Why the Potential of Big Data is Yet to be Realized in a Tech Market Ripe for Innovation

Big data may be a term that’s far from new across a rapidly evolving tech market in the wake of Covid-19 infused digital transformation, but its potential is still in the process of being fully realized by companies looking to innovate beyond their growing range of competitors in an increasingly congested industry.

With this in mind, it’s clear that businesses of all sizes should seek to embrace big data in a more comprehensive manner to accommodate a paradigm shift started by the pandemic. This requires an operational level reassessment.

Unlocking the potential of big data can be a great asset to organizations, and can help decision-makers to understand how to tackle challenges and exploit opportunities unique to the tech sector in a way that can add value for organizations and customers alike.

Developing the analytical insights of tomorrow

High velocity, volume, and variety are key factors behind the successful use of big data and big data analytics, which generally leans heavily on the creation, storage, and use of such data. Contextually speaking, this gradual increase in the relevance of information management has turned business attention towards new sources of data online.

The World Wide Web has quickly become a place that represents the main source of information for firms that, in response, have created many information systems, models, and ‘machines’ to capitalize on its potential.

The availability of information has facilitated the development of new procedures for big data analytics. Intelligence models have been adapted to deliver greater relevance to the web dimension and customer experience models – this has been an important development in an era that’s been punctuated by the Covid-19 pandemic.

In the tech market, predictive analytics should be useful for developing insights into both consumers’ and users’ behavior. Big data analytics can support decision-makers by helping them to understand current and future customer needs, as well as market demand and emerging trends.

With this in mind, one of the key success factors in product innovation processes with big data is related to the acceleration of the innovation process, customer connections, and the development of an innovation ecosystem. Furthermore, big data analytics can help firms to accelerate the pace of new product innovation processes whilst protecting the costs associated with introducing new products to the market.

As data shows, the development of new big data and machine learning technologies can help to bring greater levels of value into a tech industry that’s naturally more ripe for innovation than more traditional sectors. The adoption of more cutting-edge data innovations can help to create a more successful trajectory for businesses over a long-term cycle.

Emerging trends in big data are pushing businesses towards more in-depth investigations of new approaches based on business analytics, predictive analysis, and big data management models in a bid to support innovation processes.

Bridging the innovation gap

Despite the potential for the growth of big data solutions within the tech market being high, research and innovation in big data within the technology and communications sector has shrunk in 2021.

Recent figures suggest that the number of big data patent applications in the industry stood at 2,453 over three months ending in October 2021 – this is down significantly from the 3,864 recorded over the same period in 2020.

Furthermore, figures for patent grants related to big data followed a similar pattern to filings, falling from 3,814 in the three months ending October 2020, to 2,118 over the same period in 2021.

These figures, which track patent filings and the delivery of grants from official offices around the world, use textual analysis and official patent classifications to source data. They point to a slowdown in 2021 which could be down to a number of external issues – particularly due to the disruption caused by the Covid-19 pandemic in the year prior.

The widespread market optimism that companies enjoyed as tech firms recovered from the pandemic quickly may have led to a short-term acceleration of patents and grants, whilst the wider economic downturn in the second half of 2021 may have also been a factor.

What this means for tech firms, however, is that the development of big data solutions may be a high potential market with lower levels of competition than firms may have initially expected.

The figures are compiled by GlobalData, who track patent filings and grants from official offices around the world. Using textual analysis, as well as official patent classifications, these patents are grouped into key thematic areas, and linked to key companies across various industries.

Rapid growth forecasted

Significantly, as more tech firms continue to find their feet in a market that’s still adapting to life in a post-Covid-19 landscape, it’s clear that there is plenty of room to capitalize on new opportunities.

The big data market based on business function is segmented into finance, marketing, sales, HR, and operations. In terms of operations alone, this particular segment is expected to grow at a rapid pace over the coming years. This is down to big data helping to improve the performance of order picking and stock-taking processes when it comes to warehouse management – bringing much-needed accuracy and efficiency across the board. For tech companies looking to innovate their way to establishing themselves as market leaders, there’s plenty of room to market products.

Based on organization size, larger enterprises can use big data to make sense of the huge volume of information that’s generated across an extremely large client base. For big businesses, data can play a major role in evaluating the overall performance of organizations in real-time, and from multiple sources. For instance, making sense of the vast data produced on social media feeds, or sensors, or cameras can be well processed in a way that preserves its relation to other data and sequence in time.

Building analytical frameworks for the metaverse

Another factor that’s likely to increase the adoption of big data frameworks is the hotly anticipated arrival of the metaverse. Although it’s still many years away from becoming a reality for consumers everywhere, the metaverse is likely to be the next major catalyst for growth throughout the industry.

“It is likely that ‘the tide will raise all boats’ and Facebook’s actions have allowed many companies to discover new products or sales channels,” said Maxim Manturov, head of investment advice for Freedom Finance Europe.

“For the most part, the strong hype around other companies was due to their size, given that FB is a tech giant, then for smaller companies like Roblox or Unity, the metaverse creates more accelerated growth opportunities, which was momentarily reflected in the price and which is why there was such interest from investors.”

As the furor surrounding the metaverse intensifies, an emerging trend will see more firms seek to take on a competitive advantage in transforming through the capture and use of data. Many companies are already discovering ways to leverage data creatively to help transform their businesses, and more businesses will certainly emerge delivering Data as a Service, Analytics as a Service, and Dashboarding products.

In the high stakes game of evolving into an unpredictable and new industry like the metaverse, data will be seen as more of an asset for businesses, in a similar way as ROI is valued as a key metric today.

This will pave the way for greater industry growth and the opportunities are certainly far-reaching for businesses looking to move quickly to deliver innovative solutions for a tech market that’s ripe for the introduction of advanced big data solutions.