According to McKinsey Africa is the World’s Next Big Growth Market, despite misperceptions that the continent lags in the technology area. In fact, the continent has become an eager adopter and innovator in all things digital, and mobile in particular. There are already 122 million active users of mobile financial services on the continent.
McKinsey notes that the number of smartphone connections was forecast to double from 315 million in 2015 to 636 million in 2022 – twice the projected number in North America and not far from the total in Europe. Over the same period, mobile data traffic across Africa is expected to increase sevenfold.
In short, there is very good reason for saying that Africa is open for business and actively seeking technology success enablers to achieve its true growth potential.
Data has clearly emerged as the digital gold on which corporate success is built. Modern companies increasingly rely on data to provide evidence-based insights that can be used to streamline business processes, increase operational efficiencies, create innovative products and services, and identify new competitors and trends.
However, an increasingly complex global business environment, a flood of new technologies (including the surging popularity of cloud-based applications), the shift to enterprise mobility and the need for real-time information to support business decision-making are all challenging IT departments. The volumes of data are huge and growing, and they come from so many different directions, that IT needs help in integrating the organisation’s data pipeline in order to manage it better, more cost-effectively and, crucially, more rapidly.
Before investing in a data integration solution, companies need to ensure that it will support both current and future requirements while still being cost-effective to implement and maintain. The following are key requirements for a future-proof integration platform:
Support for any combination of on-premise and cloud integration scenarios – today, most organisations use a variety of cloud-based systems, often procured on short-term contracts, and frequently switch from one supplier to another.
Manual coding for data integration is labour intensive and difficult to maintain. So, to truly future proof your data pipeline companies must consider automated data warehouse/lake creation tools that massively reduce the total cost of ownership of the data pipeline through automation, whilst also making it easier and more cost-effective to manage frequent change.
Make sure your data integration solution is optimised for connecting your new cloud data source environments with your other systems, services and databases, no matter where they are located.
Real-time data availability
Business data is most valuable when it is captured, analysed, and actioned in real time. The volume and speed of business data is constantly growing. As a result, managing all this data a difficult challenge. So, when looking to future proofing your investment in real-time data integration always consider a tool that will empower you to accelerate data replication, ingestion, and streaming, across a wide variety of heterogeneous databases, data warehouses, and big data platforms.
Used by hundreds of enterprises worldwide, data replication moves your data easily, securely, and efficiently with minimal operational impact. Replication lets you to load data efficiently and quickly to operational data stores/warehouses; create copies of production endpoints and distribute data across endpoints.
It is designed to scale and support large scale enterprise data replication scenarios with a scalable multi-server, multi-task, and multi-threaded architecture.
Automating the creation of data warehouses
Traditional methods of designing, developing, and implementing data warehouses require large time and resource investments. The extract, transform and load (ETL) stand-up development effort alone – a multi-month, error-prone with preparation times of up to 80% and expertise from specialised developers – often means your data model is out of date before your business intelligence project even starts.
Also, the result of a traditional data warehouse design, development, and implementation process is often a system that cannot adapt to continually changing business requirements. Modifying your data warehouse diverts skilled resources from your more innovation-related projects. Consequently, your business ends up with your data warehouse becoming a bottleneck as much as an enabler of analytics.
Modern data warehousing software allows you to automate these traditionally manual, repetitive tasks by enabling you to design, develop, test and deploy operations, whilst also delivering impact analysis and change management capabilities. The latest future-proof toolsets also automatically generate the task statements, data warehouse structures, and documentation your team will need to execute projects efficiently while tracking data lineage and ensuring integrity.
Using automation instead of man hours, your IT teams can respond fast – in days – to new business requests, providing accurate time, cost, and resource estimates.
A key success lever would be to allow for automated Data Lake projects. The best tools leverage the creation of automated data lake projects that feed your data pipelines and create analytics-ready data sets. By automating data ingestion, schema creation, and continual updates, organisations realise faster time-to-value from their existing data lake investments.
Data warehousing software should also enable easy data structuring and transformation, with an intuitive and guided user interface to help you build, model, and execute data lake pipelines.
