Previously we followed the ETL data handling model. ETL stands for extract, transform and load.
Data captured by the system mainly to get reports from past actions. Different methods are used to load various files into large databases that produce desired reports.
But this is not a rigid system, which cannot take care of several data streams, especially in large volumes.
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This system also cannot change input info in real-time and is more suitable for responding to a fixed query.
But big data analytic has changed everything. Now using Advanced Analytics, the company can decide better.
Data analysis has enabled an increase in reporting interface structures, better data extraction capabilities, automatic file handling protocols, the creation of data flows that are very indexed and above all, cloud hosting capabilities and blockchain technology to run and control large systems at the basic time.
All of this comes down to better business decisions so as to increase sales and marketing effectiveness and at the same time reduce costs and eliminate waste for all digital businesses.
Companies can obtain significant benefits of data analytics services to get positive results for businesses and customers while ensuring high-level data protection. The most important advantage of sophisticated analysis is:
1. Proactive approach.
According to a report with compliance, governance and supervision advisors, 60% of data brings a little or no value. Most data loses its value if it is not contextualized in real-time, so it is important for businesses to make data in real-time with the lowest possible latency and capacity that can be scaled.
When sharing info, the only hope that customers must understand their needs correctly and to provide unlimited interactions at all stages of interaction by doing so that the company can improve customer experience, the way of a sure shot to forge a lasting relationship.
2. Offering the right product
Efficient data analysis and collection helps businesses to understand the demands of market technology to be able to position the right products or services at the right time.
3. Customized service
Currently customer behavior is very fluctuating and unpredictable plus many options available for them choose.
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The only way to get them is to offer personalized responses and make them feel valued personally.
Using large data analysis, it is possible to make the most suitable interaction with the type and personality of the customer.
For this, the system must be able to capture their customer attitudes, locations and preferences to offer customized responses in multi-channel environments.
4. Improve operating efficiency
Data analysis helps in understanding, designing and optimizing products with the highest efficiency, which is able to meet customer needs and expectations.
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Large data solutions help in improving field operations, increasing productivity and thus minimizing costs and increasing margins.
