IBM has enhanced the Watson Data platform, offering new capabilities with extensive data developments to make analysis easier for developers.
The Watson Data Platform is now equipped with data cataloguing and data refining, enabling the bringing together of datasets that live in different formats on the cloud – be it data in existing systems or third party sources. The new offerings allow the application of machine learning to process and cleanse this data so it can be ingested for AI applications.
The new data offerings aim to make it easier for developers and data scientists to analyze and prepare enterprise data for AI applications, regardless of its structure or where it resides. Not only do the new features give customers the ability to create more widespread better quality data sets, but data visibility and security is also improved allowing users to easily connect and share data across public and private cloud environments.
New capabilities make data analysis easier for developer
Security has also been boosted with the expansion to the Watson Data platform as metadata can be pulled from Data Catalog and Data Refinery, to tag and help enforce data governance policies. This enables teams to more easily identify risks when sharing data, and ensure that sensitive data stays secure.
In addition to this, IBM also announced the general availability of Analytics Engine to separate the storage of data from the information it holds, allowing it to be analyzed and fed into apps at much greater speeds. As a result, developers and data scientists can more easily share and build with large datasets.
The slew of upgrades to the Watson Data Platform come at an apt time, with AI functionality emerging as a must-have for applications. In fact, according to IDC, 75% of developers will build AI functionality into their apps by 2018.
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Derek Schoettle, General Manager, IBM Watson Data Platform said: “The key to AI starts with a strong data foundation, which turns the volume and velocity of incoming data from a challenge into an asset.
“For companies to innovate and compete with AI, they need a way to grasp and organize data coming in from every source, and to use this complete index of data as the backbone of every decision and initiative.”
However, Watson Data Platform does come with some challenges. For example, the problem of easily understanding complex data that is housed in different places that needs to be securely and continuously consumed to power applications.
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As well as improving the Data Platform, IBM has also updated its Unified Governance platform. These bring greater visibility and management of clients’ global data, including new capabilities that help to better prepare for impending data protection regulations such as GDPR.
