BI in the Telecomm Industry

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Vinod Gupta School of Management, IIT Kharagpur

Business Intelligence in the

Telecommunications sector

Submitted by:

Amey Kolhatkar (09BM8008)

Sushant Kumar (09BM8052)

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Table of Contents

Introduction .............................................................................................................................. 3

What is Business Intelligence? ............................................................................................... 3

The Telecommunications Industry in India ........................................................................... 4

Need for BI in the Telecomm industry................................................................................... 6

BI and Data warehousing implementation at some major Telecomm companies in India .... 6

Dimensional Modelling for the Telecomm Industry ............................................................. 8

The Sales and Marketing process ........................................................................................... 9

Customer billing process ...................................................................................................... 16

Call Traffic (Call Detail Records) ........................................................................................ 13

The Supply Chain Management process .............................................................................. 21

Major BI Reporting Tools ..................................................................................................... 24

SAP - Business Objects ........................................................................................................ 24

SAS....................................................................................................................................... 24

IBM- Cognos ........................................................................................................................ 25

Microsoft SQL Server .......................................................................................................... 25

Oracle-Hyperion ................................................................................................................... 26

References ............................................................................................................................... 27

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Introduction

What is Business Intelligence?

Business intelligence (BI) refers to the tools and techniques used in identifying, extracting

and analyzing business data. Business Intelligence provides historical, current and predictive

views of business operations and aids decision making for businesses.

As per Forrester’s definition:

"Business Intelligence is a set of methodologies, processes, architectures, and technologies

that transform raw data into meaningful and useful information used to enable more effective

strategic, tactical, and operational insights and decision-making."

Some popular features of BI technologies are reporting, online analytical processing,

analytics, data mining, business performance management, benchmarking, and predictive

analytics.

The main function of Business intelligence is to enable businesses to do better decision-

making. To enable such decision-making, a BI system focuses on certain critical factors such

as customers, competitors, business partners, economic environment and internal operations.

Thus, a BI system can be referred to as a Decision Support System.

Business Intelligence applications can be:

Mission-critical and integral to a business’ operations or occasional to meet some

special requirement

Enterprise-wide or local to one division, department, or project

Centrally initiated or driven by user demand

Some advantages gained by implementing Business Intelligence are:

Enhanced reaction and sensitivity of the organization toward the customers

Identification of customer demands

Capability to respond to market trends

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Improved optimality within operations

Effective use and saving of wealth

Intricate study assisting for future prospects

Optimum utilization of organizational resources

Often BI applications use data gathered from a Data Warehouse (DW) or a Data Mart.

Basically, a DW contains tonnes of historical data relating to a business. BI relies on Data

Warehousing, making cost effective storing and managing of warehouse data critical to any

BI - DW solution. Without an effective data warehouse, an organization cannot extract the

data required for analysis in time to facilitate quick decision making.

The Telecommunications Industry in India

The Indian telecommunications industry is one of the fastest growing in the world. The total

number of telephone subscribers in the country reached 806.13 million at the end of January

2011 from 787.28 million in Dec 2010, according to the data released by Telecom Regulatory

Authority of India (TRAI), making it one of the fastest growing telecomm industries in the

world. With this the overall tele-density (telephones per 100 people) has touched 67.67. The

wireless subscriber base has expanded to 771.18 million at the end of Jan 2011 from 752.19

million in December 2010, registering a growth of 2.52%

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The telecomm industry has witnessed good growth during the last few years on the back of

rollout of newer circles by operators, successful auction of the third-generation (3G) and

broadband wireless access (BWA) spectrum, network rollout in semi-rural and rural areas

and the increased focus on the booming value added services (VAS) market.

