Can your data talk intelligently? AI plugged into data management systems aims to do just that!
Intelligent analytics offers a classic approach to discover the hidden intelligence behind historical and real-time data. This myriad suite of analytical techniques and algorithms can parse mind-boggling amounts of data generated in real-time to discover the hidden gems that are often missed or go undetected by traditional statistical methods.
The methodology of mixing intelligence with analytics reaches far beyond. It erects the foundation in algorithmic methods removing any bias introduced by an individual analyst. What’s more, the sheer volume of data adds to the veracity and accuracy of the results, rather than causing an unnecessary air of confusion for the analyst.
Unearthing the Wealth of Information
An artificial intelligence (AI) and analytics platform encapsulate the means to derive untapped value from the wealth of information, data constantly generates. While advanced analytics helps enterprises to uncover insights on current business processes and even draw predictions from historical information silos, AI acts as a force multiplier on this data crunching by pledging machine learning capabilities into these data models.
The best artificial intelligence algorithms and analytics software leverage machine learning solutions into big data platform. This way they transform data into intelligent pieces of information, self-service data visualization dashboards, automation-ready capabilities to maximize revenue and operational efficiencies.
How Is AI Used in Analytics?
AI can actually transform data into an intelligent piece of Intelligence
1. Unearthing new insights from data analytics
Artificial Intelligence excels in finding hidden patterns and insights from large datasets which are often unseen from human eyes, this is done at an unprecedented speed and scale. AI-powered tools exist answering the questions about your enterprise operations, for instance, which operations cycle had the quickest turn-around in a specific quarter.
2. Deploy analytics to predict data outcomes
AI-powered algorithms analyze data from multiple sources offering predictions on an enterprise’s next strategic move. It can also deep dive into data to share insights about your customers letting you know about their preferences, and which marketing channels would be the best to target them.
3. Unifying data across Platforms
Artificial Intelligence unifies data captured from different sources and platforms, accelerating data-driven innovation across data science, business analytics and data engineering categories.
The Latest Trends in Intelligent Analytics
Data analytics software
Think business intelligence gathered from a data analytics software that identifies patterns and formulates data relationships. This paves way for actionable alerts, smart data discovery and interactive dashboards, using a comprehensive set of data analytics software on an enterprise-grade analytics platform.
Machine learning and predictive analytics platform
An able platform lets you analyze structured and unstructured big data stored in data management platforms and external sources. AI and open-source data analytics platforms combine open-source machine learning with self-service analytics and predictive analytics to achieve data intelligence.
Natural language processing and text mining
Unstructured data explains stories, sentiments, emotions of your customers, employees and stakeholders. NLP and Text mining extracts terms and concepts from brochures, legal documents, emailers, social media messages, videos, audio files, web pages to unlock the value hidden in unstructured text and yield valuable business insights.
Data visualization is the graphic representation of data. Interactive data visualizations and rich interactive dashboards are the major takeaways from Intelligent Analytics helping enterprises know their data more personally.
AI solution for sentiment analysis
Intelligent data analytics helps an enterprise to understand and highlight what is the people’s perception on social networks and the web about its products and services. Intelligent analytics is thus a blessing to enterprises for targeted customer servicing, customer engagement and retention.
In crux, AI blended data analytics aims to make the enterprise more efficient and productive thereby increasing its brand loyalty, drive revenues and eliminate the need for manual data processing mechanisms. With customised business insights that are accessible and relatable to the most critical objectives of the enterprise, Intelligent Analytics is here to stay.
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Kamalika Some is an NCFM level 1 certified professional with previous professional stints at Axis Bank and ICICI Bank. An MBA (Finance) and PGP Analytics by Education, Kamalika is passionate to write about Analytics driving technological change.
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