A Data warehouse based analysis on CDR to depict market share of different mobile brands
01 Dec 2015-pp 1-6
TL;DR: A suitable Data warehouse schema is proposed which comprises of the required dimensions along with their concept hierarchies and the lattice of cuboids is constructed to carry out the OLAP processing from all possible business perspective.
Abstract: Each mobile device represents the digital footprint of the owner; at the same time mobile location data stored in telecom operators' databases in terms of Call Detail Record (CDR). It holds the precise identity of the mobile cell tower to which the owner is connected at any given time. Effectively mobile device count within a region for some time period can be calculated. Again, International Mobile Equipment Identity (IMEI) number is an unique identity to every mobile device, a part of which, known as Type Allocation Code (TAC) uniquely identifies the make and model of the mobile device which further identify the company or manufacturer of the mobile device. So combining them it is possible to analyze different business information about mobile penetration of companies in a defined region; hence the localized market share comparisons with other companies as well as among different models of same company. In order to model the problem and analyze huge CDR data, an analytical processing is carried out here using data warehouse. Here we propose a suitable Data warehouse schema which comprises of the required dimensions along with their concept hierarchies. The ETL processing which is done to form the data warehouse is described here. Finally the lattice of cuboids is constructed to carry out the OLAP processing from all possible business perspective.
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01 Jan 2011
TL;DR: In this article, a relationship between people's mobility and their social networks is presented based on an analysis of calling and mobility traces for one year of anonymized call detail records of over one million mobile phone users in Portugal.
Abstract: A relationship between people’s mobility and their social networks is presented based on an analysis of calling and mobility traces for one year of anonymized call detail records of over one million mobile phone users in Portugal. We find that about 80% of places visited are within just 20 km of their nearest (geographical) social ties’ locations. This figure rises to 90% at a ‘geo-social radius’ of 45 km. In terms of their travel scope, people are geographically closer to their weak ties than strong ties. Specifically, they are 15% more likely to be at some distance away from their weak ties than strong ties. The likelihood of being at some distance from social ties increases with the population density, and the rates of increase are higher for shorter geo-social radii. In addition, we find that area population density is indicative of geo-social radius where denser areas imply shorter radii. For example, in urban areas such as Lisbon and Porto, the geo-social radius is approximately 7 km and this increases to approximately 15 km for less densely populated areas such as Parades and Santa Maria da Feira.
139 citations
12 Jun 2019
TL;DR: A DW schema modelling approach is proposed which integrate in a unified manner temporal and spatial data in a general data warehousing framework to facilitate the understanding, querying and management of spatiotemporal data for on-line analytical processing (OLAP).
Abstract: In a cloud based data warehouse (DW), business users can access and query data from multiple sources and geographically distributed places. Business analysts and decision makers are counting on DWs especially for data analysis and reporting. Temporal and spatial data are two factors that affect seriously decision-making and marketing strategies and many applications require modelling and special treatment of these kinds of data since they cannot be treated efficiently within a conventional multidimensional database. One main application domain of spatiotemporal data warehousing is telecommunication industry, which is rapidly dominated by massive volume of data. In this paper, a DW schema modelling approach is proposed which integrate in a unified manner temporal and spatial data in a general data warehousing framework. Temporal and spatial data integration becomes more important as the volume and sharing of data grows. The aim of this research work is to facilitate the understanding, querying and management of spatiotemporal data for on-line analytical processing (OLAP). The proposed new spatiotemporal DW schema extends OLAP queries for supporting spatial and temporal queries. A case study is developed and implemented for the telecommunication industry.
16 citations
Cites methods from "A Data warehouse based analysis on ..."
...A DW schema is also proposed in [16] for analyzing CDR data in order to generate valuable information....
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18 Jul 2018
TL;DR: An integrated framework with all related but isolated web based sub systems of a blood management system is developed and a data warehouse (DW) is proposed as an integral part of the integrated framework to store historical blood donation data in a centralized database for analytical processing.