Key Players

With many new players coming entering the sector, the intensity of competition in the

industry has increased, especially over the last few years. The resulting competition has

almost started a price war amongst the telecomm companies. The market share of the telecom

companies reflects the fragmented nature of the industry, with as many as 15 players. As of

September 30, 2010, Bharti Airtel was the market leader with a market share of 20.8%,

followed by Reliance (17.1%), Vodafone (16.8 %), BSNL (11.4 %), Tata (11.5 %), Idea

(10.8 %), Aircel (6.8 %), with the remaining share being held by other smaller operators like

MTS, Uninor, etc, Loop, MTNL, etc.

Future Prospects

As per the industry’s projections in the five year plan, the total number of telecom subscribers

is projected to grow from the present 780 million to 1,200 million during the five year period.

About 25% would be 3G and 4G subscribers, which would demand ramping up the

infrastructure significantly. The total investment in the pan-India broadband rollout is

expected to be USD 16.79 billion, while another USD 9 billion will be invested in

strengthening the transmission network.

Keeping in mind the growth and competition in this sector, and the high number of

subscribers, tons of data is generated daily, and companies need to be in a position to analyze

this data and use it for better decision making. Thus, BI plays a very critical role in the

Telecommunications industry.

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Need for BI in the Telecommunications industry

• Customer Profitability: It is imperative that the Telecomm companies acquire new,

profitable customers as well as increase the profitability of existing ones. BI solutions

can help a company identify the most profitable customers and their usage patterns.

• Cross selling: This can be a major source of selling for a telecom company. For

effective cross-selling, existing data can be leveraged using business intelligence

solutions to quickly zero in on new products that may be required by existing

customers.

• Customer Attrition: Acquiring new customers is much more costly than retaining

existing ones. Customer attrition analysis is an essential step in customer retention,

which can be achieved using BI.

• Campaign Analysis: Campaign analysis is used to analyze the effectiveness of a

marketing or promotion campaign. The effects of a particular campaign on sales of

the promoted product can be tracked using business intelligence solutions

• Forecasting: To plan their networks, telecommunications service providers perform

forecasting that helps operators to make key investment decisions

• Budgeting: Data warehousing facilitates analysis of budgeted versus actual

expenditure for various cost heads like promotion campaigns, product development,

infrastructure maintenance, investments, commissions, etc.

Role of BI at some major Telecomm companies in India

Vodafone were able to describe various benefits since implementing their BI

solutions:

o Automated import of measurement data from a wide variety of sources, allowing

the automatic creation of up-to-the-minute reports.

o Constant access to the reports from anywhere and at any time via the intranet or

Internet using a Web browser.

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o Standard presentation media; standard layout following corporate identity

guidelines.

o Dynamic selection of the level of detail in the reports.

o Dynamic creation of trend reports.

Reliance Communications’ performance improvement after BI and Warehousing

solutions implementation:

o Earlier, data loading took almost 2 - 3 hours daily.

o The implementation partner Greenplum Solution selected the S1004 model of the

Sun Data Warehouse Appliance for implementation.

o The time required to turn around a request for detailed call records shrank by over

80%, from multiple days to a few hours.

o Reduced the average time to load a day’s worth of data by over 90%, from 2 hours

to under 10 minutes.

BI and Data Warehousing at Bharti Airtel:

o The company started using BI tools from 1997-98

o The company mainly wanted to:

Identify the usage patterns at an individual level

Offer each customer customized plans based on his/her usage

o A key insight that Airtel obtained was that critical business and marketing

decisions were being based on daily revenues that were around 15% – 16% less

than the actual amount

o Hence, Airtel decided leverage its data management expertise in the Value Added

Services (VAS) based on consumer usage patterns.

o The decision-making process at Airtel has effectively moved from an observation

to a prediction model

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Dimensional Modelling for the

Telecomm Industry

The following four processes are identified which are the key ones that require the design of

fact and dimension tables. Covering these processes by large caters to the reporting

requirements of the telecommunication industry: The processes are:

1. Sales and Marketing

2. Customer Billing

3. Call Detail Records or Call Traffic

4. Supply chain management

The following dimensions are identified along which the processes will be built:

1. Time – This dimension represents the time variable along which the historic data can

be visualized. Its attributes is decided by the required granularity of the process. The

attribute may be any one among the Day of week, Type of day, Fiscal week, Fiscal

month, Fiscal quarter, Fiscal year, Holiday etc.

