The amount of information Big Data actually encompasses is not just big, but astronomical. Organizations and governments increasingly employing the growing body of smart devices, sensors and cloud-based systems to collect data on their customers, clients and citizens. Big Data is increasing in volume, velocity, variety as well as varsity day in and day out. Thanks to Big Data Analytics, users are discovering new ways to learn more about their target markets and leveraging the insight to improve service delivery. Chicago, Dublin, London, New York and Singapore are shining proof of the fact that Big Data drives efficiency of operations.
Managing Open Public Sector Data Sets in the United Kingdom
The Government of the UK provides an example of how big data is being managed. The Government provides developers with open public sector data sets through Data.Gov.UK. The Government offers these sets of data to application developers, with hopes they will create innovative solutions to increase the quality of life for citizens. Diverse data sets offered, include: live traffic information, building price and cost indices, historic flood maps, statistics on alcohol, and more.
However, with this sort of open system, there is a Code of Conduct in place. In this Code of Conduct, users are encouraged to use their resources as the primary set of data in the application, cache the data over a short period of time, and report inconsistencies. In using these datasets, developers are reminded that they must cite their source and differentiate between public sector data and external data. While the Government cannot possibly monitor all of the applications being produced from their open data sets, this Code of Conduct provides a basic regulatory framework in case these data sets are used with malicious intent.
However, the desire to unleash higher levels of efficiency using Big Data raises a few concerns about the management, security and privacy of data.
How is the large volume and variety of data being managed?
Relational databases or data warehouses are not enough to manage, process and store Big Data. Large enterprises as well as savvy government bodies are utilizing innovative Big Data management platforms. These are innovative versions of traditional data warehouses, modified for integration with Big Data analytics and systems within the logical data warehousing architecture. Data classification is being used to segment Big Data into smaller bytes that can be accessed, processed and analysed quickly.
How is the privacy and security of Big Data being handled?
The privacy and security measures for Big Data are fundamentally the same as regular data, with size and volume being the only difference. It is both easy and effective for organizations to build their Big Data environment on the cloud. Cloud storage also results in data users and cloud-service providers sharing the responsibility of privacy and security.
Another good strategy to boost data privacy and security is classification and segmentation of all forms of Big Data within an organization. Such data ownership makes it easier and more manageable for organizations to implement different privacy control and security measures such as attribute-based encryption and access.