Final Project

This is a four (4) part assignment. This consist of a written project plan, a revised business requirements document, a project plan PowerPoint presentation, and the finalized project plan. You must have Microsoft Project to complete the assignment. I will upload all previous projects in which the final project will be built upon. Please read the attached document titled “Final Project” as it holds the instructions of the assignment. Please make sure all the dates in the project plan are consisted with the initial project plan from deliverable 1 and the business requirements can be found in Project deliverable 2 document. I will upload the project plan from deliverable 5 as soon as I am done with it.
Project Deliverable 1:  Project Plan Inception
In the present super globalized world, numerous organizations face various challenges within each and every phase of their operations. The research and analytics services provided, by the company, are aimed at providing organizations with an added advantage. Terabytes of data is processed and analyzed by the organization and all the chatter and fuzz around those data are removed so that the customers can receive a proper understanding regarding the competition they are facing and the market in which they are present.
The research, analytical processing, and collection of data, done by the organization, is leveraged and by putting focus on the functional excellence with an industry-level standard model of delivery, leading organization can make intuitive decisions regarding the business.
A complete portfolio of the services of the organization includes of financial, business, and market research, domain centered analytics and processing of data services. The main focus of the organization is on manufacturing, retailing, insurance, and FMCG, finance and banking industries.
Collection of Data

  • SP-centered Data – The data which is generated via the network traffic is known as SP-centered data. It offers data to the tool suppliers. Secure data is not collection.
  • Panel-centered Data – This is the data collected from the internet users.
  • Tool-monitoring Data – The user installs this data. A critical example of this type of data is Alexa.
  • Online monitoring Data – The users take surveys and offers data to the organization.

Description of Information System
The organization contains an online database used for the processing of manual data, batches, messages, and data. It consists of 2 integrations –

  • Vertical integration – Here the data processing is performed in the office (ERP), and,
  • Horizontal integrations – In this process, data is achieved in numerous archival systems.

Databases consists of Open SQL Database in which messages, batch data, and process values are saved. It offers client-server architecture for data display. In addition to data display, the users also have the capability to perform data evaluation, analysis of data, and generation of reports.
Hardware and Software

  • Server Hardware – Minimum – P IV, 100GB HDD, and 1GB RAM.
  • Client Hardware – Minimum – P II, 500 MHz
  • Server OS – Windows 2003 Server or Windows 2000 Server.
  • Client OS – Windows XP or Windows 2000.
  • Server Database – MS-SQL Server 2000 or Sybase.
  • Client Database – MS-SQL Server or Sybase.

Additional Components

  • Development toolkits
  • Interface with ‘other systems’
  • Maintenance
  • Parameter control
  • Interface with ‘web server’
  • Electronic signature
  • Document archive
  • Standard reports
  • MS-Excel add-on
  • Value correction/Manual data
  • Batch reports, and archiving (including e-signature)
  • Backup server
  • Redundant coupling
  • Messages
  • Process values (500-15,000 values/minute)

Types of Business
Web Analytics – The organization’s proficiency in web analytics comprises of the following operations –

  • Social Media Analytics and Data Mining
  • Conversion rate analysis
  • Content analysis and research
  • Online traffic analysis
  • Campaign management – from inception to completion in addition to ROI Analysis
  • Up-sell/cross-sell analytics and acquisition
  • Retention of consumers.

Business and Finance Research – The organization’s proficiency in business and finance research backs its client’s tactical decision-making and daily operation by helping with reports, research, and intelligence.
Detailed Organization and Industry centered Research –

  • Company profiles and tear sheets.
  • Value chain analysis, SWOT, shareholdings, and stocks.
  • Standardization of industries and detailed reports on various sectors.
  • Business intelligence
  • Positioning tactics and market entry
  • Future predictions and trend analysis
  • Demographic and economic studies
  • M&A support and Corporate finance
  • Support for preparation of Pitch Book
  • LBO models, comparisons and benchmarks
  • Financial analysis and valuations
  • Equity research
  • Models of finance and predictions
  • Research reports
  • Earning summarization
  • End-to-end providers of solution to research and corporate houses, and market research
  • Designing surveys
  • Proposal research
  • Composing proposals
  • Composing set of questions
  • Management of surveys
  • Programming of surveys
  • Performing web surveys
  • Management of online panel
  • Processing and management of data
  • Processing of data
  • Coding and scripting
  • Transcription of data
  • Data validation
  • Analysis of content (for qualitative GDs and Dis)
  • Report writing and presentations
  • Report validation
  • Composing tabulated data
  • Presenting reports regarding major PPT software
  • Market research analytics
  • Modeling of brands
  • Modeling of consumers
  • Segmentation of market
  • Mixture of marketing

Outsourcing Activities
Outsourcing and offshore activities consists of the following activities –

  • Conversion and processing of data – Processing and collection of data MS-Excel, and CSV. Conversion of data to other DB formats like SPSS, SAS, Quantum, etc. for additional processing.
  • Processing of data – Banner tables.
  • Conversion and processing of data into tabulated format.
  • Processing of data – Services of Data Analytics.
  • High-level statistical services for the promotion of fact-centered decision making for the organization.

Data Warehouse
The organization collects a large amount of data which typically runs into terabytes. A warehouse of data is the only choice even though it is not very organized, compared to RDBS. However, when it is utilized along with RDBS, data warehouse provide a huge assistance. Each moment, an individual visit to a webpages generates a large number of records which needs to be stored. Data might become obsolete, however, it can’t be removed and in a few months’ time, it can be utilized for analysis. This generation of analysis provide future prospects for the business. This analysis relies on the manner in which collection of data is done, and how effectively it has been arranged to provide a clear image for analysis. A data warehouse supplier which will enhance the analytics operations was sought after.
The organization’s information system contain interfaces for evaluation of data, that is, reports explained by users via MS-Office (MS-Word and MS-Excel), standard software components like Business Objects and Crystal Reports. As the organization is almost 2 years old, Google Analytics is being utilized for web analytics.

Infrastructure and Security

The company has employed various security policies such as Issue-specific security policy, Enterprise Security Policy and Systems-Specific security policy. It also employs NIST security model and works on the architecture of IETF security. In addition to this, it has chosen firewalls on the basis of its structure and also implements an Intrusion Detection and Prevention Systems. Access roles and privileges are defined for accessing Virtual Private Network.
Kimball, R., & Ross, M. (2011). The data warehouse toolkit: the complete guide to dimensional modeling. John Wiley & Sons.
Luján-Mora, S., Vassiliadis, P., & Trujillo, J. (2004). Data mapping diagrams for data warehouse design with UML. In Conceptual Modeling–ER 2004 (pp. 191-204). Springer Berlin Heidelberg.
Intel Corporation, 2015. Big Data in the Cloud: Converging Technologies : How to Create Competitive Advantage Using Cloud-Based Big Data Analytics, s.l.: Intel Corporation.
Gall, M. et al., 2011. Analysis of Requirements for the Deployment of Cloud Systems, s.l.: ASMONIA.

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