Explore data analysis and visualization in Excel, the cloud benefits of Power BI, and Power Pivot, pivot tables, and tools previously known as Power Query.
Microsoft Excel is one of the most widely used solutions for analyzing and visualizing data. Beginning with Excel 2010, new tools were introduced to enable the analysis of more data, resulting in less time spent creating and maintaining the solutions and enabling a better understanding of what the data means. This better understanding is facilitated by improved visualizations and more sophisticated business logics.
Do you want to take your advanced Excel skills to the next level? Are you exploring new ways to get and transform your data and create visualization?
Check out this practical new course, taught in short, lecture-based videos, complete with demos, quizzes, and hands-on labs, and skill up on many of the built-in business intelligence (BI) tools and features in Excel. Learn how to present the most relevant data with dynamic reports and presentations, as expert Dany Hoter walks you through all the important details.
In this course, get an introduction to the latest versions of these new tools in Excel 2016. See how to import data from different sources, create mashups between data sources, and prepare the data for analysis. After preparing the data, learn about how business calculations—from simple to more advanced—can be expressed using the DAX calculation engine. And see how these different technologies work together inside Excel. Learn how the data can be visualized and shared to the Power BI cloud service, after which it can be used in dashboards, queried using plain English sentences, and consumed on mobile devices.
What you'll learn:
- How to gather and transform data from multiple sources.
- How to discover and combine data in data mash ups
In business, data and algorithms create economic value when they reduce uncertainty about financially important outcomes. This course teaches the concepts and mathematical methods behind the most powerful and universal metrics used by Data Scientists to evaluate the uncertainty-reduction – or information gain - predictive models provide. We focus on the two most common types of predictive model - binary classification and linear regression - and you will learn metrics to quantify for yourself the exact reduction in uncertainty each can offer. These metrics are applicable to any form of model that uses new information to improve predictions cast in the form of a known probability distribution – the standard way of representing forecasts in data science.
The simple spreadsheet is one of the most powerful data analysis tools that exists, and it’s available to almost anyone. Major corporations and small businesses alike use spreadsheet models to determine where key measures of their success are now, and where they are likely to be in the future. But in order to get the most out of a spreadsheet, you have know how to use it. This course is designed to give you an introduction to basic spreadsheet tools and formulas so that you can begin harness the power of spreadsheets to map the data you have now and to predict the data you may have in the future.
One of the skills that characterizes great business data analysts is the ability to communicate practical implications of quantitative analyses to any kind of audience member. Even the most sophisticated statistical analyses are not useful to a business if they do not lead to actionable advice, or if the answers to those business questions are not conveyed in a way that non-technical people can understand. In this course you will learn how to become a master at communicating business-relevant implications of data analyses.
This course provides an analytical framework to help you evaluate key problems in a structured fashion and will equip you with tools to better manage the uncertainties that pervade and complicate business processes. Specifically, you will be introduced to statistics and how to summarize data and learn concepts of frequency, normal distribution, statistical studies, sampling, and confidence intervals.
The use of Excel is widespread in the industry. It is a very powerful data analysis tool and almost all big and small businesses use Excel in their day to day functioning. This course is designed to give you a working knowledge of Excel with the aim of getting to use it for more advance topics in Business Statistics.
Cuando finalices este curso habrás logrado un gran número de habilidades como introducir información, ordenarla, manipularla, realizar cálculos de diversa índole (matemáticos, trigonométricos, estadísticos, financieros, ingenieriles, probabilísticos), extraer conclusiones, trabajar con fechas y horas, construir gráficos, imprimir reportes y muchas más.
This course explores Excel as a tool for solving business problems. In this course you will learn the basic functions of excel through guided demonstration. Each week you will build on your excel skills and be provided an opportunity to practice what you’ve learned. Finally, you will have a chance to put your knowledge to work in a final project.
Why do the prices of some companies’ stocks seem to move up and down together while others move separately? What does portfolio “diversification” really mean and how important is it? What should the price of a stock be? How can we discover and exploit the relationships between equity prices automatically?