2. Customer – This dimension captures the data about the customers. The related data

may be the name of Customer, Customer id, locality of the customer, State of the

customer and the country he resides it.

3. Product – This dimension describes the various products the telecommunication

company offers. The products may be Call, SMSs, MMSs, GPRS etc. This dimension

has an id associated with each product known as the product id and the corresponding

description of the product.

4. Promotion – This dimension is mostly used in sales and marketing. This dimension

describes the various promotions used for selling the connections by the company. Its

attributes contains the name of the promotion, its cost and the locality in which it is

being promoted.

5. Sales Executive – This dimension captures the details of the sales representatives of

the company. The sales rep has a unique Id along with other details such as their

name, sex, age locality and the state on which they are employed.

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6. Location – Location is a dimension which captures the district, state and the country

of the operation of the company.

7. Retailer – This dimension is very useful in analysing the Supply chain of the

company. How the various retailers manage the recharge coupons and other vouchers

of the company. The attributes contains the name of the retailer its locality and state

along with the unique identifier called Retailer_id.

8. Service Line - The dimension service line signifies the connecting and transmitting

tower which has a unique Id and an area code for a particular locality and state. This

dimension is handy in analysing the call traffic and call details records.

The Fact and Dimensions for the various processes are represented in the following Bus

Matrix.

The Sales and Marketing process

This process is one of the most important ones in a Telecomm company. Due to increasing

nature of competition, a telecomm company must be able to identify the factors which

contribute the most to its revenues. By means of a BI system, one can easily identify things

like which area has the maximum number of customers, which time of the year witnesses the

maximum revenues, or which product generates maximum revenue, so that the telecomm

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company can focus accordingly. Also, one can analyze which marketing or promotional

campaign has given the best results.

Design Considerations:

The Time dimension helps us do an analysis for any period in an year, for example, sales per

week, per Fiscal quarter, etc, with the lowest level of granularity being a single day.

The Customer dimension maintains details of all the customers of the company, along with

other details such as date of joining of service, area or locality, state, etc.

The Promotion dimension is useful in maintaining details of all promotional campaigns

which have been undertaken by the company, alongwith details like Promotion cost,

promotion start and end date, promotion location, etc.

Similarly, there are other dimensions to store the details of various sales representatives,

products etc.

The Sales and Marketing fact and dimension tables are represented below:

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Analysis:

The above dimensional model is used to store data related to Sales and marketing activities

and can be very useful to analyse sales data and take important decisions. As mentioned

earlier, the things which could be analysed are Sales by region, sales by various time periods,

effectiveness of various promotional campaigns, popularity of various services/products,

performance of various Sales executives, etc. A sample record can be as shown below:

Time_ID 20110412120000

Product_ID CALL

Customer_ID ABC1234

Location_ID KGP

Promotion_ID NIGHT02

SalesExec_ID ASDF1111

Revenue 18

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Some of the reports which could be generated are:

Report 1:

Which product generated the maximum revenue in the year 2005 in Mumbai?

Time Location Product Revenue

2005 Mumbai GPRS 12600

2005 Mumbai SMS 5600

Result: On querying the warehouse, we deduce that the GPRS service was the highest

revenue grosser in the year 2005 in Mumbai circle.

Report 2:

Which year showcased the highest no. of newly added customers?

Year No. of Customers

2002 114500

2003 116000

Result: We find out that the year 2003 witnessed the highest addition of new customers for

the telecomm provider.

Some other queries which can be answered:

• Which promotions has been the most popular in a region?

• Which telecomm circle earns the maximum revenue for the company?

• Comparative analysis of the performance of sales executives based on factors such as

gender, age group, region.

The above queries shown are just a sample. The above dimensional model can similarly be

used to perform many other analyses, which can be extremely useful in decision-making.

