Cloud - Big Data

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Cloud-Based LMS with Big Data and Machine Learning built on PRINCE2-DSDM methods and XP-COBIT5 software for Educational Institutes Business Plan Proposal Table of Contents INTRODUCTION 1 PROJECT MANAGEMENT METHOD 2 MARKET SECTOR DEFINITION 4 PRODUCT DEFINITION 5 BIG DATA INTO THE CLOUD 6 MACHINE LEARNING INTO THE CLOUD 8 REQUIREMENTS TO ENTER THE MARKET 9 FEASIBILITY STUDY AND BUDGET DEFINITION 9 MARKET AND PRODUCT 9 PRODUCT PHASES 9 TIME LINE 10 STRATEGIES AND CONTROL 10 PRODUCT DIFFUSION PROCESS INTO THE MARKET 11 BALANCE SHEET 11 BUSINESS ETHICS AND VALUES ORIENTATION 11 Introduction Our organization (CSC) provides IT-solutions aimed towards innovation. We would like to provide a product (service) able to meet the requirements the transformations in the educational field demands. In the following chapters we will provide the elements we would like to implement in order to achieve our purpose. Therefore, we will discuss our Project Management Method regarding the

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Cloud-Based LMS with Big Data and Machine Learning built on PRINCE2-DSDM methods and XP-COBIT5 software for Educational InstitutesBusiness Plan Proposal

Transcript of Cloud - Big Data

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Cloud-Based LMS with Big Data and Machine Learning built on PRINCE2-DSDM methods and XP-COBIT5

software for Educational Institutes

Business Plan Proposal

Table  of  Contents  

INTRODUCTION   1  

PROJECT  MANAGEMENT  METHOD   2  

MARKET  SECTOR  DEFINITION   4  

PRODUCT  DEFINITION   5  

BIG  DATA  INTO  THE  CLOUD   6  MACHINE  LEARNING  INTO  THE  CLOUD   8  

REQUIREMENTS  TO  ENTER  THE  MARKET   9  

FEASIBILITY  STUDY  AND  BUDGET  DEFINITION   9  

MARKET  AND  PRODUCT   9  PRODUCT  PHASES   9  TIME  LINE   10  STRATEGIES  AND  CONTROL   10  PRODUCT  DIFFUSION  PROCESS  INTO  THE  MARKET   11  BALANCE  SHEET   11  

BUSINESS  ETHICS  AND  VALUES  ORIENTATION   11  

   

Introduction   Our organization (CSC) provides IT-solutions aimed towards innovation. We would like to provide a product (service) able to meet the requirements the transformations in the educational field demands. In the following chapters we will provide the elements we would like to implement in order to achieve our purpose. Therefore, we will discuss our Project Management Method regarding the

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use of PRINCE 2 in order to tackle the management process, its integration with DSDM in order to cope with the development, feasibility and integration of our product, the employment of Extreme Programming (XP) software in order to face the delivery process and eventually, the application of COBIT 5 in order to provide quality, security and limit information technology risk. Afterwards, we will analyse the Market Sector we would like to enter to and how we justify our choices in regard to the educational field. Moreover, we will define the Product we would like to deliver and why it represents an innovation in the market by comparison with our competitors: we will see that Cloud-Based LMS with Big Data Analysis and Machine Learning is the right direction and how Xeon Processor-Based servers and storage along with Intel networking resources and Big Data processing tools provides the high-performance compute power needed to analyse vast amounts of data efficiently and cost-effectively in order to achieve our goals. Our next step would define the Requirements to Enter the Market in relation to what we consider the best approach possible. Eventually, we will define aspects of our Budget, some characteristics of the Feasibility of our business plan and our Business Ethics and Values Orientation.

Project  Management  Method   In order to deliver efficiency we need a solid approach to the phases of development and implementation of our product. We believe that the integration between PRINCE 2, DSDM and XP represents the best possible choice in regard to the Project Management method to implement.

- PRINCE 2 provides the overall Project Management and governance processes.

- DSDM is used as a wrapper for XP to provide process and control within PRINCE 2.

- Selected XP techniques are used within DSDM for software engineering aspect of delivery.

