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Bessere Infrastrukturen dank Big Data
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Artificial Intelligence and Machine Learning in data analytics and business applications
Artificial Intelligence and the sub-set of it which is machine learning are hot. It’s been impossible to attend an IT conference in the last year or so without encountering a dead human genius reincarnated as a software system or a robot.
What lies beyond the hype? In the data management field, experts tell us there are many basic things organisations can do to get more business value from their data before they over-commit to experimenting with machine learning.
And yet, as the articles in this e-guide show, there is real worth in AI/ML, and it might open up new roles and more business-central activities for IT professionals. This is suggested in the lead article here, which explores the impact AI/ML is having in the Law, and suggests parallels in other sectors. However, the potential for AI to take away, but fail to replace jobs should not be ignored, and needs to be understood and managed.
A recent McKinsey study suggests adoption of AI/ML is fairly modest outside the technology sector itself, but does indicate significant investment. And there does seem to be a concatenation of technologies – blockchain, IoT, machine learning that might, together, transform the business applications side of IT more broadly.
SAP and IBM are among the suppliers investing in artificial intelligence and machine learning. The latter is showcasing some of its Watson AI capability at Wimbledon this summer. But all the enterprise software giants are pitching in and one of the articles in this e-guide counsels against too hasty adoption of a “black box” approach”.
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Big Data and Analytics Applied to Oil and Gas
Informational value is the most important commodity throughout the oil and gas industry – from upstream operators to pipelines that deliver products to world markets.
Newly embedded devices and sensors make it easier to collect data at an ever-increasing rate; while cloud storage technologies make it simpler to store the data. However, real value is created from data when informational context and associations are made inside and outside of an organisation.
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CW ANZ: Taming the data beast
Software-defined storage (SDS), which promises greater transparency and control over data, is an increasingly important tool in the enterprise technology armoury. In this issue of CW ANZ, we look at how Australian enterprises are turning to SDS to improve data management and direct data to different tiers of storage or to applications.
Also in this issue:
Analysts query Australian government’s IBM deal after previous tech problems
Industry analysts and experts have called into question the wisdom of the Australian government’s A$1bn IT deal with IBM, with one claiming it should have used a range of suppliers instead.
What machine learning practitioners can learn from data warehousing
Cloudera’s head of emerging business, Charles Zedlewski, shares lessons that machine learning practitioners can learn from their cousins in the data warehousing sector.
'Splunking' data for APAC’s enterprises
Splunk’s regional vice-president, Chern-Yue Boey, tells Aaron Tan about the company’s business strategy and how its customers are using big data analytics in security and IT operations.
