ANZ businesses will move beyond simple data analytics and will evolve to data-centric organisations, a global provider of analytic data platforms, marketing and analytic applications, said.
The 2016 Teradata ANZ Survey
revealed that 15% of companies constantly analyse data and make real-time data-based decisions; and a further 21% collect and analyse data to make business changes, though not in real-time. Only a quarter of the companies said they collect data but don’t analyse it.
Alec Gardner, GM, advanced analytics at Teradata, said: “Businesses are beginning to realise the need to move beyond simply acquiring the right technology and tools to collect and analyse data, towards a cultural shift that puts data at the centre of the business, effectively giving data a seat at the decision-making table.”
Gardner added: “Companies that use data, as opposed to instinct or guesstimates, to drive decisions, are likely to be more successful in the long-term, delivering ongoing value to customers and shareholders.”
“This value manifests as lower costs, increased customer satisfaction and revenues, and an improved bottom line. As data becomes a recognised asset, organisations may reflect its value on the balance sheet.”
Teradata predicted five key trends to emerge as more organisations realise the value of data:
Big data: from IT and beyond
- Increase in data agility. Businesses will work more with agile data warehouses, to create a balanced, decentralised framework for enabling various workloads and data types. By enabling companies to analyse data, they can improve customer experience, logistics, sales, operations, finance and human resources, among others.
- Rise in collaborative idea creation. The pooling of data and insights will give companies a better view of trends and challenges. Self-service tools allow employees to interact with data, which in turn leverages the trend towards social approaches to decision-making.
- Crucial role of disciplined testing. Disciplined testing, as well as a solid business case, is a must in order to translate data insight into actions. Disciplined testing includes consistency, accuracy, coverage, correctness, and completeness.
- Use of IoT for making predictions. Analysis of IoT data allows businesses to predict and determine the likelihood of future outcomes, trends, or events. This will help companies improve customer experience and organisational performance.
- More work for data scientists. To make the most out of data, organisations require staff with the right skills and training. According to recent Teradata Index, more organisations are realising the importance of data scientists: 10% of companies said they’re planning to hire one data scientist; 11% plans to hire an entire team of data scientists; 13% will use an external partner; and 6% will develop in-house talents.
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