BI tools: Excel’s Pivot table Stefano Grazioli

Critical Thinking Last unit of the BI segment Easy meter

You do the talking Name, major Learning objectives Things you like about the class Things that can be improved Attitude towards the Tournament

Pivot tables In Excel

Welcome to ACME! You are a BI/finance consultant at ACME Inc., a company with a global presence. It is year-end and your boss, the CFO, wants to check the differences between budgeted costs and actual costs.

Your job Without Pivot tables

First, ask about the data model and the data dictionary…. Single table, on a remote RDBMS (SmallBankDB) Doable in Excel, but… Division = geography Category = group of items, e.g., commission, lease, utilities

WINIT What Is New In Technology?

Your job with Pivot tables demo

Pivot Tables … are data summarization tools. They aggregate data according to various dimensions (e.g., time, location, department, product….) Then they let you see your data in new ways. Slicing and dicing.

Homework Demo

The big picture for the homework Transactions / Operations Real time, individual, action Business intelligence & Analytics Historical, aggregate, decision Accounting Extract Clean Transform Load Query Report Analyze Visualize Pivot Table Acme Budget Table Europe HR Managers & Decision makers Recommended reading: TDWI Smart Companies Report 2003, available at www.tdwi.org Data warehousing includes two parts – getting data in, and getting data out. Getting data in is the hard part – it includes taking data from source systems, transforming the data, and loading it into an integrated data store. Getting data in is 80 % of time and resources, and 50% of unexpected costs. Getting data out is the fun part – it include the BI tools that casual and power users use to access the data warehouse data. When users use the data, they can deliver value to the organization. The data store in the middle can be an enterprise data warehouse, a data warehouse with dependent data marts, independent data marts, or a federated database environment. Typically, the independent data mart approach is least effective. The focus of today is on designing the data structures for a dependent or independent data mart that is tuned for on-line analytical processing (OLAP). BI consultants Data scientists = YOU

Pivot Architecture Remote DBMS “Smallbank DB” Dataset & Datatable “myDataset” “BudgetDataTbl” ListObject “BudgetDataLO” Pivot Cache “myPivotCache” Pivot Table “myPivotTable” User