By Abed Khooli
Oil has been a major player in the economy (and politics) in MENA for many years. With alternative energy sources, smart power grids and decreasing revenues, raw data is emerging as a potential replacement of crude oil. To extract value from raw data technical skills are required, yet data literacy in the MENA region is still making baby steps in most countries. To start tackling this issue, two immediate steps are essential: raising awareness and building capacity.
Extracting value from data has always been around but it was limited to reporting or retroactive analysis in major enterprises and some government agencies. With the abundance of data, advances in technical infrastructure and analytics as well as the low cost of relevant products and services, deriving insights from data has become easier, cheaper and faster. Not only 'after-the-fact' analysis are possible, but predictive analytics and instantaneous analysis of streaming data are now possible.
The region is witnessing a growing trend in the interest in data as a driving force for development in different areas and sectors. However, the official adoption is still relatively slow as decision makers need to appreciate the data potential and see real impact, but nothing is expected if the eco-system is not ready. To break this vicious circle, work should be done at all levels: awareness and publicity, technical capacity building, technical, business and legal infrastructure in addition to data availability.
Capacity building in data science for development was a key action item in the Data Driven Innovation in MENA project. Having surveyed the region for potential, needs, readiness and available resources, we designed a training course of two parts: foundations of data science and applied data science with special focus on entrepreneurship and development. The course will equip data professionals with the skills needed for operation optimization or new services in existing enterprises and to start a data driven entrepreneurship. Both training courses are planned to be adapted as elective courses at local universities.
In the spirit of openness and knowledge sharing, training material will be open to the public. Datasets will be available as open data as well. The first professional training is expected to start in early November, 2016 in Palestine.
As with crude oil, raw data is expected to be replaced with smart data. Internet of Things(IoT) devices are exdpected to generate, manage and maintain most of the data in the future. Data professionals need to keep their skills up to date to outsmart what they design and develop.