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Moreover, a useful tool that allows managers to bridge the gap between control requirements, technical issues and business risks could be implemented. COBIT 5 software represents the best solution since guarantees the quality, security and limit information technology risk through the use of methods such: aligning, planning, organizing, building, acquiring, implementing, service delivery and supporting. It aligns with frameworks and standards such as Information Technology Infrastructure Library (ITIL), International Organization for Standardization (ISO), Project Management Body of Knowledge (PMBOK), The Open Group Architecture Framework (TOGAF) and the Management method we intend to use: PRINCE 2. COBIT Process Model Table

A synched DSDM/PRINCE 5 approach should be undertaken as the Organizational Chart shows below:

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Market  Sector  Definition   Given the nature of the challenge we are facing and the current tech. developments in the educational field we hold the necessity to address our products to both public and private education-oriented organizations:

- Schools (K-12 or other depending on the country) - Universities - Institutes - Organizations with educational purposes

Many researches and surveys show us how there is a positive trend regarding the integration between technologies and education; we, hence, believe this market sector to be extremely promising for future returns.

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Moreover, to provide innovation and value to the community in a broad sense represents a paramount value for our organization.

Product  Definition   In order to deliver a competitive product we must focus on innovation and be able to satisfy the technological and educational needs of our clients. Moreover, given that our organization (CSC) already provides Cloud solutions and has specific and pertinent resources in this field we believe that a Cloud-Based LMS platform with a Big Data Analysis tools and Pattern Recognition software is the answer. The Cloud presents the usual basic features that define it: IaaS, PaaS and SaaS characteristics. Moreover, it has to provide the educational content necessary to satisfy our clients’ requirements. Therefore, it is necessary to integrate an LMS/LCMS platform (SaaS) compatible with the Cloud. Examples of possible LMS/LCMS platforms could be:

- DoceboLMS - EduWave - Expertus - Litmos - TalentLMSTOPYX

Given the previous considerations, our Cloud has to provide:

1) Customer-Oriented Features - institute requirements, needs and

goals:

- LMS Platform (provides the administration, documentation, tracking, reporting and delivery of E-learning education courses or training programs and includes: Digital Learning (Blended Learning and Flipped Classrooms) and Educational Simulation software)

- Tech. Level Diagnostic app. (emphasise where there is room for technological improvement within the institute) – this serves also as a first analysis of what the customer lacks and can come as a promo product.

- MOOC Integration Possibility (when/if required)

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2) Individual-Oriented Features - institute stakeholders (students,

teachers, etc.) needs:

- LCMS Environment for teachers (they can collaborate and create educational content to be delivered via the LMS platform)

- LCMS Environment for students (easy-to-use platform in which students can develop educational projects, share contents, create a community and work together under the tutelage of teachers)

3) ICT Cloud Software Features – tech. methods to be implemented into the product in order to delivery quality and innovation:

- Pattern Recognition - Machine Learning - Complex Analysis - Big Data Analysis

All these Cloud software Features represent the core of our product innovation.

Big  Data  into  the  Cloud   The presence of Big Data Analysis into the Cloud represents a new feature: AaaS (Analytics as a Service). Cloud computing offers a cost-effective way to support Big Data technologies and the advanced analytics applications that can drive business value. Predictive analytics will allow us to move to a future-oriented view of what’s ahead and will offer opportunities for driving value from big data. Real-time data provides the prospect for fast, accurate, and flexible predictive analytics that quickly adapt to changing conditions. Combining the Intel® Xeon® processor-based servers and storage, along with Intel SSDs and Intel 10 GbE networking resources used in Cloud environments, with Big Data processing tools like Apache Hadoop* software provides the high-performance compute power needed to analyse vast amounts of data efficiently and cost-effectively. Running Hadoop* in virtualized environments continues to evolve and mature

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with initiatives like VMware’s open-source project Serengeti*, among others. Using Cloud Infrastructure to analyse Big Data strengths:

- Big data may mix internal and external sources - Data services are needed to extract value from big data - Investments in big data analysis can be significant and drive a need

for efficient, cost-effective infrastructure

Through this method we can address user needs across the full range of analytics requirements with cloud-based AaaS, from data delivery and management to data usage. By developing a comprehensive cloud-based Big Data strategy, we can define an insight framework and optimize the total value of the enterprise data. An AaaS insight framework encompasses the following key capabilities:

- Capturing and extracting structured and unstructured data from trusted sources, including prioritizing the most critical data and identifying what to retain and for how long.

