Big Data and Analytics
Big Data has been on the radar for a significantly longer time than its intense implementation. Although there is no agreed-on definition, the term is often characterised by three key attributes; high volume, high velocity and high variety. Unlike statistical data compiled for specific purposes, big data is made up of byproducts founded on the principles of business and administrative systems, social networks and the internet of things. The success of Big Data projects lies not in the implementation but rather in its analysis to establish an ecosystem that drives change in the processes of an organisation. Innovations in Big Data are propelled by utmost adherence to analytics. Organisations can implement the concepts of Big Data and benefit from the analytics by learning from the best practices and adapting those that have the potential for meaningful insight.
Big Data for Efficiency
Big data and analytics solutions can improve the efficiency of assets and critical infrastructure and help organisations take a proactive approach to preventing or minimising costly outages. When assets are not functioning correctly, costs go up. Data is significant in attending to the needs of a group, individuals and even organisational assets. Management and governance are efficiently exercised by aligning consumer attributes to the
data in action. Desired business outcomes are well-arrived at through significant, consistent and elaborate methods of data analysis. Creation, duplication and interpretation of data significantly put pressure on the planned outcomes of an organisation. It’s equally important to note that, without analytics, big data can be just noise. Running analytics on a wide range of existing data creates a vivid yet clear picture of what importance big data brings to an organisation.
Achieving a high level of operational excellence can be an overwhelming challenge. Big Data and Analytics solutions can enable companies to make significant improvements by helping them address their operations as an interconnected ecosystem as opposed to a collection of isolated departments. At the foundation of any company’s ecosystem is their customer base.
The Consumer Question
Consumers are demanding more from organisations, such as better products, personalised services and heightened quality of care. Quality in service and product delivery is a key driving factor in the actualisation of a company’s financial goals. Workplace expectations are also changing as most people need to make well-informed decisions so businesses can respond immediately. In exploring the potential of Big Data, an organisation needs to portray effectiveness in delivery which is essential in fulfilling consumers’ needs.
Big Data and analytics can help companies/organisations to streamline their existing operational processes to meet ever-changing customer needs.
The Potential of Big Data
Predictions aligned to the revolving sphere of Big Data, supported by ‘intense’ research, indicate that by 2020 the growth of all data – in digital formats – is forecasted to grow by more than 40,000 Exabytes. This growth attempts to bend much focus on the technological (methods) perspectives. This is also directed by the capabilities, information management and predictive analysis. Big Data is the new data source in the outlining, achievement and improvement of the constraints which govern the operation ability and functionality of select business entities. To maintain the operation ability of planned patterns, Big Data comes forth in order to attain set objectives.
Although the effective and smart use of big data is evolving, the potential to transform the way individuals look at information is not controversial. Big data exploration is an exercise in asking new and better questions as well as an opportunity to challenge conventional thinking about the collection and production of statistics.
In some cases, big data can allow policy analysis to move beyond aggregates and look at what lies beneath to better inform policy responses. Big data may allow better measurement of the effects of financial inclusion, access to financial services and economic growth. Electronic money systems, such as M-Pesa, are growing rapidly in developing economies and with them, opportunities to measure the effects of financial inclusion on poverty reduction, gender inequality, and economic growth.
Faster insights are one of the biggest promises of big data, because key variables – for example, financial and price data – can be observed almost instantaneously. To monitor economic and financial developments and to provide early-warning signals of stability risks, timely data is essential to statistics fit for policy use.
For a predictive maintenance solution to deliver relevant results, it must be able to capture and critically analyse structured data, unstructured data, resting data and most importantly – streaming data.
Conclusions and Work Ahead
By now, many national and international statistical organisations have recognised that big data is not just a buzzword, but a potential strategic asset that requires a vision and a plan. Best practices for the building of lasting partnerships between official statistical agencies and data owners are being developed and tested, legal questions clarified, and best-use cases field-tested. Organisations learn that big data success is not about implementing one piece of technology, but about putting together an environment of people and processes that take the big data innovations forward and put them to work. Infrastructure spaces and big data sources continue to evolve and with them the possibilities, challenges, and limitations. Given the diverse skills and collaboration needed, big data projects are also an opportunity to break institutional silos.
Big data is not a static but a dynamic phenomenon, so the systems and networks generating it will continue to evolve, as well as the opportunities that big data offers, the challenges it poses and its statistical implications.