Over the past two years, many South African corporates have accelerated their adoption of smarter, hybrid IT solutions.
But these solutions are about more than the technology being implemented. Instead, a smarter environment requires the integration of teams, code, platforms and data.
In this, the first in a series of four articles examining the ‘new’ hybrid approach that decision-makers must contend with, I explore the data layer.
Data has become the foundation on which the modern enterprise is built. Worldwide revenues in the big data market are expected to top $77 billion by the end of next year. From healthcare and banking, to mining, manufacturing and retail, every industry segment is using data to drive the decision-making process.
Global events of the past two years have highlighted just how important data capturing, processing and analysis can be to save lives, improve risk management strategies and monitor the spread of infection.
Data relevance
Providing employees with access to relevant data is crucial if a business is to succeed in today’s connected world. Whether an organisation adopts public, private or hybrid cloud solutions, finding the means to efficiently access data in real-time across systems makes for a significant competitive advantage.
It is essential to bridge data centres, branch technologies and edge computing to facilitate smooth data transition. Once this is done, automated systems can be used to analyse the data and provide business and technology leaders with relevant insights.
Data automation has become one of the most significant growth areas in the field. Organisations are turning towards more effective handling and processing of data at scale than what is possible by doing it manually.
This also leaves employees with the capacity to focus on leveraging insights for strategic use as opposed to being stuck in routine tasks.
Cost impact
Management is now under pressure to transition to hyperscalers and adopt software-as-a-service to consume services on demand. Even though this has been positioned as an affordable option to remain on-premises, the reality is that if the data is not managed, the cloud can become more expensive than traditional approaches.
Whether it is the data store, data flow, or data evolution, smarter data management must become part of standard operating procedures.
This is especially evident when organisations try to ‘lift and shift’ their data function as is to the cloud. Not every process and system needs to migrate.
If anything, the superfluous data analysis capabilities used in the cloud will make the entire environment unsustainable from a costing perspective. Development teams need to carefully consider what they need in the cloud, and what they can get away with on-premises.
Edgy stuff
Exacerbating this has been the rapid shift to remote work. Employees accessing corporate resources from home have created an increasingly complex edge infrastructure that must be managed.
Effectively, their homes have become an extension of the IT network and the corporate office.
A global survey found that one in three businesses have been hit by an online breach since the shift to remote work. Furthermore, almost a quarter of businesses have not updated their remote work security policy in more than a year.
Management must understand how data can be accessed, controlled and managed while ensuring its security. They need to think of themselves as the infamous Eye of Sauron that sees everything.
If not, gaps will start emerging in the data estate that can not only give rise to potential cyber attacks but can also bring inefficiencies into processes that need to operate as optimally as possible.
This is where service providers play a critical role in helping companies manage their data lifecycle as securely and effectively as possible.
Whether it is the data store, data flow, or data evolution, smarter data management must become part of standard operating procedures, especially when factoring in the importance of an edge computing-driven business ecosystem.
Value-based
Face it, conversations around big data, analytics and business intelligence have changed. These discussions are no longer focused on what companies can do with their data but rather about how to best capture value from their data.
As such, companies are reconsidering traditional approaches to data analytics while recognising the positive influence that artificial intelligence and machine learning can have in this regard.
Discussions must now centre less on the smorgasbord of solutions that claim to tap into the secretive insights lurking within the data. Rather, the C-suite must find ways in which the organisation can leverage technology to squeeze value from the right data.
It calls for assessing the relevant technology that makes sense for the business and how it wants to capture value.
There is little doubt that data is an essential part of the modern business. It has become the fuel, the oil, the black gold, if you will, that every successful organisation yearns for.
Companies must therefore look differently at their data and adopt different strategies to extract maximum value across a hybrid ecosystem of solutions.
A momentum shift has already occurred between the ones who embrace becoming data-driven and the ones who choose to ignore the potential that this will unlock. There is simply no going back to the way things were.
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