- Managing and controlling data under comprehensive policy and governance guidelines across a global enterprise and in compliance with specific industry requirements.

- Performing data integration, analysis, transformation, and

visualization to deliver the right information to the right location at the right time.

Big Data in our Cloud will allow educational institutes to analyse grades, absences, etc. for individual students and might be able to predict behaviour that leads to negative or positive educational outcomes. This would enable educators and teachers to be proactive at an early stage and help or support their students. Moreover, it will allow institutes to predict trends and cultural transformations that can be paramount to reorganize their educational content and face the new challenges ahead. Our IT team can work with our business users to get the best cloud-based analytics solution possible by making sure these important areas are considered:

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Machine  Learning  into  the  Cloud   The presence of Machine Learning software provided with a Pattern Recognition tools based on Complex Analysis into our Cloud will allow institutions to track the preferences of every student/user through computational statistics and mathematical optimization, allowing them to provide a customized educational content to their students. Our specific tasks are to find valuable insights, patterns and trends in Big Data (large volume, velocity, and variety) that can lead to actionable information, decision-making, prediction, situation awareness and understanding. To complete these technical tasks, we intend to integrate our Cloud framework with machine learning technologies. It can be realized through the use of the Hadoop* cluster by leveraging Apache ecosystems and focusing on analysing and mining our data sources by using open source ML algorithms and by developing our own ML algorithms using software like Matlab.

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Requirements  to  Enter  the  Market    

- Market Survey - Benchmarking our competitors - Advertisement and Marketing Strategy - Possible Partnerships Consideration - Product Feasibility and Testing - Policy, Patent and Legal Requirements

Feasibility  Study  and  Budget  Definition  

We believe that focusing on innovation and the human factor are the keys of the future. ���

Market  and  Product   We are delivering a product that presents elements of incremental innovation by comparison with our competitors already present into the market (incumbents) considering that Cloud-Based Platforms are already present into the market. Nevertheless our product presents elements of radical innovation if we consider features such: Big Data Analysis and Machine Learning. We believe that this is the way towards the future. Moreover, we believe that our choice to enter the market is justified consider that our product is driven by elements of “market pull” (more and more institutes are considering Cloud-Bases Platforms as an investment) and “technology push” (the technology is at our disposal and needs only to be implemented).

Product  phases   - Development - Testing - Launch The phases will be developed through the Project Management Method (PRINCE 2, DSDM) and Software (XP, COBIT 5) process.

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Time  Line  

We believe that we can deliver into the market in less than 3 years considering that our company (CSC) has already the Cloud-Based technology we need while all the additional software needed are already present.

Strategies  and  Control   Given the market circumstances we must focus on a Quality Function Development (QFD) Strategy based on the House of Quality (HOQ) Principle and SWOT Analysis: - Define the Market circumstances - Surveys and Benchmarking - Analysis and Implementation of the HOQ - SWOT Analysis SWOT Analysis Diagram

Following this strategy we will be sure of the “goodness” of our product, we will reduce the lead-time (time to market) and minimize our

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development costs. Moreover, our LMS platform will be more flexible and customizable. Furthermore, our Business Core Strategy will better define the following criteria: - Costumer value proposition - Technology implementation - Growth strategy - Opportunities Identification.

Product  Diffusion  Process  into  the  Market   We can obtain good valuations if considering the Brass Model as far as the diffusion process of the product into the market is concerned:

n(t) = dN(t)/dt = p[m – N(t)] + q/m * N(t) [m-N(t)] n(t) = sum of costumers that had implemented innovation (our product) in the time t. m = market potential for innovation p = coefficient of innovation (depends on the inclination to implement innovation independently from social influences) q = coefficient of imitation (expresses the probability of implementing innovation depending on social influences)

Balance  Sheet  

- Investment Analysis Considerations - Valuation of fixed costs - Valuation of variable costs - Valuation of expected ROI

Business  Ethics  and  Values  Orientation   Our organization strives for delivering excellence; we are customer-oriented and create an environment for positive change built on collaboration and trust. We aspire individually and collectively to be more tomorrow than we are today and accept individual responsibility for our commitments and expect to be accountable for results. Moreover, our ethics compel us to put humanity into the center of every business and activity: we believe in what makes us human beings.