects

In this module, we will learn the phases of the cycle of a data-based project, focusing on those with more active involvement of the data analyst.

Data Quality

In this module, we will focus on the characteristics that quality data must meet. And we will learn the main causes and consequences of using low quality data, focusing on establishing good practices to improve its quality.

Introduction to Descriptive Statistics

In this module, we will learn about the basic concepts of descriptive statistics that every data analyst should know to perform their work efficiently.

Introduction to Inferential Statistics

In this module, we will focus on the normal distribution, its properties and main uses. We will also learn the concepts of population and sample, and parameter estimation (point and interval). We will also offer a definition of hypothesis testing, and we will discover other concepts of inferential statistics that will surely be very useful.

Creating Stories Through Data

In this module, we will learn about the importance of knowing how to transmit the information obtained from data clearly and concisely to attract the interest of our audience.