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Call Traffic (Call Detail Records)

The call details record contains the data for all the calls. This process examines the call traffic

and up to the detail of a particular transmission tower in a locality from which the call has

been connected. This process has the following three dimensions:

1. Time

2. Customer

3. Service line

The granularity of the Time dimension is hour, so that the check can be made at an

hourly basis that which region has high call density on a particular hour of the day. Similarly

other attributes of the Time dimensions like ‘day of week’,’ week’ etc helps the decision

maker to watch out for the call density at various point of time in a week/ month.

The customer has his attributes as his name, id, locality and state. The service line

dimension has an area code to identify the area, along with the city and state.

The fact table contains the attributes required for measuring the density of the calls.

The call start time and call end time relates to the no of minutes a customer has been

connected to a call. All the calls are identified with the unique call Id. The access id is the id

for a particular connecting and transmitting tower. Data downloaded is the amount of data

transmitted through the tower to the customers end. Similarly for SMS and MMS, SMS ids

and MMS Ids are created which is unique for a particular transmission. The fact table and

dimension tables are as below:

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The sample call details record is shown:

Time_ID 201104142210

Customer_ID ABC1234

Service line_ID Kgp

Call_ID 222C

Duration(min) 33

Call start time 11:02 AM

call end time 11:35 AM

access ID kgp_12

connection start time 1:43 PM

Data downloaded 64MB

SMS_ID 111SMS

SMS time 4:00 PM

MMS_ID 434MMS

MMS time 3:00 PM

Analysis:

The Call records process is of great use to the decision makers by giving us a lot of

insights. Many questions can be addressed by analysing the data for the various calls made at

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a particular time of the day on a certain locality. It can be judged which area encountered

maximum traffic density or which week day experienced maximum calls.

We consider a hypothetical situation where only two customers made calls between

11 am and 12 pm on a certain day in two different regions namely, Kharagpur and Kolkata.

Their call details records are shown:

Time_ID 201104142310 201104142311

Customer_ID ABC1234 ABC1235

Service line_ID Kgp kol

Call_ID 222C 227C

Duration(min) 33 21

Call start time 11:02 AM 11:34

call end time 11:35 AM 11:55

access ID kgp_12 kol_12

connection start time 1:43 PM 2:43 PM

Data downloaded 64MB 66MB

SMS_ID 111SMS 118SMS

SMS time 4:00 PM 5:00 PM

MMS_ID 434MMS 474MMS

MMS time 3:00 PM 4:00 PM

The records of calls, SMSs and MMSs can be used to create valuable reports by

conducting operations like joins etc so as to get the result as required. For example if the

company requires to know the area or day having maximum traffic, or on which day

maximum SMSs were sent, the following reports may be generated to get an insight for

answering these queries.

Report 1:

Time_ID 201104142310 201104142312 201104142320 201104142330

Customer_ID ABC1234 ABC1235 ABC1236 ABC1237

Service line_ID Kgp kol Bankura Bishnupur

Call_ID 222C 227C 221C 232C

Duration(min) 33 21 11 31

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Call start time 11:02 AM 11:34 11:27 11:12

call end time 11:35 AM 11:55 11:38 11:43

Decision taken: In the region Kharagpur there was maximum call traffic during the 1hr

period from 11:00 am till 12:00 pm.

Report 2:

Day Sunday Monday Tues Saturday

Customer_ID ABC1234 ABC1235 ABC1236 ABC1237

Service line_ID Kgp Kgp Kgp Kgp

Call_ID 222C 227C 221C 232C

Duration(min) 33 21 11 31

Call start time 11:02 AM 11:34 11:27 11:12

call end time 11:35 AM 11:55 11:38 11:43

Decision taken: In the region Kharagpur there was maximum call traffic on Sunday of a

particular week.

Report 3:

Date 1st jan 14th feb 26th jan 15th aug

Service line_ID Kgp Kgp Kgp Kgp

No of SMSs 643 3321 234 312

Decision taken: In Kharagpur region, maximum SMSs were sent on 14th

February in the year

2010.

