Cloud-Based LMS with Big Data and Machine Learning

built on PRINCE2-DSDM-XP-COBIT5 software for

Educational Institutes
Business Plan Proposal

Table of Contents
INTRODUCTION

PROJECT MANAGEMENT METHOD

MARKET SECTOR DEFINITION

PRODUCT DEFINITION

BIG DATA INTO THE CLOUD

MACHINE LEARNING INTO THE CLOUD

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8

REQUIREMENTS TO ENTER THE MARKET

FEASIBILITY STUDY AND BUDGET DEFINITION

MARKET AND PRODUCT

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

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10
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BUSINESS ETHICS AND VALUES ORIENTATION

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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

use of PRINCE 2 software 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
employment 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 ProcessorBased 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.

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 software 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:

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.

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)

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 costeffective 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
whats 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

with initiatives like VMwares 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:

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.

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 Software
(PRINCE 2, DSDM, XP, COBIT 5).

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 and 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

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 customeroriented 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.