FROM A DATA ANALYTICS AND BUSINESS INTELLIGENCE PERSPECTIVE , MINING ORGANISATIONS ARE UNABLE TO EFFECTIVELY LEVERAGE THE POTENTIAL OF COMPETITIVE ADVANTAGE .
INDUSTRY WATCH
The mining sector has not escaped the move toward digitalisation , but the nature of the industry means that it faces multiple challenges when it comes to managing , protecting and storing data . One of the central factors for these challenges is the decentralised nature of mining operations , as well as the tendency towards frequent mergers and acquisitions . A lack of consolidated data and centralised data management leaves data vulnerable .
Aside from causing mines to fall foul of the many regulations and compliance requirements , there is also the safety element . Mining organisations need to centralise their data and data management and adopt a holistic strategy as well as an appropriate data management solution to prevent unnecessary loss of life and unlock the power of their data for competitive advantage .
Mining companies typically operate from a head office , often in another country , as well as at multiple mine sites which are in remote areas . This means that head office and the various mines frequently have disparate IT systems , distributed data storage and even completely different and potentially unmanaged solutions . Equipment at mines , such as that which measures temperature or gas in the shafts , is operated and controlled by the mines , while back-office IT systems like payroll are managed by head office .
These two environments do not talk to each other – and the systems between mines themselves do not either – creating a web of disconnected solutions . This means there are no centralised policies or control , no consolidated data governance , no holistic IT management , and many loopholes and vulnerabilities that can be exploited by those with malicious intent .
It also means from a data analytics and business intelligence perspective ; mining organisations are unable to effectively leverage the potential of competitive advantage .
With multiple disparate data sources and massive data sprawl it becomes a challenge to implement an effective and manageable cyber security framework . This is complicated by systems and solutions outside of the control of head office , many of which do not interoperate .
FROM A DATA ANALYTICS AND BUSINESS INTELLIGENCE PERSPECTIVE , MINING ORGANISATIONS ARE UNABLE TO EFFECTIVELY LEVERAGE THE POTENTIAL OF COMPETITIVE ADVANTAGE .
In such a scenario , disaster recovery becomes impossible . In the event of ransomware or a cyberattack , data may be compromised , but more importantly , systems that are critical to safety may be taken offline , and this can affect human lives .
Aside from this , mines also have the obligation to protect the large volumes of personal information they store . It is essential to have a single , consolidated data management solution as well as consistent policies and procedures across the organisation .
Not all data is created equal and not all systems are mission critical , but without proper data management it is all but impossible to effectively prioritise and understand how to rebuild in the event of a disaster . The central management of IT assets , alongside data management and security , is crucial , and it needs to incorporate next-generation data protection solutions such as cyber deception , cyber resilience and artificial intelligence .
Having an overarching IT , compliance , risk and data management framework that covers everything in the mine , from business to remote locations , operations and more is a significant challenge , but it is also vital , not only for cybersecurity but for the safety of employees .
Hemant Harie , Group Chief Technology Officer , Gabsten Technologies
Iniel Dreyer , Managing Director , Data Management Professionals South Africa
Head office will have regular data backups , but because the mines may have limited connectivity due to their location , they may only backup once a day , and backups may not all go to the same place .
This becomes even more important in the event of an acquisition , when new systems and data need to be integrated , understood , and protected . Without it , the risk of continued data disparity and siloes grows and
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