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Oxford Software Engineering is pleased to present:




 Software Development Analytics




Friday, 26 June 2015, 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.





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.





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, September 2014
















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