University of Manchester Big Data Community
De Wiki de Ilan Chamovitz - Informatica, Administracao, Eng. Producao, Educacao, Tecnologia da Informacao
Manchester Informatics Big Data Community Launch | Building the Big Data Community at Manchester
http://events.manchester.ac.uk/event/event:mf-hofjobi0-gycpyv
Big Data is one of the 8 great technologies that are driving funding over the next few years.
(source: https://www.gov.uk/government/publications/eight-great-technologies-infographics )
Supporting technologies where our science strengths and business capabilities combine is a core part of the government’s Industrial Strategy. In autumn 2012 the Chancellor highlighted eight great technologies where the UK can lead the world, announcing an additional £600 million investment to support their development.
We selected the eight great technologies after carefully analysing UK scientific and business capabilities. Each technology: •is an area in which the UK has world-leading research •has a range of applications across a spectrum of industries •has the potential for the UK to be at the forefront of commercialisation
The eight great technologies are: •big data and energy-efficient computing •Satellites and commercial applications of space •robotics and autonomous systems •synthetic biology •regenerative medicine •agri-science •advanced materials and nanotechnology •energy and its storage
These 8 areas show how the government is working with researchers and industry to foster world class technology capability in the UK. They are not exclusive or exhaustive, and there are many other important areas of science and innovation in which the UK excels and will excel in future.
Some insights concerns to all V's and can be explained at http://inside-bigdata.com/2013/09/12/beyond-volume-variety-velocity-issue-big-data-veracity/
Beyond Volume, Variety and Velocity is the Issue of Big Data Veracity
Retrievend from http://inside-bigdata.com/ (by Kevin Normandeau)
Volume
Big data implies enormous volumes of data. It used to be employees created data. Now that data is generated by machines, networks and human interaction on systems like social media the volume of data to be analyzed is massive. Yet, Inderpal states that the volume of data is not as much the problem as other V’s like veracity.
Variety
Variety refers to the many sources and types of data both structured and unstructured. We used to store data from sources like spreadsheets and databases. Now data comes in the form of emails, photos, videos, monitoring devices, PDFs, audio, etc. This variety of unstructured data creates problems for storage, mining and analyzing data. Jeff Veis, VP Solutions at HP Autonomy presented how HP is helping organizations deal with big challenges including data variety.
Velocity
Big Data Velocity deals with the pace at which data flows in from sources like business processes, machines, networks and human interaction with things like social media sites, mobile devices, etc. The flow of data is massive and continuous. This real-time data can help researchers and businesses make valuable decisions that provide strategic competitive advantages and ROI if you are able to handle the velocity. Inderpal suggest that sampling data can help deal with issues like volume and velocity.
Veracity
Big Data Veracity refers to the biases, noise and abnormality in data. Is the data that is being stored, and mined meaningful to the problem being analyzed. Inderpal feel veracity in data analysis is the biggest challenge when compares to things like volume and velocity. In scoping out your big data strategy you need to have your team and partners work to help keep your data clean and processes to keep ‘dirty data’ from accumulating in your systems.
Validity
Like big data veracity is the issue of validity meaning is the data correct and accurate for the intended use. Clearly valid data is key to making the right decisions. Phil Francisco, VP of Product Management from IBM spoke about IBM’s big data strategy and tools they offer to help with data veracity and validity.
Volatility
Big data volatility refers to how long is data valid and how long should it be stored. In this world of real time data you need to determine at what point is data no longer relevant to the current analysis.
The University of Manchester has internationally recognised strengths in Big Data (including linked data and open data) across a range of faculties.
On the 9th December, Manchester Informatics is launching the Big Data Community, in order to bring together these research strengths and to promote interdisciplinary collaboration in all forms of data research. The intention is to improve the University's responses to funding calls in Big Data and help to raise Manchester’s profile as a leading centre for Big Data research.
Our first event, 'Building the Big Data Community at Manchester,' will seek to map out the landscape of Big Data research taking place across the university, begin working towards building interdisciplinary relationships and seek to showcase our strengths to external organisations.
We would very much encourage researchers from all disciplines to join us at Chancellors on the 9th December 2013.
More about bigdata (history)
2012 Critical Questions for BigData http://www.tandfonline.com/doi/pdf/10.1080/1369118X.2012.678878
T H E D I G I T A L U N I V E R S E I N 2 0 2 0 :B i g D a t a , B i g g e r D i g i t a l S h a d o w s , a n d B i g g e s t G r o w t h i n t h e F a r E a s t http://www.emc.com/collateral/analyst-reports/idc-the-digital-universe-in-2020.pdf
