My first encounter with Big Data was during my university studio project – part of my course work as Town Planning student in University Technology Malaysia (UTM). Our lecturer will divide the class into 2 teams and we were given an assignment to prepare a regional development plan within 1 semester. We started our assignment by gathering policy, guideline, zoning data from local authority, state agencies, environmental department, irrigation and drainage department, etc. At the end of the assignment, we will present our proposed regional development plan to our fellow course-mates and lecturers and substantiate our proposal with rationale backed by facts and figures.
One of the usual comments given by our lecturers that I still remember is – Our group has gathered loads of data but failed to turn them into information to support our rationale/analysis/proposal”. On hindsight this can be due to many reasons, among others not enough scientific methodology was used to process the data, we were not effective in communicating our findings, or lacked of visual aids to integrate various data sources into useful and easy to understand information for our audiences.
Have you had similar experience in your recent presentation to your bosses/stakeholders?
Hence, challenges associated with big data are not new. It is about how to effectively turn massive amount of data into useful information that will help you make decision, whenever you need it and in format usable for you. Else the data still remain as data and it wouldn’t help you to be more informed.
Richard Leadbeater, Esri State Government Industry Manager once wrote “Big Data: The Three Vs and the Missing L“ – there is much attention applied to the three Vs of big data – Volume, Velocity and Variety of data. GIS provides the foundation for information integration by assembling massive amounts of data – often, types of data that are unrelated except for their geographic Location. He opines GIS map provides better understanding and reference than an informative spread sheet.
Nearer to home, Datuk Prof. Sr Dr. Abdul Kadir Bin Taib (Director General of Department of Survey and Mapping Malaysia, JUPEM) once said this in his conference speech, he was appealing to all attended to not just manage geospatial data, but manage all our data geospatially. According to him, managing our data geospatially will allow us to be more informed and our data is more accessible in the form of useful information, where and when we need it, that will help enhance our understanding by leveraging on the location analytic capability of GIS technology.
Indeed, location analytic helps many enterprises to take advantage of this processed information to next level and reveal greater insights and understandings. GIS is the most important element of location analytics. It enables users to turn data into information and add in 2D/3D location dimension, as well as 4th dimension (time) to produce useful insights/pattern (distribution), co-relations, hidden in between rows and rows of textual/database records. If a picture can tell a thousand words, how will you describe an informative/interactive/analytic map that can generate endless scenarios and analysis supporting your decision-making?
Location analytic is not just meant for business community but any organizations that would like to drive performances or Key Performance Indicators (KPI), be it in utilities, public sectors, education, finance/insurance, transportation, retail, etc. To read more about location analytics, I have uploaded a good white paper from Esri explaining Location Analytics for Business Intelligence in my blog Library.