Presented By:

Kapil MahajanSameeksha Sahai

& Raphel Shervon

NEXT GENERATION - ENTERPRISE BI ANALYTICS

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KONDA KAVUM FOR DESSERT..?

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Data Model Presentation Decision Forecasting

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Data Model Presentation Decision Forecasting

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Data Model Presentation Decision Forecasting

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Data Model Presentation Decision Forecasting

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Data Model Presentation Decision Forecasting

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Data Model Presentation Decision Forecasting

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EVOLUTION OF DATA

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 20200

5

10

15

20

25

30

35

40

45

Data (ZetaBytes)

Source: IDC

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EVOLUTION OF DATA MODELLING

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EVOLUTION OF DATA VISUALIZATION

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EVOLUTION OF DATA VISUALIZATION

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DELIVERY APPROACHES FOR

ENTERPRISE BI ANALYTICS Corporate BI

IT Managed - Self Service

Business Led

Utilization of reports and dashboards published by IT for business users to consume

A “managed” approach wherein reporting utilizes only predefined/governed data sources

Utilization of reports and dashboards published by IT for business users to consume

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DELIVERY APPROACHES FOR

ENTERPRISE BI ANALYTICS Category Approach Managed by Ownership Scope for

business usersGovernance

Business led Self Service BI

Bottom – Up Business All elements are supported by business

Data preparation, data modeling, report creation & execution

Business

IT Managed Self Service BI

Blended Approach

IT IT : Data+ semantic layer Business : Reports

Creation of reports and dashboards

IT: data + semantic layerBusiness: reports

Corporate BI Top – Down IT IT Execution of Reports

IT

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ALIGNING WITH AGILE MANIFESTO

Embrace change - Reporting requirements are dynamic, tools should be simple for end user to develop

Deliver working reports regularly – All three types of delivery models should be aligned so that new and meaningful insights are generated regularly

Strive for iterations – The process from source data to visualization should be iterative.

Test throughout the lifecycle – Testing becomes very critical when business does their own reporting. IT should pass testing practices to business and they should run through out the process from data to visualization

Getting the architecture correct by experimenting all suitable options through POC

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SCALING

AGILITY

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BANKING CASE STUDY

Self Service BI Example - demo

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4 4

4

3 5

5 4

3

5

4 4

4

3 4

35

3

4

3

3

5

4

IMPACT ON CLIENT: Client can reach to many subscribers by sending limited number of campaigns

SOCIAL NETWORKING ANALYTICSSocial networking analysis can be performed based-on degree of centrality

SNA using Degree of Centrality Step 1: Find out the number of direct ties to the other people in

the network for subscribers with high churn probability

Step 2: In order to spread retention campaign to as many subscribers, we will find out subscribers having higher degree of centrality. Assuming, if a subscriber with high degree of centrality is churned then probability of its peer group getting churn is high

Step 3: Send campaigns to the target subscribers (found in step 2)

Degree of Centrality

IT Managed Self Service BI Example - demo

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NEXT GENERATION- BI ANALYTICS

Corporate BI Example - demo

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DATA IS LIKE A BIKINI!What it reveal is suggestive, but what it conceals is vital.

"Analytics can reveal everything" Do It Yourself (DIY)

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