Customer billing process

This process is mainly required to keep the track of the call charges applicable to a particular

customer and provide a monthly bill for the customer against his usage. Each month, the

operational billing system generates a bill for each phone number. Since the wireless

company has millions of service lines, this represents a significant amount of data. However,

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a customer can have multiple connections or numbers, which appear as separate line items on

the same bill; each service line has its own set of billing metrics, such as the number of

minutes used and monthly service charge. There is a single rate plan associated with each

service line on a given bill; this plan can change as customers’ usage habits evolve. Finally, a

sales representative (and his or her respective sales organization and channel) is associated

with each service line in order to evaluate the ongoing billing revenue stream generated by

each rep and channel partner.


The Dimension table are built to the lowest level of granularity possible. Here in the

billing process, the required granularity of the time frame is one month because a bill comes

to the customer once every month. Therefore the grain is one month. However for making

possible decisions the Time dimension takes into account the quarterly data and the annual

data.

The Customer dimension has the data of customers like his unique ID, his name,

locality, state and the date he has taken a connection and the date he has left any previous/

existing connections. These dates are necessary for generating the bills as the number of

days/ months can be computed from these data for every customer.

The Sales executive dimension captures the data for all the sales executives, their

name, sex, age etc. This dimension is useful in carrying out the decisions related to the

problems associated in payment by a customer and the corresponding sales rep handing the

various cases of payment difficulty as in modes of payment or lagging the payment date.

The granularity of the Fact table represents the rates for various products offered by the

operator. The following products and charges are taken into consideration:

1. Calls charges

2. Roaming call charges

3. Long distance call charges

4. SMSs charges

5. MMS charges

6. GPRS charges

7. Late charges

8. Monthly service charges

9. Taxes

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The billing fact and dimension table are represented below.

A sample Bill is shown below:

Customer name Sushant Kumar

Customer ID ABCD1234

Locality Kharagpur

State West Bengal

Country India

Bill Date May-June

Date of Joining 23rd may'11

Date of leaving NA

Sales executive ID ABCD4321

No of call 34

Call charges 34

No of SMSes 5

SMSs charges 5

No of MMSs 6

MMSs charges 6

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No of roaming minutes 8

Roaming charges 16

Long distance minutes 23

Long distance charges 46

GPRS data downloaded 34MB

GPRS charges 34

Taxes 12

Service charges 12

Late charges 50

Due amount 241

Due amount with late

charges 291

Due date Jun-30

Analysis:

The billing process is of great use to the decision makers. Apart from bill generation,

this process gives us a lot of insights. Many questions can be addressed by analysing the data

for the various bills generated for the customer base with constant parameter such as time or

place. In a particular year it can be judged how many customers have delayed the bill

payment and how much revenue is generated by the late charges. Moreover, it can also be

seen which region of the country is making maximum no of calls and how/ which customers

are of greatest value to the company.

Consider a hypothetical situation where only two customers are in a particular area,

‘Kharagpur’. Their bills details are as shown below.

Customer name Sushant Kumar Amey Kolhatkar

Customer ID ABCD1234 ABCD1235

Locality Kharagpur Kharagpur

State West Bengal West Bengal

Country India India

Bill Date May-June May-June

Date of Joining 23rd may'11 24th may'11

Date of leaving NA NA

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Sales executive ID ABCD4321 ABCD4322

No of call 34 38

Call charges 34 38

No pf SMSs 5 5

SMSs charges 5 5

No of MMSs 6 6

MMSs charges 6 6

No of roaming minutes 8 8

Roaming charges 16 16

Long distance minutes 23 23

Long distance charges 46 46

GPRS data downloaded 34MB 98MB

GPRS charges 34 98

Taxes 12 12

Service charges 12 12

Late charges 50 50

Due amount 241 313

Due amount with late

charges 291 363

Due date Jun-30 Jun-30

The bills can be used to create valuable reports by conducting operations like joins etc

so as to get the result as required. For example if the company requires to know the most

valuable customer in the Kharagpur region, the following reports may be generated.

