Information Analytics

There is no shortage of attention to unlocking unstructured data as a key competitive advantage. It is a multimarket, multi-industry untapped store of significant value.

AvePoint has acquired tyGraph, developer of platform that allows organizations to organize, measure, and analyze human interactions in the workplace.

CyberRes, a Micro Focus line of business, has announced a new version of Voltage File Analysis Suite (FAS), a cloud platform that combines data discovery and data protection. Among the new features in Voltage FAS is SmartScan, a tool for intelligent sampling and dynamic tagging for petabyte scale data discovery, enabling data analysts to find the areas of higher data risk faster. 

Companies in Singapore are the most likely in the Asia Pacific to use data analytics and visualisation, cybersecurity and robotic process automation (RPA) in the next 12 months, according to a survey by global professional accounting body CPA Australia. Singapore-based businesses are already the top users of RPA in the region, with 57 per cent of local respondents saying their company deployed RPA as a business tool.

Most Australian and New Zealand healthcare organisations struggle to use data analytics to support their business objectives. This is among the findings of The State of Healthcare Analytics & Interoperability Study – Australia & New Zealand.

Data quality is still a struggle for many enterprises, and new types of data and input techniques are adding to the burden. Jonathan Grandperrin, CEO of Mindee, explains the impact of bad data and how enterprises can use deep learning and APIs as part of their “good data” strategy.

Koverse, Inc. has announced availability of Koverse Data Platform (KDP) 4.0, a security-first data platform that introduces attribute-based access controls (ABAC) to enforce Zero Trust for data, allowing users to safely work with complex and sensitive information to power the most demanding analytics, data science, and AI use cases.

Enterprise search vendor Sinequa has announced the addition of optional neural search capabilities to its Search Cloud Platform, using four deep learning language models. These models are pre-trained and ready to use in combination with Sinequa’s advanced Natural Language Processing (NLP) and semantic search for the best relevance and question-answering capability, optimized to run efficiently even at scale.

Recently developed artificial intelligence (AI) models are capable of many impressive feats, including recognising images and producing human-like language. But just because AI can perform human-like behaviours doesn’t mean it can think or understand like humans. As a researcher studying how humans understand and reason about the world, I think it’s important to emphasise the way AI systems “think” and learn is fundamentally different to how humans do – and we have a long way to go before AI can truly think like us.

New market research commissioned by IBM has revealed that global AI adoption grew steadily over the last year, to 35 percent of those surveyed in 2022, further underscoring that AI growth is poised to accelerate as it continues to mature, becoming more accessible and easier to implement.

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