YOGYAKARTA - Business competition is getting tighter in this digital era. This makes the big data analytic platform with AI for business now a vital necessity, no longer just an option to stay in the market.
In fact raw data is useless without in-depth analysis. Companies that utilize AI technology to process big data are shown to be 5x faster in making strategic decisions than their competitors.
Reporting from the IBM page, the big data analytic platform with AI is a state-of-the-art system that processes and analyzes large data volumes systematically to extract a variety of valuable information.
Unlike conventional analytics that only deal with structured data, this platform is able to process structured, semi-structured, and unstructured data from various sources such as IoT sensors, social media, and financial transactions.
By integrating artificial intelligence, machine learning, and predictive modeling, this platform converts raw data into follow-up intelligence to support real-time data-based decision-making.
Not just theory, big data analytics with AI for businesses can be useful in the following scenarios:
The big data analytic platform with AI allows businesses to analyze data when the data is generated. This capability helps companies respond to market changes instantly and identify business opportunities quickly.
By uncovering hidden trends, patterns, and correlations in large data, business leaders can formulate more effective strategies in supply chain management, e-commerce, and overall operations.
Predictive analytics help identify business process inefficiency, eliminate waste, and allocate more efficient resources. Companies can save operating costs while increasing productivity.
Understanding customer needs, behavior and sentiment becomes easier. Business can adjust marketing strategies based on consumer preferences for maximum results.
Preditive technology analytics allows companies to identify and address potential threats before they are realized, creating a more solid preventive strategy.
In order for big data analytics to function optimally, there are several key features as follows:
The ability to predict future trends uses historical data, statistical modeling, and advanced AI algorithms.
Visual representation of data that makes it easier for stakeholders to understand complex insights through easily understood interactive graphs, charts and reports.
The ability to collect and process data from various sources such as cloud, mobile applications, IoT sensors, and traditional databases in one centralized system.
Stream processing technology to deal with real-time data streams and batch processing for large data volumes over a given period.
The data cleaning, validation and verification system is to ensure the integrity, accuracy, and reliability of the resulting information.
The ability to understand, interpret, and extract insights from unstructured text data in massive quantities.
Many business owners understand the analytic big data, but not everyone understands how to choose the best platform for their business. In order not to be confused, here are some criteria that must be considered:
Identification of the types of data to be analyzed (structured, unstructured, or semi-structured) and the required analytic methods, which include:
Make sure the platform can handle the exponential growth of your future volume, speed, variation and complexity of your business data.
Select solutions that offer easy integration with existing systems, adequate technical support, comprehensive training, and trial periods to test functionality before full commitment.
Calculated total ownership costs including licensing, infrastructure, and maintenance versus potential cost savings and increased revenues that can be generated.
It can be concluded that the big data analytic platform with AI is no longer a luxury, but rather a strategic need to survive in the digital era. Interestingly, companies that adopt this technology are shown to be 5x faster in decision making and superior to competitors.
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