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West Africa’s interest in adopting AI- and ML-powered technologies has reshaped the relationship between businesses and data. As more and more companies use data and analytics to improve their commercial performance and inform their decision-making, combined with increased investments in IT and digital infrastructure, more data becomes available to them. For some, data will become the dominant business driver.
In light of this, businesses in the region need to revamp their data management capabilities. There are challenges to face, but with the right resources and an understanding of how data can ultimately be a corporate asset and deliver significant value, businesses can take a step towards real transformation and eventually realise their AI/ML ambitions.
Quality over quantity and other requirements
Yes, it is indeed possible to have ‘too much data’. In many cases, accumulated data can prove to be more of a liability than an asset. It is also possible to lose sight of how much data there actually is. As organisations’ IT operations grow and teams deploy multiple monitoring tools to help understand their infrastructure, applications, and networks, the accumulated data and resulting storage costs can compromise the organisation’s return on investment.
Furthermore, gathering data without a clear goal in mind for it, backed by sufficient data management and governance procedures, can lead to several challenges. For example:
- The data can be too much to handle: Large volumes of data spread across thousands of databases, each containing millions of tables and columns, can make it difficult for users to find, access, and use the information they need.
- The data isn’t of adequate quality: Actionable data needs to be complete, accurate, and well-understood, especially when it comes to data being used to train AI models.
- Data can be siloed throughout the organisation. An organisation’s data landscape may consist of multiple stores across business workflows, processes, and units, and integrating it can be time-consuming and expensive.
Additionally, organisations also have to deal with data security and compliance risks, putting themselves and their customers at risk should regulations not be adhered to or if the data is not adequately protected against breaches and unauthorised access. The result? Too much data that is siloed and of varying quality can negatively impact business performance, profitability, and security.
What it means to be a data-driven enterprise
Simply put, the ability to manage data enables businesses to scale and adapt to changing organisational needs and market trends, helping them provide information to the right people and the right time while delivering actionable insights. In an IT-driven environment, businesses need to align their database strategy to their application strategy, a process that accounts for all variables ranging from infrastructure (on-premise, public cloud, etc.) to architecture (containers, databases, and data ingestion and preparation tools).
Consider the implications of data management for an industry like financial services, which is moving quickly to embrace new technologies like AI and analytics while gaining greater insight into their customers. As institutions and service providers gather data from sources – mobile apps, ATMs, website portals, and physical branches – they can build reliable and actionable representations of their customers, effectively getting to know them better (within the confines of privacy and data handling regulations). In doing so, providers can enhance their customer services and marketing systems, enable omnichannel and personalised communication, and leverage that customer data in other business units such as product development and market research.
But this is just one industry example. Effective data management represents a net positive for all industries. For many organisations, especially those looking to embrace AI, the starting point is using platforms that can handle key functions and, importantly, centralise them.
Having the right eth-OS
One of the ways that businesses in West Africa can centralise and unify their IT infrastructure is through their operating system (OS). At a time when infrastructure is distributed and made up of multiple different cloud environments, the OS can serve as the glue between them by providing a framework for efficient data storage, organisation, and access.
For example, an enterprise solution like Red Hat Enterprise Linux includes several popular data servers with versions delivered as application streams. This enables increased flexibility without impacting the underlying platform. At the same time, RHEL as a platform provides consistency across the application experience, regardless of the environment it’s deployed in, and can help meet growing data-centred demands by quickly processing large volumes of it.
These platforms also open the door to AI/ML-enabled applications. Algorithms are only as good as the data that’s available to train them. With sorted, high-quality data, organisations can build and deploy applications that are compliant, competitive, secure, and capable of fulfilling essential outcomes.
Data is incredibly valuable if you treat it well. With the right platforms and a sound management strategy, businesses in West Africa can extract maximum value while laying the groundwork for the next generation of applications.
By Oluwafiropo Tobi Ogundare, Regional Sales Lead for West Africa & Mauritius at Red Hat