Report 1:





Due amount 241 313

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Decision taken: In the region Kharagpur the customer named ‘Amey Kolhatkar’ is of great

value to the company because revenue from him is the greatest in the region.

Report 2:





Late charges 0 50

Due amount 241 313

Due amount with late charges 241 363

Due date Jun-30 Jun-30

Decision taken: In the region Kharagpur the only one customer has delayed payments.

Report 3:

Locality Kharagpur Kolkata Bankura Bishnupur

State West Bengal West Bengal West Bengal West Bengal

Total Call usage (min) 354 121 322 111

Decision taken: In the region Kharagpur the total call usage is highest as compared to any

other region in the state.

The Supply Chain Management process

The Supply Chain Management (SCM) process mainly tracks the distribution of the

telecomm company’s various products – SIM cards, recharge vouchers of various

denominations, special recharge vouchers, internet data cards, etc. This process mainly helps

the companies track the performance of various retailers and the sale or demand of products

by retailer or by locality. This enables the company to manage the supply-demand situation

better and helps it forecast future demand of products in various areas.


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The Time dimension has the granularity of 1 day. Subsequently, data for any particular time

period can be obtained using the time dimension.

The Retailer dimension has details about the Retailer Id, Name, Locality of operation, etc.

The Product dimension has the Product ID, Description and the Category (sub-product). For

example, the product Id is Recharge Coupons (RC), and the sub products are the coupons of

various denominations such as RC10, RC30, RC100, etc.

The dimensional model for this process can be designed as follows:

Analysis:

Many questions regarding the Supply chain management of the company can be answered

using the dimensional model for this process.

Report 1:

• Which product has the highest demand with Retailers in Kharagpur location?

Location Product Category Quantity sold

Kharagpur Recharge Coupons

(RC)

RC30 1500

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Kharagpur Special Recharge

Voucher (SRC)

3000FREESMS 800

Result: The above data shows us that Recharge Coupons of Rs. 30 denomination has been

the product in most demand in Kharagpur.

Report 2:

• Performance of Retailers by location in a particular period.

Location Retailer ID Quantity sold

Kharagpur IITMAIN 600

Kharagpur RLYSTN 500

Result: The above analysis shows us that the Retailer outlet with ID IITMAIN has been the

one doing the maximum sale in terms of quantity in the Kharagpur area.

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Major BI Reporting Tools

The major players in the field of BI reporting are:

SAP - Business Objects

SAP business objects provide the following reporting and analysis tools which is intelligent

and robust enough to be used as per data requirements and platform used.

SAP Crystal Reports – This report connect to virtually any data source, design and format

interactive reports, and share them internally or externally.

SAP BusinessObjects Analysis – This Perform analysis of multi-dimensional data sets

using OLAP tool designed for financial and business analysts. The business objects for

Microsoft perform analysis for Microsoft office environment.

SAP BusinessObjects Web Intelligence – This feature of BO perform queries and analysis

across data sources online or offline.

SAP BusinessObjects Predictive Workbench – This mine the information sets and predicts

future trends.

SAS

SAS is the market leader in business intelligence software and services, and one of the largest

independent vendors in the market. It has the following types of reporting tools:

Business visualization – This provides business visualization for interactive data

exploration and visual queries. This tool make complex interrelationships visible in an

easy-to-understand picture.

Web and desktop reporting – This tool provides a Web-based, interactive reporting

interface for information consumers. Rich desktop-like experience through the utilization

of AJAX provides more drag-and-drop functionality, resizing of objects on the screen,

partial screen refresh and context-sensitive menus.

Query and analysis – This tool provides query capabilities for all levels of users across

multiple BI interfaces. It is a web-based, interactive interface for advanced users looking

for new views that define answers to questions by exploring and analyzing the OLAP

cubes.

