October 2018 Issue
Managing data is one of the biggest challenges companies face. Businesses are producing and storing data in huge volumes. According to research group IDC, the world will be creating 163 zettabytes of data a year by 2025. But this volume of data also represents an important chance for companies to leverage new business opportunities. However, if they are to truly benefit, companies must make informed strategic choices about data collection, storage and utilisation. In order to do this adequately, they must establish solid data management principles.
It is vital that companies ensure that their data is safely stored and well protected. In the face of increasing criminal behaviour, great strides are being made in data security. According to ESG Research, 28 percent of enterprise organisations are collecting, processing and analysing substantially more security data than they did two years ago. A further 49 percent of firms are collecting, processing and analysing somewhat more data than they did in the past.
However, companies have more work to do. Measures such as identifying sensitive data and limiting access to it, improving the frequency of data back-ups and augmenting security measures would be prudent, particularly as data breaches are common. The number of significant breaches at US businesses, government agencies and other organisations exceeded 1300 in 2017; in 2005 there were fewer than 200, according to the Identity Theft Resource Centre.
“The biggest data-related challenges we face are how to achieve data security and realise data privacy protection,” says Great Gu, a cyber security, risk management and IT governance expert at Amgen Biotechnology Company. “So companies need to pay more attention to finding the critical and sensitive data in-house and implement appropriate mechanisms to protect that data in order to prevent, detect and respond to any incidents targeting their valuable data.”
Though cyber security is critically important, it is merely a constituent part of the wider data management framework which companies should have in place. A sound data management strategy should provide a relevant framework and the architecture required to support it. Armed with a solid strategy, companies can develop integration strategies, implement new technologies and draw up effective data policies.
Data is one of the most valuable resources available to companies. Neglecting data management can result in loss of that data, which can have disastrous consequences. According to the National Archives & Records Administration, in 2015, 93 percent of companies that lost their data centre for 10 days or more due to a disaster filed for bankruptcy within one year.
Companies need adequate capacity and equipment suitable for storing huge quantities of data. Regularly upgrading technology, including storage hardware and software, can be complex and expensive. Companies should invest in new software which will enable them to locate, move and delete data before retiring old technology for new systems. Identifying new storage technologies and management tools before existing infrastructure becomes obsolete may be inconvenient, but it allows companies to get ahead of the game.
The value of a company’s data is intrinsically linked to both the quality of the data and the data source. Data entry errors, conclusion errors and processing inefficiencies are all risks companies may face in the absence of a strong data management plan and strategy. “The best approach to get good quality data is to first set up a data repository, which allows you to better understand your data as early as possible,” explains Mr Gu. “Knowing your data includes the whole life cycle of data creation, data collection, data use, data sharing, data archiving and data destruction. You can then extract good quality data to aid your business goals. Good quality data enables business growth and allows companies to remain compliant.”
Data management is evolving. As technology becomes more prevalent, data management will likely become more targeted, predictive and automated. Big Data, artificial intelligence and other specialised technologies will become more influential. While companies have strategies to cope with existing data management challenges, they must remain agile and be able to adapt to new, emerging technologies, such as deep learning, machine learning and natural language processing. If companies are to continue to benefit from their data and utilise it to differentiate themselves from their competition, they need to be able to tap into analytics and operational capabilities.
“Companies should become more vigilant about data evolving from traditional business to digital business,” says Mr Gu. “These changes create a more complicated environment in which to build a data management lifecycle. Completely data-driven businesses create revenue out of data. Such companies must ensure their processes remain relevant to the business they hold. In other words, they must take action to recognise, analyse, use and share all of the data which drives their business.”
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