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Augmented Analytics Expected Drive Smart Data Market to $31B

March 12, 2019

Advancements in data processing tools and adoption of next-generation technologies such as augmented analytics to extract insights from Big Data are expected to drive the Smart Data market toward $31.5 billion by 2022. Augmented analytics automates data insights and provides clearer information, which is not possible with traditional analysis tools. Companies such as Datameer, Xcalar, Incorta, and Bottlenose are already focusing on developing end-to-end smart data analytics solutions to obtain valuable insights from Big Data.

"Markets such as the US, the UK, India, and Dubai have rolled out several initiatives to use Artificial Intelligence (AI) and machine learning-powered data analytics tools to generate actionable insights from open data,” said Naga Avinash, Research Analyst, TechVision. "Smart Data will help businesses reduce the risk of data loss and improve a range of activities such as operations, product development, predictive maintenance, customer experience, and innovation."

Frost & Sullivan’s recent analysis, Turning Big Data to Smart Data: Emerging Opportunities, highlights key market developments, technologies used to convert big data to smart data, government programs, and the companies applying data analytics. It also presents use cases and analyst viewpoints on smart data.

"The evolution of advanced data analytics tools and self-service analytics endows business users instead of just data scientists with the ability to conduct analyses," noted Avinash. "Technology developers can ensure much wider adoption of their solutions by offering in-built security mechanisms that can block attackers in real time. They could also develop new business models such as shared data economy and even sell data-based products or utilities."

Various governments have already begun to use data analytics on open data to solve issues related to smart city and water crises.

Other important growth opportunities for Smart Data solution providers include:

Employing augmented analytics and self-service data analytics tools, as they enable any business user to make queries, analyze data, and create customized reports and visualizations.

Leveraging a data monetization approach, as it allows businesses to utilize and bring value at every point in the data value chain.

Adding new data analytics services to existing offerings.

Partnering with innovative Smart Data solutions providers (emerging startups) across the world. This will help companies enhance their implementation capabilities by leveraging open-source Smart Data solutions focused on enterprise data management and analytics.

Collaborating with the government to address the issue of talent shortage and setting clear investment and data strategy goals.

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