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OLAP storage and OLAP data exploration interface- This unique tool provides a

powerful, industrial-strength multidimensional database designed to handle large volumes

of business intelligence data. It also supports multidimensional (MOLAP) and hybrid

(HOLAP) data stores.

IBM- Cognos

Cognos Business Intelligence expands traditional BI capabilities with planning, scenario

modeling, collaboration, real-time monitoring and predictive analytics. It provides the

following reporting and analysis tools:

Query and Reporting - Cognos query and reporting capabilities ensure users are equipped

with the information from which they need to make fact-based decisions in a system

that’s simpler, faster and easier to manage. Its analysis capabilities allow all users to

explore information easily and intuitively to drive better, smarter business decisions.

Dashboarding - Cognos dashboard capabilities allow any user to access, interact and

personalize content in a way that supports the unique way they make decisions

Scorecarding- Cognos scorecarding capabilities enable organizations to capture

corporate strategy and communicate that strategy at the operational level.

Real-time Monitoring- Cognos features real-time monitoring capabilities for consumers

of actionable business intelligence. It provides an organization’s frontline employees with

a rich view of operational KPIs and measures to support up-to the-moment decision

making.

Microsoft SQL Server

Microsoft Business Intelligence helps to make important decision making by the reporting

tools capable of performing complex tasks:

Aggregate seemingly disparate metrics into a single overall performance scorecard.

With Managed self-service Business Intelligence, it empowers users to create their own

ad-hoc reports using familiar, easy-to-use tools they already know. It Identify patterns and

exceptions with data trending.

Understand performance issues such as capacity spikes or downtime with greater event

detail.

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Rely on a robust security model that provides data security starting at web sites and

dashboards, all the way down to cell-level detail.

Oracle-Hyperion

Oracle BI provides following benefits through a comprehensive list of reporting and

analytics tools:

Comprehensive BI functionality built on a unified infrastructure— This tool reduces cost

and increase productivity with a common infrastructure for producing and delivering

enterprise reports, scorecards, dashboards, ad hoc analysis, and OLAP analysis.

Unified business model— This ensures that all metrics, calculations and definitions are

uniformly consistent to provide better alignment and visibility across the organization

Scalability, reliability and performance— This optimizes the performance while

simplifying systems configuration and lifecycle management. An integrated systems

management console provides superior scalability, high availability, and security benefits,

while making upgrades and systems management effortless.

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References

Ralph Kimball, Margy Ross, The Datawarehouse toolkit, 2nd edition -

The complete guide to Dimentional modeling

Data Warehousing for the Telecom Industry

http://www.information-management.com/issues/19981201/260-1.html

http://downloads.ingres.com/online/collaterals/bp/JaspersoftBITelecom-BP.pdf

Data Warehouse implementation at Reliance Communucations

http://www.authorstream.com/Presentation/amsmazin-632783-data-warehouse-

implementation/

http://www.greenplum.com/customers/reliance-communications/

Best Practice DataWarehousing and Analytics at Vodafone

http://www.sas.com/success/vodafone.html

http://www.teradata.com/library/pdf/Podcast_Stewart1107.pdf

Data Warehousing as a Strategic Tool at Bharti Airtel Indian School of Business, Hyderabad - Case No. CS-08-001, Version 1.0, July 2,

2008

Business Intelligence

http://www.nivtindia.com/Resource/Business%20Intelligence.pdf

http://en.wikipedia.org/wiki/Business_intelligence

India Brand Equity Foundation (IBEF) - Telecomm Industry in India

http://www.ibef.org/industry/telecommunications.aspx

http://www.trai.gov.in

Major BI Reporting tools

http://www.sas.com/technologies/bi/

http://www.oracle.com/us/solutions/ent-performance-bi/enterprise-edition-

066546.html

http://www.microsoft.com/sqlserver/en/us/solutions-technologies/business-

intelligence.aspx

http://www-01.ibm.com/software/data/businessintelligence/

http://www.sap.com/solutions/sapbusinessobjects/large/business-

intelligence/index.epx

BI in the Telecomm Industry

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