Abstract: Blood donation is an important issue throughout the world to save and manage lives. In order to make this process more effective an automated system could be built to monitor and organize blood donation camps. In this paper we developed an integrated framework with all related but isolated web based sub systems of a blood management system. We propose a data warehouse (DW) as an integral part of the integrated framework to store historical blood donation data in a centralized database for analytical processing. Proposed system would enable the authorities to take informed blood donation camping decision based on the analytical reports from the DW for some area for a particular time and citizen demography. Finally, we introduce a new measure of humanity (scoring system for good deeds) of citizens called Philanthropy Score (PS) and Philanthropy League (PL) derived from PS. In our proposed system after blood collection at donation camps, few health related details would be updated in the blood management system database and most importantly PS of the donor would be updated into the national citizens’ database. A well-advertised communication would allow the citizens to know about the PS points they can accrue for every possible good deed. Blood donation is merely a prototype use of the proposed PS.
11 citations
Cites background or methods from "A Data warehouse based analysis on ..."
...Similar kind of DW schema has been developed in telecom [8] and that has been consulted....
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...Firstly, we model a data warehouse [8] for blood donation camp management for making informed camping decision along with an integrated framework with all blood system related component modules....
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Journal Article•
TL;DR: This paper shall review a few existing DW schemas used to consolidate CDR and CRM data and propose a generic model DW schema with indentified facts and dimensions for the central DW.
Abstract: Mining operational telecom data has given many interesting insights about customer behavior, mobility, social interaction etc and has great business value. But to have truly unbiased analysis over a defined geographic region, we need to first consolidate all telecom data from many different operators present within the region and then analyze them. This necessitates an integration architecture that will allows to integrate, consolidate and store different type of operational telecom data such as call detail record (CDR), customer relationship management (CRM) data, network data etc into a central data warehouse (DW). Though almost all operator stores semantically same type of data but in a little different form and format. Again these operators are separate business entities so integrating data from their operational databases and data marts needs to be independent of each other and flexible in fetching data for extract, transform and loading processes. In this paper we shall review a few existing DW schemas used to consolidate CDR and CRM data and propose a generic model DW schema with indentified facts and dimensions for the central DW. Next we propose integration architecture to collect data and consolidate in the central DW from many different operational databases of different telecom operators. Web services (WS) has been proposed as a mode of communication between central DW and other operational databases. Keywords—Datawarehouse; Integration Architecture; Telecom CDR; DW Integration Using Webservices;
9 citations
01 Sep 2016
TL;DR: A mechanism is developed to store CDR data in a suitable Data Warehouse (DW) schema and analytically process these using OLAP tools to understand the prepaid customers usage, spending and propensity to marketing offers.
Abstract: Retaining an existing customer than acquiring a new one is less expensive in terms of marketing cost, bonus, and incentives offered etc. Telecommunication industry across the globe is stiff competitive environment where market is almost saturated and main focus of customer service becomes retaining existing customers and snatching others' customers to increase market share as well as profit. At the same time telecom industry facing the problem of churn or attrition more than anything especially for prepaid customers as the customers could switch the service providers easily. Telecom operators generate huge volume of call detail records every day for every call, SMS or internet access made by its customers. Telecom operators use these huge operational data for business processing to understand customer behavior. In this paper a mechanism is developed to store CDR data in a suitable Data Warehouse (DW) schema and analytically process these using OLAP tools to understand the prepaid customers usage, spending and propensity to marketing offers. Depending on the usage pattern proper segmentation of the customers has been done and they have been categorized for different types of targeted marketing offers and benefits to retain as well as acquire new customers.
9 citations
References
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Book•
01 Jan 1992
TL;DR: This Second Edition of Building the Data Warehouse is revised and expanded to include new techniques and applications of data warehouse technology and update existing topics to reflect the latest thinking.
Abstract: From the Publisher:
The data warehouse solves the problem of getting information out of legacy systems quickly and efficiently. If designed and built right, data warehouses can provide significant freedom of access to data, thereby delivering enormous benefits to any organization. In this unique handbook, W. H. Inmon, "the father of the data warehouse," provides detailed discussion and analysis of all major issues related to the design and construction of the data warehouse, including granularity of data, partitioning data, metadata, lack of creditability of decision support systems (DSS) data, the system of record, migration and more. This Second Edition of Building the Data Warehouse is revised and expanded to include new techniques and applications of data warehouse technology and update existing topics to reflect the latest thinking. It includes a useful review checklist to help evaluate the effectiveness of the design.
2,820 citations
TL;DR: Y the authors' company decides to build a data warehouse and you are designated the project manager, and you have specific questions that need specific answers, and building a data Warehouse is an extremely complex process.
