Intelligent CIO Africa Issue 23 | Page 36

business ‘‘ TALKING //////////////////////////////////////////////////////////////////// warehouse appliances require massive throughput for mainstream, file-based workloads and cloud-native, object-based applications • True scale-out design. The power of data lake is its native, scale-out architecture, which allows batch jobs to scale limitlessly as software – not the user – manages resiliency and performance • Multi-dimensional performance. Data is unpredictable and can arrive at any speed—therefore, organisations need a platform that can process any data type with any access pattern • Massively parallel. Within the computing industry, there has been a drastic shift from serial to parallel technologies, built to mimic the human brain, and storage must keep pace A true data hub must have all four qualities as all are essential to unifying data. A data hub may have other features, like snapshots and replication, but if any of the four features are missing from a storage platform, it isn’t built for today’s challenges and tomorrow’s possibilities. For example, if a storage system delivers high throughput file and is natively scale- out but needs another system with S3 object support for cloud-native workloads, then the unification of data is broken and the velocity of data is crippled. It is not a data hub. For organisations that want to keep data stored, a data hub does not replace data warehouses or data lakes. For those looking to unify and share their data across teams and applications, a data hub identifies the key strengths of each silo, integrates their unique features and provides a single unified platform for business. Think of storage like a bank, or an investment. We put our money in banks, or in the stock market because we want our money to work for us. Modern organisations need to do the same with data and they should speak to their preferred vendors to see how they can help. n Driving the effective use and adoption of information Adriaan Hubinger, Engagement Manager: Data, Information and Analytics at Decision Inc, examines how to effectively adopt data inside the business. J ust consider how much data is available to decision-makers. In 2015, 12 zetabytes (1ZB is the equivalent of about one trillion gigabytes) of data was created worldwide. And by 2025, it is forecast to increase to a staggering 163 zetabytes. Clearly, companies need a carefully constructed adoption strategy to capture, manage and understand the information they have at their disposal. Adding to the complexity of this challenge is the fact that many existing business intelligence (BI) tools are not being used to their full capacity. There is a willingness to adopt them, but there is a lack of understanding how to integrate BI across the organisation for all employees to benefit from it. Even though the financial sector has received a lot of attention when it comes to data analysis and information strategy adoption, 36 INTELLIGENTCIO the reality is that any sector can benefit from this. In the current difficult economic environment, businesses are trying to keep costs low while still being competitive and maximising the technological solutions they have at their disposal. To truly achieve business value from BI and other analytics tools, companies must extract value out of the information they have at hand. This is not only a South African challenge. Local companies are on par with their international counterparts when it comes to adoption rates. Some statistics show that insurance and technology lead all other sectors in terms of BI adoption with 40% of organisations having 41% or greater penetration of BI. It all boils down to making solutions accessible and customisable to the specific needs of the business. Change management Moving beyond the willingness to change and having the capabilities to analyse data more effectively, another component that needs to be considered is change management. It has become too easy to migrate BI and data analytics solutions without taking into account the people who need to use it. Granted, costing is always a consideration as organisations want to run as optimally as possible. Even though it might be too expensive to convert the entire organisation to a comprehensive BI platform, there are options to embrace a more modular approach. This is not only cost-effective but enables the organisation to train sections of people with the solution and gauge its impact on the organisation. African expansion Looking at the rest of Africa, there are significant opportunities for businesses to extract additional value from insights across the continent. Data structures differ in each country and these are not always in the most accessible formats. By getting the data into a usable format, businesses can gain a greater understanding of the needs of their target markets. Data needs to be accessible in its simplest form for decision-makers to gain actionable insights. Currently, it is about transforming innovative technologies like Machine Learning and Artificial Intelligence into relevant solutions that can deliver BI value for the organisation. The opportunities are there as is the willingness. Now it is a matter of combining data with tools and ensuring employees can unlock the insights inside it. n www.intelligentcio.com