"Analysis does not set out to make pathological reactions impossible, but to give the patient's ego freedom to decide one way or another." - Sigmund Freud
To me statistics was an impenetrable forest of numbers. All organizations require high performers which give the organization much more than data analysing and algorithms. Study of analytics provides smarter business solutions as each and every employee is focussed on the right activities, making the right decisions, at the right time. It helps organize, explore, predict and optimise huge data in a structured manner to help solve problems.
SPSS is a Computer program used for survey authoring and deployment (IBM SPSS Data Collection), data mining (IBM SPSS Modeler), text analytics, statistical analysis, and collaboration & deployment (batch & automated scoring services)
SPSS basics were taught starting from reading the data, using data editor, data organization, running on analysis, data frequencies, descriptive cross tabulation was studied taking various examples. Reading spreadsheets is very important because that is how you analyse and interpret data. Cross tabs forms two-way and multiway tables and provides a variety of tests and measures of association for two-way tables.
Most of the techniques used for segmentation and profiling are exploratory. There is no write and wrong answer and the result are not open to interpretation. Different techniques include Factor Analysis , Hierarchical Clustering, K-Means Cluster, Non-Linear Principal Components Analysis (PRINCALS/CATPCA) . Factor Analysis - to find patterns within variables, Categories - use if data doesn’t fit assumptions for Factor Analysis , Cluster Analysis - to find patterns between individuals, Two-Step Cluster – To use with both categorical and continuous variables, Discriminant Analysis - to look for differences between groups, try to predict target variable, AnswerTree - combinations of data, to predict target. These techniques are inter-related, but don’t have to use all of them. Can use a combination of these techniques to segment the data
HARD FACTS ON BUSINESS ANALYSIS
Did you know that:
• 70% of all project failures are as a result of poor requirements.
• There is a 60% time and cost premium to be paid on projects with poor quality requirements.
• As the projects get more interdepartmental and complex, the failure rate rises.
• It costs 80 times as much to fix defects after delivery, than at the specification stage.
• 74 per cent of all companies have immature requirements practices.
• Large scale systems project fail with alarming regularity. A typical project over-ran its budget by 189% and over-ran its schedule by 222%.
• Average project has about 30% rework. This means that for every Kshs 1,000,000, Kshs 300,000 is spent redoing something that was thought to be complete.
• The average company with low requirements maturity wastes 34% of the organization’s IT development budget.
• 68% of companies simply did not use the necessary competency in requirements discovery at the start of their project to assure project success.
Source: IAG Business Analysis Benchmark, 2008
Group : Marketing Group 5
Author of the Article : Apoorva Bhalerao
Roll No : 13009
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