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Oxford Software Engineering is pleased to present: Software Development Analytics - Friday, 29 April 2016, Central London “Data,
data, data, I'm surrounded by data. Can't anyone give me the information I
really need.” - Alexander the Great Contemporary software development
environments are generating large quantities of data about systems,
development activity, as well as project status, risks and prospects. These
data can give you an edge – if you can extract and interpret the relevant
information, and have the confidence to act on the insights it gives you. Sound analysis that delivers credible
results gives you that edge. It gives decision makers, whether technical
staff or managers, the
confidence to act on the information extracted from these subtle and complex
environments, and the ability to communicate the information convincingly and
unambiguously. This one day course brings together, for
the first time, the most useful and robust analytical and statistical methods
for extracting information for software development’s complex, unique and
occasionally messy data. It shows how anyone can make friends with their
data, learn from it and act, and share what they have learned with others. Contents: The course has been designed to equip
software professionals with a variety of specialist tools for understanding
and analysing the data being produced by design intensive, software development,
and knowledge working environments. It has six stand alone modules, each
containing a collection of useful methods, techniques and examples. These
build into a set that enable participants to confidently address their
information needs with technically correct, focussed analysis of their data
that delivers accountable and communicable results. The modules: 1.
Characteristics of Software Development, Test and Project Data: What is it
that makes software development and test data different? In this module the
characteristics of software and software development data, and data generated
in design intensive and knowledge working environments are explored. The
constraints (and opportunities) this places on analysis are identified as a
foundation for the selection and application of analytical techniques and
statistical tests. 2.
Making Friends with the Data – Graphical Techniques: Good analysis is not simply a matter
of selecting and applying the right techniques but a matter of exploring and
understanding the data. In this module the techniques for this are presented,
showing how there is far more to data analysis than procedures for
evaluating ‘significance’ and
‘confidence’. 3.
The Search for Pattern – Transformation and Regression: Information doesn’t
always reveal itself directly. Data needs to be presented in a way that
allows patterns to reveal themselves enabling analysts to ask further,
searching questions – if needed. This module shows you how to present the
data to reveal underlying patterns, and how to evaluate them. 4.
Odds and Probability: There are no guarantees that your
decisions will be right, sadly, but they can be the best, given available
information. This module explores what we mean by probability and chance, and
how this influences how decisions are made. 5.
Statistical Tests: When the data is well understood it can be used to test
‘hypotheses’ and to make inferences as an aid to decision making. Statistical testing distils out the
essential information to improve the odds that your decisions will be
accountable, and the best possible. 6.
Modelling, and other Topics:
This module rounds out the course be presenting a variety of topics
that give a balanced view of data analysis. Topics include: ‘no data’
decision making, modelling (including Monte Carlo’) and Bayesian statistics. Outcomes & Benefits: At the end of the course you will be able
to characterize you data, enabling you to select the correct techniques to
reveal the information you need. You will have an improved ability to
evaluate complex situations and a better decision making capability, as well
as being able to communicate the information you extracted in a convincing
and credible way. An addition
benefit is the ability to detect defective, inappropriate or misleading data
analyses received from elsewhere. Who should attend: Anyone working in a complex technical
environment who needs to better understand their environment as an aid to
decision making and to communicate their understanding with others. Presenter: The presenter is Clifford Shelley. He is a
software developer with a background in analytical and statistical
methods. He has a long standing
interest in software measurement and data analysis with experience in (CMMI)
high maturity organizations and agile development environments. He is a
popular trainer and speaker and a member of the UK Software Measurement
Association. Course details and Logistics: Venue:
Central London – venue and joining details will be sent to you after
registration. Time:
9.30 – 16.30 with morning and afternoon breaks and 45 minutes for lunch. Course Format: Interactive: a mix of lectures with
examples and workshops. Cost:
£545 plus VAT Registration:
To register simply email your request to take part to: shelley@osel.netkonect.co.uk CCS, March 2016 |
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New PODS Products & Services
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