Abstract: Y our company decides to build a data warehouse and you are designated the project manager. What are your first steps? You’ve read the books, attended the conferences, and perused the trade publications. Now you have to act. There are numerous vendors, all touting the wonders of their products, but you have specific questions that need specific answers, and building a data warehouse is an extremely complex process. Questions you have to weigh fall into the following general categories:
1,272 citations
"A Data warehouse based analysis on ..." refers background in this paper
...The classic definition of a Data warehouse (DW) by Inmon states that a DW is a subject-oriented, integrated, nonvolatile, and time-variant collection of data in support of management’s decisions [5]....
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TL;DR: The ‘Mobile Landscapes' project is presented: an application in the metropolitan area of Milan, Italy, based on the geographical mapping of cell phone usage at different times of the day, which enables a graphic representation of the intensity of urban activities and their evolution through space and time.
Abstract: The technology for determining the geographic location of cell phones and other handheld devices is becoming increasingly available. It is opening the way to a wide range of applications, collectively referred to as location-based services (LBS), that are primarily aimed at individual users. However, if deployed to retrieve aggregated data in cities, LBS could become a powerful tool for urban analysis. In this paper we aim to review and introduce the potential of this technology to the urban planning community. In addition, we present the ‘Mobile Landscapes' project: an application in the metropolitan area of Milan, Italy, based on the geographical mapping of cell phone usage at different times of the day. The results enable a graphic representation of the intensity of urban activities and their evolution through space and time. Finally, a number of future applications are discussed and their potential for urban studies and planning is assessed.
857 citations
"A Data warehouse based analysis on ..." refers background or methods in this paper
...CDRs have been used for analytical processing by the help of DW and data mining tools for many of the above mentioned purposes [3, 13, 14, 15, 16, 17, 18]....
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...For example in [13,14], the authors used mobile location data of hundreds of thousands of mobile phone users of city of Graz in Austria and created an ‘Mobile Landscapes’, visualizing the real time dynamics of the city....
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TL;DR: In this article, the authors survey the contributions made so far on the social networks that can be constructed with such data, the study of personal mobility, geographical partitioning, urban planning, and help towards development as well as security and privacy issues.
Abstract: In this paper, we review some advances made recently in the study of mobile phone datasets. This area of research has emerged a decade ago, with the increasing availability of large-scale anonymized datasets, and has grown into a stand-alone topic. We survey the contributions made so far on the social networks that can be constructed with such data, the study of personal mobility, geographical partitioning, urban planning, and help towards development as well as security and privacy issues.
556 citations
TL;DR: Analysis of the movements of 1.9 million mobile phone users in Haiti and the destinations of people who left the capital during the first three weeks after the earthquake suggest that population movements during disasters may be significantly more predictable than previously thought.
Abstract: Most severe disasters cause large population movements. These movements make it difficult for relief organizations to efficiently reach people in need. Understanding and predicting the locations of affected people during disasters is key to effective humanitarian relief operations and to long-term societal reconstruction. We collaborated with the largest mobile phone operator in Haiti (Digicel) and analyzed the movements of 1.9 million mobile phone users during the period from 42 d before, to 341 d after the devastating Haiti earthquake of January 12, 2010. Nineteen days after the earthquake, population movements had caused the population of the capital Port-au-Prince to decrease by an estimated 23%. Both the travel distances and size of people’s movement trajectories grew after the earthquake. These findings, in combination with the disorder that was present after the disaster, suggest that people’s movements would have become less predictable. Instead, the predictability of people’s trajectories remained high and even increased slightly during the three-month period after the earthquake. Moreover, the destinations of people who left the capital during the first three weeks after the earthquake was highly correlated with their mobility patterns during normal times, and specifically with the locations in which people had significant social bonds. For the people who left Port-au-Prince, the duration of their stay outside the city, as well as the time for their return, all followed a skewed, fat-tailed distribution. The findings suggest that population movements during disasters may be significantly more predictable than previously thought.
537 citations
"A Data warehouse based analysis on ..." refers methods in this paper
...Even CDR has been put to use completely different purposes [19] such as to analyze the population displacement pattern just after Haiti earth quake in 2010 and again in October 2010 during cholera outbreak to predict the areas that are at high risk of spreading....
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