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DATA WAREHOUSE AND BI

Presented byAli Asad, Amaldas AS, Ankita Banerjee & Israa Tolson

ToProf. Monica Luxemburg

Alcohol consumption among students

A3I data analyst

Business Consulting Master

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AGENDA Company profile & Objective Problem statement & Business Case KPI description Star schema Excel prototype SAP BW & Data flows Qlikview Analysis Conclusion Recommendation Lessons learnt

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COMPANY PROFILE FOUNDED: 2012

INDUSTRY: IT/Data analytics

HEADQUARTERS: Stuttgart, Germany

BUSINESS PROCESS: Customer oriented

STRATEGY: Growth and innovation

CUSTOMERS: Open to all kinds of projects, clients ranging from Banking to Retail etc.

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OBJECTIVE Inspecting, cleansing, transforming, and modelling data with the

goal of discovering useful information, suggesting conclusions, and supporting decision-making.

Emphasizing the generation of actionable insights that lead to tangible improvements in constituent touch points across the organization.

Improve the member experience and deliver more value to customers.

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PROBLEM STATEMENT NGO approached us to analyze data to measure alcohol

consumption among students and the main factors that play a role in this case.

Statistical analysis of several attributes that could lead students to consume alcohol, behavioral elements for example.

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BUSINESS CASE

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KEY PERFORMANCE INDICATOR

Alcohol consumption (Weekend + Weekday consumption) First Term grades Second Term grades Final grade(Average of term 1 and 2)

• Dimensions : Time Student Subject

8KPI DESCRIPTIONFirst term grade

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• Second term grade

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• Final grade

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• Alcohol consumption Weekdays

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• Alcohol consumption Weekend

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• Average alcohol consumption

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STAR SCHEMA

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EXCEL PROTOTYPE: FACT TABLE

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With alcohol consumption of 1(lowest) pass percentage is 71.37%

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ALCOHOL CONSUMPTION WEEKDAYS

With alcohol consumption of 5(highest) there is a considerable drop in the pass percentage 38.89%

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ALCOHOL CONSUMPTION WEEKEND

With alcohol consumption 1 pass percentage is 65.56%

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ALCOHOL CONSUMPTION WEEKEND

With alcohol consumption of 5 there is a slight change in pass percentage ie 53.57% as it’s the weekend and generally doesn’t affect the grades much

20NAMING CONVENTIONDimensions Key Figures Data Sources

Student A05_STD_NSP_05Student Subject A05_SUB_NSP_05Student_ID A05CHSTDID Grade_1 A05KFGRD Time A05_TIM_NSP_05Age A05CHAGE Alcholo_cons_W A05KFACWD Fact Table A05_FT_NSP_05

Sex A05CHSEX Alchol_cons_weekend A05KFACWEFamily_status A05CHFAMS Avg_alc_cons A05KFAVGCPstatus A05CHPSTAT Average_grade A05KFAVGGstudytime A05CHSTUDT students A05KFSTDfailures A05CHFAIL pass/fail A05KFPORFactivities A05CHACTabsences A05CHABS

Subject Info PackagesSubject_id A05CHSID Student

A05_STD_NSP_05

Subject_name A05CHSNAM Subject A05_SUB_NSP_05

TimeA05_TIM_NSP_05

Time Fact Table A05_FT_NSP_05Term A05CHTermTerm_Desc A05CHTerm

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SAP BW• Datasources

• Infosource

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• Info Object • Info provider

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DATA FLOWS• Data flow for transaction data grades • Data flow for students dimension

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• Data flow for subjects • Data flow for term

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ANALYSIS OF DATA IN QLIKVIEW

• We would be looking into the following parameters for our analysis and will try to draw some meaningful conclusion from the same.

