HOW TO TRANSFORM BIG DATA TO SMART DATA USING DATA ENGINEERING?
Specialized components backed up by AI and ML known as Data Sensors pick up data and transmit to collection-point where the data is used for actionable insights. These ultimately processed largely by third-party yet seamless Analytics platforms. Modern Industrial Internet of Things Systems leverage Data Sensors. The other form of information collected and processed by the data-driven systems is one that is generated by end-users or customers across various touch-points during the course of an automated business transaction.
As machines also learn with training data, there is a substantial need for Smart Data that is real-time as well as actionable – and this is achieved with complex Machine Learning algorithms in place. Data is collected, handled, transmitted, and processed – the four major stages in ‘data journey’ – towards tangible information-driven results. Smart Data is now regarded and treated as one of the most powerful information-rich assets.
The initiatives towards leveraging AI and ML in order to derive Smart Data from Big Data provides flexibility to organizations in terms of data usability by enabling bots to comprehend business data – with cognitive capabilities for collecting and transmitting the required data. This is often made possible with the use of data-ready platforms, and the legacy business systems or enterprises are upgraded to the same.
Data specialists and strategists from the healthcare domain have indicated a rising significance of data-centric platforms coupled with Data Sensors, along with their key benefits. But those establishments making use of such sensors are still a few in numbers, the research concludes. Most of them are in the nascent stage of adopting intelligent platforms that streamline healthcare operations, and moving to Big Data and then Smart Data is gradually happening.
Marketing and B2B powerhouses are increasingly seeing through the ‘thick’ of data and would want to work with cool and smart data alternatives that are thin and sleek. These organizations have moved into the mainstream of ‘Smart Data’ initiatives, reports suggest. The focus will now be on interpreting real-time Business Intelligence from clusters of Smart Data to manage long-time reputation with partners, manage product lines, trim or enrich discounts and offers, and more importantly – manage relationships with partners and valuable stakeholders.
Industries such as wine and beverages are aiming at tapping data based on customer-centric requirements. Research quotes domain expert admitting real-time information is indeed vital – and as data is powerful for them, they would deploy AI that can segregate meaningful information, as consumer eyes newer beer variants in a market that is ‘saturated’. Smart Data would help gauge the preferences of a consumer who is looking around for substitutes according to buying patterns – such as changing moods and weather conditions.
With increasingly dynamic enterprise solutions ecosystem, businesses can effectively liaise between entities our touch-pints that leverage data towards cutting-edge transformation.
Green check mark and red cross icon set. Circle and square. Tick ...Tapping into service lines that require real-time decisions based on data-centric insights
Green check mark and red cross icon set. Circle and square. Tick ...Level-playing field for customers seeking various options across devices and platforms
Green check mark and red cross icon set. Circle and square. Tick ...Wholesome data strategy that can bundle swiftly with new-age practices such as DevOps
Green check mark and red cross icon set. Circle and square. Tick ...Efficient collection, transmission, and storage of information across the vital ‘data points’
Green check mark and red cross icon set. Circle and square. Tick ...Superior Business Intelligence with AI and ML to tap and convert Big Data to Smart Data
Green check mark and red cross icon set. Circle and square. Tick ...Enterprise-wide and data-ready systems that automate processes with quick data assimilation
Advanced forms of Analytics normally focus on a customer’s actions and behavior, rather than their thoughts. Marketing organizations will often use this kind of analysis to manage reputations, manage products, and provide competitive Business Intelligence. Techniques for collecting this kind of information include short surveys and comprehensive software platforms.
With the latest buzz around leveraging data-driven applications and processes, NYGCI is poised to create and sustain the ideal technology ecosystem and intelligent framework for its clients. We are delighted to build competency around new-age platforms that can help businesses turn around their investments to profitable returns.
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