Use Excel to Make The Most of Your Data
Using Microsoft Excel, participants will learn the various powerful features of spreadsheets before using them in combination with statistical techniques to explore and discover relationships present in their data. This module will enable professionals looking to unlock latent value in their data and make the most of a powerful, familiar and intuitive software package.
- Use PivotTables and Functions effectively to summarise and augment Data in Microsoft Excel
- Visualize Data & create dashboards for reporting with Microsoft Excel
- Assess Data distributions and statistical relationships with Microsoft Excel
Who should attend:
Enterprise Data Practitioner (EDP)
Excel Analytics is one of the modules under our Enterprise Data Practitioner (EDP) programme. EDP is a nine-day training program that super-charges Business Intelligence analysts with new skills to analyse and communicate insights effectively.
Details of Subject
- Spreadsheet Fundamentals – All students start with basics like Navigation, The Tool Bar, and Comparison Operators. References and Data types prepare students use Excel like a pro.
- Predefined Functions – Functions are a powerful tool to simplify operations in Excel. This section will introduce time-saving functions such as VLOOKUP, INDEX MATCH, COUNTIF.
- Normalisation – Many of us work with Data, but good analysis begins with an organized dataset. Participants learn how to organize spreadsheets and lay the foundation for easier Data analysis.
- Pivot Tables – Pivot Tables are an important function for aggregating large amounts of data at once. We use Pivot Tables to quickly understand large datasets but also as a pre-cursor to Data Visualisation techniques in Excel.
- Data Visualization in Excel – We can use Visualization techniques to quickly understand large Data at a glance. Learn how to create and use sparklines, boxplots and line graphs for analysis towards decision- making.
- Dashboarding – Dashboards are a versatile tool frequently used in the realm of Business Intelligence. Participants create strategic dashboards for decision-makers to track KPI’s at a glance.
- Data Profiling – The first task for many Data analysts when approaching a new dataset is to perform data profiling. Understanding where the center of the Data lies (mean, median, mode) and how spread out the Data is (quartiles, std. dev., variance) provides insights into the kind of analytical techniques that are effective for that particular dataset. This saves time, energy, and resources.
- Categorical Explanatory and Response Variables – Moving beyond single variable students move on to Cross Tabulations and Conditional Percentages.
- Categorical Explanatory and Quantitative Response Variables – This chapter examines distributions of different subgroups. For example, which products are performing better in the market? How are the sales of each product affected by the customer quality rating? We will use simple statistical techniques to answer these questions.
- Quantitative Explanatory and Quantitative Response Variables – Examine linear relationships through the Pearson Correlation Coefficient via a combination of scatterplots and Excel formulae. Correlation is not causation but can often hint at it providing a starting point for further investigation.
EDP CADS Certified Excel Analytics
Excel is everywhere and often used for quick descriptive and diagnostic analyses. This certification test covers the following topics: Pivot Tables, Dashboards, Analytical Functions, Distributions, and Statistical Relationships. If you know the ins and outs of using Excel for analytics, stand out from the crowd with a certification that will attract the right attention.
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