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In the eight years
that Data Science Automation has been in existence, we have
developed a methodology to our project execution that has proven
to be very successful. During the design, development, installation
and maintenance of hundreds of projects, we have refined our
methodology; constantly improving on the services we are able
to provide our clients. Data Science Automation has been using
this methodology of a distinct Planning Phase followed by the
Implementation Phase with great success for both our company
and that of our client.
The key aspect of the Planning Phase is the development of a
project specification document. Like the blueprint for a house,
this document guides all further project related work. It details
the specific tasks, responsibilities, functionality, user interface,
timeline, costs, manpower allotments, work schedules, development
tools, documentation, installation, and client acceptance criteria.
The Implementation Phase is then only an execution of the details
provided in this specification document. DSA has been using
this project approach for many years with great success for
both our company and our clients. It eliminates rework and helps
ensure the integrity of the project timeline.
Applying our methodology to your project will ensure successful
completion of the project within the budget and time constraints.
PLANNING PHASE
All projects contracted with Data Science Automation start with
a project Planning Phase during which the projects feasibility
is evaluated, the specifications are documented, user interface
templates and the application software architecture is designed,
and hardware selection is finalized. The typical Planning Phase
deliverables may include estimated measures of ROI, documented
specifications, flowcharts and schematics, and functional software.
The design phase is divided into four stages: Feasibility, Specification,
Design, and Procurement.
| Feasibility
Stage |
Specification
Stage |
Design
Stage |
Procurement
Stage |
| The
first stage of the project is to study the feasibility
of the project. During this stage, a process consultation
is conducted, feasibility of an automated solution is
evaluated, capabilities of different tools may be compared,
and the estimated cost of the implementation is weighed
against the estimated return on investment (ROI). In addition,
one needs to consider the reliability and future maintenance
and upgrade costs of the selected solution. |
During
this second stage of the project, jointly with the client,
we will develop a specifications document. With an established
list of relevant questions, we break the project into
a list of specifications and establish their importance,
urgency, complexity, interdependence and estimated cost.
We will also identify/define scalability requirements,
performance/acceptance criteria, timeframes and budgets
during this time. |
With
the help of the specifications document, we design the
application in this next stage. During this stage, software
and process flow-diagrams, system schematics, and screen
layouts are developed, revised and approved by the client.
Proof-of-concept, functional prototypes may be developed
and refined time and cost estimates completed. In addition,
third-party vendors are considered and system components
are selected. |
This
stage involves the procurement of any/all third-party
components identified for system development and deployment. |
IMPLEMENTATION PHASE
The design phase is followed by the project Implementation Phase.
During this phase, the application software functionality is
coded, hardware is configured and tested, hardware and software
are integrated, the system is tested, client acceptance testing
is concluded, and documentation is developed and updated. The
Implementation Phase is also divided into four stages: Development,
Testing, Deployment and Support.
| Development
Stage |
Testing
Stage |
Deployment
Stage |
Support
Stage |
| The
actual application is built to design specifications in
the development stage. Software programming is performed
and modular hardware assembly/integration occurs. During
this stage the individual application modules will undergo
'Alpha' or unit-level testing. With frequent client interaction
the application will begin to take its final shape in
this stage. |
At
this point the application modules and necessary hardware
is ready for on-site assembly, integration and 'Beta'
or system-level testing. on to the next stage, while errors
will put us back into the development stage |
Once
modular testing has been completed to the satisfaction
of the client, the system is delivered in its final form,
installed at the client's location, and fully integrated
with the client's process. 'Gamma' or verification-testing
of acceptance/performance criteria is performed during
this stage. Operator training is also conducted for the
use of the application as provided. |
Now that the application is successfully
installed at the client location, Data Science Automation
provides a variety of ongoing calibration, maintenance
and support contracts to provide the client with continued,
high quality service for their automation needs.
This is our preferred, staged approach. However, we
recognize that certain client requirements or methods
may necessitate a higher level of flexibility. We pride
ourselves on balancing the client's expectations with
good project management and process development disciplines
throughout the lifecycle of the project.
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