Strategic Data Warehousing and Forecasting for Enhanced Marketing Decision-Making
This document outlines the operational aspects of a Data Warehouse (DWH) for marketing analysis, highlighting the importance of forecasting and user activities. It discusses response times, data accessibility, and the integration of internal and external data sources. The emphasis is on managing data ranging from small to large-scale, supporting strategic decision-making. Various forecasting methods are examined, including linear, exponential smoothing, and Holt-Winters techniques, to aid marketing managers in retrieving actionable insights from complex data.
Strategic Data Warehousing and Forecasting for Enhanced Marketing Decision-Making
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Presentation Transcript
Property Operational DWH Operations Analysis, forecasting, Useractivities etc. Sub. sec. to seconds Sec. to hours Response Time Read and write Primarily read only Access Current data (30-60 Historical data Nature of data days) (snapshots over time) (timeperiod) Internal Internal and external Data sources Small to large (<100 Large to very large (50 Database Size GB) GB to 2 TB) Production Strategic decisions Types ofDecision management Making DWH vs OLTP:
DM1 DWH ….. DM2 DMk DMn DWH vs. DATA MARTS
EXPRESS SERVER APPLICATION Multi-dimensional Data Base
MARKETING INFORMATION SYSTEM of BTC Marketing manager Queries MkIS Decision making information DWH
periods periods periods periods regions regions regions regions exchanges exchanges exchanges exchanges subscribers subscribers subscribers subscribers lines services changes services THE MAIN VARIABLES IN THE MkIS capacity changed lines usage revenue
Method Time Horizon Data Pattern Minimum number of observations Single Immediate, short Stationary 2 Exponentioal Smoothing Double Immediate, short Linear 3 Exponentioal Smoothing Tripple Immediate, short Non-linear 4 Exponentioal Smoothing Moving Average Immediate, short Stationary 3 Holt-Winters Short to medium Seasonal 2 seasons Linear Trend Medium, long Linear 3 Exponential trend Medium, long Non-linear 3 Percentage change Medium, long Stationary, linear 2 CHOOSING A FORECASTING METHOD
Windows Client Applications (Oracle Express Objects) Oracle Express Server Instance User id SNAPI Calls Cached data cubes Marketing data base Stored procedures USER ACCESS TO MARKETING DATA BASE
LIBRARY REPORTS LIBRARY MAIN LIBRARY USERS LIBRARY LOADREPORT LOAD REPORT SAVEREPORT 35 FREQUENTLY USED REPORTS
