This model can be applied wherever historical numerical data is available. One of the most widely used predictive analytics models, the forecast model deals in metric value prediction, estimating numeric value for new data based on learnings from historical data. Other use cases of this predictive modeling technique might include grouping loan applicants into “smart buckets” based on loan attributes, identifying areas in a city with a high volume of crime, and benchmarking SaaS customer data into groups to identify global patterns of use. Using the clustering model, they can quickly separate customers into similar groups based on common characteristics and devise strategies for each group at a larger scale. But is this the most efficient use of time? Probably not. If an ecommerce shoe company is looking to implement targeted marketing campaigns for their customers, they could go through the hundreds of thousands of records to create a tailored strategy for each individual. The clustering model sorts data into separate, nested smart groups based on similar attributes. The breadth of possibilities with the classification model-and the ease by which it can be retrained with new data-means it can be applied to many different industries.
Please note that Power Query, Power Pivot and Power BI Desktop are only available on the Windows platform, so Mac users will require Bootcamp running Windows or a Virtual machine with a Window O/S. In this course we focus on Excel Power Tools, join us for this exciting journey. To get the most out of this course we would recommend you do the previous courses or have experience with these topics. The previous courses: Excel Fundamentals for Data Analysis and Data Visualization in Excel, cover data preparation, cleaning, visualisation, and creating dashboards.
This is the third course in our Specialization on Data Analytics and Visualization.
We will finish off by venturing out of Excel and introducing Power BI, which also uses the Power Query and Power BI architecture but allows us to create stunning interactive reports and dashboards. We will see how Power Pivot revolutionises the actual analysis process by providing us with an analytical database inside the Excel workbook, capable of storing millions of rows, and a powerful modelling language called DAX which allows us to perform advanced analytics on our data.
In this course, we will learn how to use Power Query to automate the process of importing and preparing data for analysis.
Over the last few years, Microsoft have worked on transforming the end-to-end experience for analysts, and Excel has undergone a major upgrade with the inclusion of Power Query and Power Pivot. In this four-week course, we introduce Power Query, Power Pivot and Power BI, three power tools for transforming, analysing and presenting data.Įxcel's ease and flexibility have long made it a tool of choice for doing data analysis, but it does have some inherent limitations: for one, truly "big" data simply does not fit in a spreadsheet and for another, the process of importing and cleaning data can be a repetitive, time-consuming and error-prone. Welcome to Excel Power Tools for Data Analysis.