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Gartner's top data and analytics predictions for 2019
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The use of analytics to improve operations is growing, and healthcare organizations are on the cusp of deriving increasing value from the data they have. Gartner, a major consulting firm, has issued a set of predictions for the implications that data and analytics will have across all industries. This post originally published on Andrew White's Gartner blog, which can be viewed here.
Predictions about data and analytics strategy
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* By 2022, 90 percent of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.

* By 2022, 30 percent of CDOs will partner with their CFO to value the organization’s information assets for improved information management and benefits.

* By 2022, more than half of major new business systems will incorporate continuous intelligence that uses real-time context data to improve decisions.

* By 2023, data literacy will become an explicit and necessary driver of business value, demonstrated by its formal inclusion in over 80 percent of data and analytics strategies and change management programs.

* By 2023, 60 percent of organizations with more than 20 data scientists will require a professional code of conduct incorporating ethical use of data and AI.
Predictions about analytics and BI solutions
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* Through 2020, 80 percent of AI projects “will remain alchemy, run by wizards whose talents will not scale in the organization." And through 2022, only 20 percent of analytic insights will deliver business outcomes.
Predictions about digital ethics, policy and governance
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* By 2021, legislation will require that 100 percent of conversational assistant applications, which use speech or text, identify themselves as being nonhuman entities.

* By 2022, 30 percent of organizations will use explainable AI models to build trust with business stakeholders, up from almost no usage today.

* By 2023, over 75 percent of large organizations will hire AI behavior forensic, privacy and customer trust specialists to reduce brand and reputation risk.
Predictions about data management solutions
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* By 2021, enterprises using a cohesive strategy incorporating data hubs, lakes and warehouses will support 30 percent more use cases than competitors.

* By 2022, 50 percent of cloud buying decisions will be based on the data assets provided by cloud service providers rather than on the product capabilities.

* By 2022, organizations utilizing active metadata to dynamically connect, optimize and automate data integration processes will reduce time to data delivery by 30 percent.

* By 2023, AI-enabled automation in data management will reduce the need for IT specialists by 20 percent.

* By 2023, 75 percent of all databases will be on a cloud platform, reducing the DBMS vendor landscape and increasing complexity for data governance and integration.
Predictions about core technologies supporting AI
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* Through 2022, only 15 percent of use cases leveraging AI techniques (such as machine learning and deep neural networks) and involving edge and IoT environments will be successful.

* Through 2022, more than 75 percent of organizations will use DNNs for use cases that could be addressed using classical ML techniques.

* Through 2023, computational resources used in AI will increase five-fold from 2018, making AI the top category of workloads driving infrastructure decisions.

* By 2023, 70 percent of AI workloads will use application containers or be built using a serverless programming model, necessitating a DevOps culture.

* By 2023, 40 percent of infrastructure and operations teams will use AI-augmented automation in large enterprises, resulting in higher IT productivity with greater agility and scalability.

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Healthcare analyticsBusiness intelligenceData managementArtificial intelligence Machine learning
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