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How augmented analytics will make big data smarter

The next-generation technology will drive the smart data market, helping to automate data insights and obtain information that isn’t possible with traditional analysis tools

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Augmented analytics will allow non-data scientist users to conduct data analyses
Augmented analytics will allow non-data scientist users to conduct data analyses

Advancements in data processing tools and adoption of augmented analytics to extract insights from big data are predicted to drive the smart data market toward $31.5bn by 2022.

 

Augmented analytics automates data insights and provides clearer information, which is not possible with traditional analysis tools.

 

From big to smart data

 

According to Frost & Sullivan’s report, Turning Big Data to Smart Data: Emerging Opportunities, augmented analytics will play a “vital role” in converting big data to smart data.

 

The analyst notes that various governments have already begun to use data analytics on open data to solve issues related to smart city and water crises.

 

“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 at Frost & Sullivan’s TechVision practice.

 

“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.”

 

The report highlights key market developments, technologies used to convert big data to smart data, government programmes, and the companies applying data analytics. It also presents use cases and analyst viewpoints on smart data.

 

Companies like Datameer, Xcalar, Incorta, and Bottlenose are already focusing on developing end-to-end smart data analytics solutions to obtain valuable insights from big 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”

Other important growth opportunities for smart data solution providers identified in the report include:

  • Employing augmented analytics and self-service data analytics tools, as they enable any business user to make queries, analyse data, and create customised reports and visualisations
  • Leveraging a data monetisation approach, as it allows businesses to utilise 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 start-ups) 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.

“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,” added 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.”

 

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