As technology has enabled digitally native consumers to access information, products and services at a faster pace, businesses need real-time data technologies to stay competitive and keep up with their customer
With the adoption of technology, more businesses are expanding rapidly in data analytics, resulting in a surge in data-driven models and the normalization of automation in operational processes.
Deb Dutta – General Manager, Asia Pacific & Japan, DataStax
How can Indian enterprises leverage real-time data to effectively and efficiently bring products to market for sustained success, despite the complexity it may bring?
With real-time data becoming a game changer, the need for businesses to have the ability to harness data for insights is no longer optional but necessary for the success of the enterprise of the future.
In fact, real-time data can unlock a range of newfound efficiencies.
According to a report by Mckinsey, by 2025, smart workflows and human-machine interactions will become the standard for business, with employees using data to optimize every aspect of their work. Automation, artificial intelligence and machine learning can work hand-in-hand with real-time data to drive seamless interactions between people and technology, and will become the standard; requiring employees to utilize data to optimize every area of work.
Despite accelerated digitization in recent years, Indian organizations are not making the most of the data available to them. MMA Global’s report indicates that in 2022, only 54 percent of Indian businesses have leveraged consumer data in their marketing efforts. Indian businesses need to go beyond capturing and storing data from applications to advanced analytics – converting their data into insights – if they want to remain competitive and deliver personalized customer experiences.
By tapping into the data streams directly as data moves, businesses can take a new approach to leveraging real-time data towards real-time intelligence and automation in any kind of operational or business environment. This provides the enterprise with the agility and optimization to detect and address operational or market challenges quickly, and have the opportunity to meet them with data-driven decisions and actions. This ultimately leads to having the insights to customize and personalize offers for the customer journey.
What are the main challenges in harnessing real-time data?
IT complexity from piecemeal architectures and silos make it difficult for the business to harness real-time data. Without effective and impactful digital transformation, switching to a real-time data model can incur unnecessary costs to the enterprise, and unintentionally create more data silos as a result. A haphazardly executed model would also produce poor and undesirable results for the business.
The challenge with real-time data lies in the fluctuation of data flows, and its unpredictable volume. And because data is flowing constantly, it is impractical to restart tasks when flaws emerge in the pipeline, causing a domino effect in the results.
An effective solution begins with maintaining the quality of the data, with every stakeholder in any function comprehending the importance of accurate data, and being meticulous about it. Automated procedures with data must also be scrutinized for quality to ensure only reliable data are used; reducing the need for data processing during the analytics stage.
In your opinion, why do you think Real-Time Data is a Business Essential in 2023 and beyond?
As technology has enabled digitally native consumers to access information, products and services at a faster pace, businesses need real-time data technologies to stay competitive and keep up with their customers. Apart from improving internal processes, real-time data also enables the enterprise to track inventory, detect fraud, and even monitor their fleet deliveries—in the moment.
With India’s public cloud sector expecting to reach USD 13 billion by 2026, according to IDC, more and more businesses are waking up to the power of real-time data to optimize and improve their offerings – a clear signal that Indian businesses are eyeing technologies that offer them real-time data.
Real-time analytics enable the business to extract more value from their data, and set up automation to leverage on these insights. While cloud technologies have changed the speed businesses engage with customers, real-time data adds a layer of intelligence and relevance to the already seamless customer experience; turning casual browsing into a compelling sales pitch.
How is NoSQL important to machine learning & AI in data analytics?
Many businesses today have turned to the NoSQL database standard as a foundation for more advanced technologies such as artificial intelligence (AI) and machine learning (ML). This is driven by the need to access a high-availability, high-performance database to support the massive amounts of data needed to support high-velocity AI and ML algorithms.
NoSQL databases, including Apache Cassandra, address all the above, with some featuring in-memory data-processing framework, enabling the business to analyze data faster than ever. Some have even eliminated the need for an additional analytical layer by streaming data from AI databases in real time.
ML capabilities will also enable the enterprise to train, deploy and use abstractions to shorten development times. That’s because machine learning reduces the amount of backlog coding required when developers add new features to existing applications. At the same time, internal stakeholders can utilize the database easily and quickly for any tasks imaginable.
Please list down a few instances where real-time data analytics has helped Indian businesses?
VerSe employs DataStax-powered technology to enable more than 300 million of their users to consume content in their local languages, inspiring creativity and connection through digital empowerment. This has been the engine behind India’s fastest growing short video app, called Josh. The utilization of DataStax technologies has elevated VerSe from a startup to one of India’s tech unicorns for local languages.
What are the most important data analytics trends that you see emerging across the globe?
The top three trends that are dominating today’s expanding marketplace are data science, big data analytics and artificial intelligence. With the adoption of technology, more businesses are expanding rapidly in data analytics, resulting in a surge in data-driven models and the normalization of automation in operational processes.
At the same time, we are witnessing many businesses jumping on data analytics to support their enterprises with data-driven decision-making, adopt new data-driven models or simply to expand their businesses into previously untapped segments. We are also seeing a surge in interest in utilizing artificial intelligence to improve customer support, automate processes, and drive content and creation, as well as non-enterprise utility such as artificial intelligence-based fact checking.
