How augmented analytics is turning big data into smart data

Smart data is generated by filtering out the noise from big data that's generated by media, business transactions, Internet of Things (IoT), and data exhausts from online activity. Smart data can uncover valuable commercial insights, by improving the efficiency and effectiveness of data analytics.

Furthermore, vast amounts of unstructured big data can be converted into smart data using enhanced data analytics tools that utilise artificial intelligence (AI) and machine learning (ML) algorithms.

Advancements in data processing tools and the adoption of next-generation technologies – such as augmented analytics used to extract insights from big data – are expected to drive the smart data market toward $31.5 billion by 2022.

Augmented analytics market development

Augmented analytics automates data insights gathering 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 AI and ML-powered data analytics tools to generate actionable insights from open data,” said Naga Avinash, research analyst at Frost & Sullivan.

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 worldwide market study uncovered key market developments, technologies used to convert big data to smart data, government programs, and the IT organizations applying data analytics. It also found use cases for smart data applications.

“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.

Outlook for augmented analytics application growth

As an example of other application scenarios, various governments have already begun to use data analytics on ‘open data' sets to solve issues related to smart city and municipal 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, analyse data, and create customized reports and visualisations
• Leveraging a data monetisation 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, driven by enterprise CIOs and CTOs
• 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 digital transformation talent shortage and setting clear investment and data strategy goals