Computer/Embedded Technology

The importance of automation and data strategy in future-proofing cloud adoption

28 September 2022 Computer/Embedded Technology

Cloud computing is one of the key catalysts of the Fourth Industrial Revolution (4IR). It has single-handedly accelerated business efficiency through its ability to drive contingency, scalability, almost real-time data availability, and a reduction in on-site skills required to manage complex environments.

For Africa, the cloud provides the means for organisations across the continent to embrace automation and develop cloud strategies that will not only improve the efficiency and competitiveness, but also future-proof growth prospects. However, some of the biggest challenges have been inferior, or a lack of, infrastructure such as hardware. This is coupled with both the global influence such as the shortage of semiconductor chips, and a massive skills shortage in data sciences.

Overcoming obstacles

In a connected world, cloud computing provides a compelling answer to the infrastructure and skills barriers that have hampered business development. As with any revolution, there is a natural resistance to change. Cloud computing is expensive and many question the safety of one’s data. Yet, cloud providers are trusted enough to handle one’s banking and personal data, so why is there resistance to moving business data assets into the cloud?

The secret to successful cloud computing, which yields a faster return on investments, is two-fold.

Firstly, the use case for cloud needs to be expanded and often redefined. If, for example, cloud adoption was seen as merely a cloud-based database, the benefits would be limited to elements like improved hardware performance, automated redundancy, improved disaster recovery, and protection against hackers and ransomware.

Cloud adoption, when coupled with a data strategy, dramatically grows the value of the data assets, and delivers tremendous value to businesses. A data strategy that aims to democratise data within all levels of the organisation as well as outside, has shown the best return on investment.

Unpacking the data strategy

A data strategy is a business plan for data. Data strategies define the roles of people, process, and data with the aim of supporting business decisions and insights. More importantly, a data strategy should be aligned to the vision and mission statements of the business.

Data warehouses and data lakes are important considerations in leveraging the best value from data assets. Unfortunately, both have suffered from a negative perception due to the high number of failed implementations.

The primary driver behind these failures is either the lack of a data strategy or a data strategy that is too rigid, aligned to a particular technology or methodology, or is aimed at IT governance rather than business. It is vitally important that a data strategy is technology agnostic, and is representative of the company’s future growth and direction.

Introducing automation

The second element of successful cloud computing is automation. Data warehouses and data lakes would typically take months to set up correctly and often the focus would be on one area of the business. This limits the return on investment. Of larger concern is the inherent skills shortage that plagues the data sciences. We simply cannot keep up with the changing demands and direction in a timeframe that brings value to business.

Automation tools allow us to onboard data from almost any source through a powerful replication tool. The replicate tool has a zero-footprint which mirrors the data in real-time from a source without overhead or impact on the system. It is technology-agnostic, which removes the typical limitations of a single vendor technology. This is a large advantage of the cloud, as we can bring a variety of datasets into the cloud at a minimal cost. In the data sciences, change data capture – understanding what changed – represents the most crucial and difficult of the skillsets .

This is handled through the replicate tool. Automation takes this a step further and builds this data into a data lake or data warehouse automatically, allowing for seamless integration and management of data into usable information assets. As automation removes human bias, these structures do not become obsolete.

Through automation, this information is digested into functional business-ready data marts and enriched through a data catalogue for the business user, data scientist, or data analyst to consume.

Business needs

This is all done while allowing the data environment to be scalable, in line with the business needs, and is agnostic of any technology, allowing for growth into the future.

Cloud computing, when coupled with a comprehensive data strategy and automation tools, eliminates the traditional barriers to entry, reduces costs, and multiplies the return on investment. The result is an agile business that can respond with intuition to any macro, medium, or micro challenge or opportunity to become a truly global player.

By using the cloud and data analysis tools, real-time actionable insights to key decision-makers can be presented across the business to improve operations, drive efficiency, and boost the bottom line. This is how one future-proofs an organisation’s competitiveness and growth. African businesses would therefore do well to accelerate their cloud strategies.

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