AAi NewsBytes May 2015
May 2015 Edition
The Real Data Scientist
Three years ago, in 2012, the Harvard Business Review was calling the role of data scientist “the sexiest job of the 21st century”, and roughly this time last year, Forbes columnist Bob Violino wrote that data science skills “are among the hottest, with demand far outstripping supply”. No one doubts the crucial role data scientists will play with the rise of big data projects, but all too often, “data scientist” is used as a blanket title to describe a range of jobs. Frequently, the question is asked “what exactly is a data scientist?”
A common response is to define a list of critical or desirable skills; a recent article by Gregory Piatetsky, co-founder of the KDD conference and ACM SIGKDD Association for Knowledge Discovery and Data Mining, showed that a search of keywords in job descriptions returned a list of specific skills, such as knowledge of SQL, Python and R. Experience in business or analytics also featured strongly in a list of desirable attributes. Topping this list of keywords, however, was the term “team”, which appeared in 88% of the job ads analysed.
Clearly, today’s specialists in analytics need a comprehensive skill set to face the challenges posed by a dynamic and changing market. Technical ability is paramount but there is also increasing recognition that a successful data scientist must have a strong understanding of how data can be used and applied in a wide range of environments. This requires sound understanding of the industry they are working in. More, they must be able to communicate with stakeholders, which requires the ability to clearly express their technical findings to non-technical clients or colleagues. Above all, they must be a capable and willing member of a team, prepared to work collaboratively to identify problems and discern new ways to leverage data to achieve positive outcomes.
Remember: there’s no shortage of useful data in most organisations and government departments which, when properly mined and interpreted by AAi, can created unexpected opportunities for driving productivity and business growth.
Advanced Analytics Institute
Big Network and Graph Data ScienceA major value of data science lies in its ability to help people understand their data and discover potentially important knowledge from the data. The process of discovering knowledge from data is the essence of data science (traditionally known as data mining), which cannot be achieved effectively without proper data representation technologies. Using networks and graphs to represent multi-relational big data has become increasingly important in modelling big data structures and their interactions. Network and graph representation naturally captures critical structural elements and important feature iterations in many types of practical systems and domains, such as road networks, social networks, telecommunication networks, customer service networks, and email networks, as well as the biological gene-to-gene interaction network. Because of the significance of such data representation techniques, the AAi research program “Big Network and Graph Data Science” strategically selects network and graph data analytics to develop the next generation data scientific algorithms for social benefit. Read more here | |||
Various Flavours of Big Data in Computer Vision, Banking and Teaching At the recent UTS Data Science Symposium, Prof Massimo Piccardi presented the approach of his research team in relation to Big Data and its relevance in the diverse fields of computer vision, banking and teaching. Prof Piccardi highlighted that sample size, dimensionality and structure are key parameters for defining Big Data; however, while data can be big because they are many, each sample can also contain many values (dimensions), or have structured values. Data of such large dimensionality result in a large model, which carries the risk of overfitting. Prof Piccardi also shared his view of the data science skills spectrum, ranging from software engineer and data engineer to data scientist, applied scientist and research scientist. Read more here | |||
CeBIT and CITTC AAi’s Multimedia and New Media Analytics research group continues its work to demonstrate its intelligent video surveillance and multimedia search project at various industry events including Sydney CeBIT event in May and and Beijing CITTC in April. These demonstrations are a reflection of the group’s years of research on video analytics for traffic monitoring and include vehicle counting, vehicle tracking, vehicle re-identification and vehicle behaviour analysis on freeways or at intersections in metropolitan areas. Read more here. | |||
Programming for statistical computing and graphics R is a widely used programming language and software environment whose popularity has increasingly grown since its inception in 1993. Participants in our previous short courses on R Programming Stages 1 and 2, and others who already have a working knowledge of R, will be pleased to know that Stage 3 (Advanced) will be offered by AAi on 11 June 2015. Follow this link for more details, and to register Short Courses in July – dates for your diary The following short courses will be offered in July: Wednesday 8 July -- Advanced Data Analytics - an Introduction Friday 10 July -- Data Mining - Stage 1 (Introduction) Wednesday15 July -- R Programming – Stage 1 (Introduction) Wednesday 22 July -- Text Analytics and Sentiment Analysis - an Introduction AAi Education – Public and In House (Corporate Training) AAi offers a range of public short courses in data analytics that we strive to constantly review and update. We also deliver in-house (corporate) training selected from our present portfolio of short course topics, and can develop topics specifically tailored to your organisation. Short Course Survey We welcome your input and suggestions in relation to our short course program, and invite you to take part in the AAi Education and Training Short Courses Survey. Your contribution will enable us to stay ahead of the field in offering relevant, dynamic and effective programs to suit the current market. |