While costs are rising, they are also being mitigated by greater efficiencies in the hyperconvergence and virtualization of existing infrastructure. By adopting modern data platforms and progressively decommissioning the old legacy systems, companies gain a significant cost reduction in their IT infrastructure.
The great accessibility of data centricity – by employees, suppliers, customers and others – also presents the challenge of building complex security and privacy requirements, cited as the second greatest challenge (27% of respondents). The data-centric organization must not only deepen its cyber-security offensive and defensive measures, but it must also spread the net to cover a diverse set of players.
A key operational challenge of data centricity is the complexity of connecting and integrating diverse data systems (the third greatest challenge, cited by 25% of respondents) – a key contributor to the cost of technology.
It goes beyond simple cost metrics. To develop true data centricity, it is necessary to aggregate and curate data from thousands of enterprise information systems, suppliers, customers, markets, and regulators, as well as internal control systems, IoT devices and sensor networks.
Furthermore, an increasing number of organizations are developing data strategies that offer opportunities for new revenue-generating operating models including those where they are commercializing their data. One of the emerging opportunities in this area are those where data ecosystems are created across organizations to sell curated data sets and models or insights that have been trained using an ecosystem of data.
The technology: managing the data deluge
This scale will demand a reset in the fundamentals of how data is managed. “Many companies remain in the experimental stage with their data,” says Vaibhav Jajoo, Head of Data Engineering at DoorDash. “They are not prepared for the scale of what is coming at them to convert data into actionable insights.”
Data is only valuable when it is transformed into insights and drives informed decision-making. Given the expanded user base of data, data strategists should place a strong priority on democratizing data – making it more user-friendly and accessible through a wide range of devices or through citizen developers.
Finally, there are emerging technologies that are focused on rationalizing flows of data and improving its management. Software defined storage (SDS), which decouples storage resources for the underlying hardware platform, can increase efficiency and scalability. Flash array, which is now becoming more affordable, can provide the speed and volume to manage data at scale. These are only a selection of technology-based solutions designed to enable data management.