1. Grades vs weekday alcohol intake2. Grades vs weekend alcohol intake 3. Family size vs alcohol consumption4. Parents status vs alcohol consumption5. Study time vs alcohol consumption6. Student activities vs alcohol consumption7. Past failures vs alcohol consumption

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DATA IN QLIKVIEW• For our analysis we have taken

subject Portuguese Term 1 and Mathematics Term 1

27WEEKDAY AND WEEKEND ALCOHOL

CONSUMPTION TERM 2 SUBJECT MATHS

28MORE INSIGHT IN WEEKDAY ALCOHOL CONSUMPTION

Alcohol consumption of scale 1


29MORE INSIGHT IN WEEKEND ALCOHOL CONSUMPTION



30WEEKDAY AND WEEKEND ALCOHOL CONSUMPTION TERM 1 SUBJECT PORTUGUESE

31MORE INSIGHT IN WEEKDAY CONSUMPTION



32MORE INSIGHT IN WEEKEND CONSUMPTION



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FAMILY SIZE AND ALCOHOL CONSUMPTION

• Family size GT3 is family size greater than 3 LE3 is lesser than 3• For the report we find that alcohol consumption majorly takes place

among students whose family size is greater than 3.• Conclusion to be drawn is that loneliness or feeling left out (which

may happen if family size is less than 3) is not a reason for the student to consume alcohol.

sub: protugese term1

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PARENT STATUS AND ALCOHOL CONSUMPTION

• Parents status T stands together and A for separated.• Attention towards the scale of maximum alcohol consumption of 4

and 5 , interestingly we find that the parents status of students is separated.

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STUDY TIME AND RELATIONSHIP ALCOHOL CONSUMPTION

• Study time of 1 is the least with < 2 hours and 4 is highest with >10 hours.

• From the report we find that alcohol consumption from scale 1 to 5 is done majorly by students whose study time is the least i.e of 1 and 2 .

• The maximum alcohol consumption of 4 & 5 is only done by students with study time of 1 and 2

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EXTRA CURRICULAR ACTIVITIES VS ALCOHOL CONSUMPTION

• Marginal difference so drawing any conclusion from this attribute is not feasible.

37PAST FAILURES AND RELATIONSHIP WITH ALCOHOL CONSUMPTION

• Past failures have been measured on scale of 0-3 (0 lowest , 3 highest)• Concentrate on alcohol consumption 4 and 5 (highest) we find that

count of students is more in this regard with failures of 2 and 3 .

38CONCLUSIONAverage alcohol consumption data doesn’t help us to evaluate or draw

any suitable conclusion as the weekend alcohol consumption does not affect the grades of the student majorly.

The weekday alcohol consumption clearly illustrates that pass percentage of students with alcohol consumption 5 is 42.46% where as with least alcohol consumption of 1 is 83.37%.

The Family size of most of the students who consume alcohol is grater than 3.

The Parent status of the majority of students with high alcohol consumption is separated.

Study time of students with more alcohol consumption is lessThe student activities show marginal difference but still students with less

activity time consume more alcohol.Students with more past failures are prone to more alcohol consumption.

39RECOMMENDATIONS

• We have provided the NGO with our analysis and our recommendation would be that the parents and teachers should look into study time and activity time of the students and the parents should also look into their family atmosphere.

“Because building a better world starts with raising healthy , happy and empowered children.”

40LESSONS LEARNT• Data quality plays an important role for correct decision making.

Some roles with names of not assigned populated but for data quality we changed the tag to 0 to make more sense.

• Aggregated data is not always meaningful , segregation can be more useful in certain situations.

E.g.: Average alcohol consumption & weekday consumption.

• Multiple analysis possible with multidimensional start schema.

E.g.: Initial scope of project was to analyze alcohol consumption with grades but with multidimensional data model we could identity more attributes for analysis.

41PROJECT PLANProject phase Task Start date End date Progress

PreparationSetting topic and scope 18.10.2016 24.10.2016 100%

Business case 25.10.2016 07.11.2016 100%

Defining KPIs 25.10.2016 07.11.2017 100%

Modelling and Prototyping

Identifyting and collecting data sources 08.11.2016 14.11.2016 100%

Analysing the data sources 15.11.2016 21.11.2016 100%

Defining the star schema 22.11.2016 28.11.2016 100%

Creating excel prototype 29.11.2016 05.12.2016 100%

Data warehouse ImplementationCreating infocubes and dimension 06.12.2016 12.12.2016 100%

Uploading of data 13.12.2016 19.12.2016 100%

Creating connection with DWH 20.12.2016 25.12.2016 100%

BI Implementation Using QV extracter extracting the data query from SAP BW 5.01.2017 6.01.2017 100%

Reloading of query in Qlikview and generating reports 7.01.2017 10.01.2017 100%

Testing Testing for the project

Testingreports in Qlikview