Guest Author: Dr. Jagreet Kaur, Chief AI Officer, Xenonstack
What is Data Intelligence?
The world is leading towards data-driven intelligence. To stand in the world of evolving technology and the competition phase, organizations must make data and AI-based decisions. It becomes difficult for the organizations that are not working on those aspects and data to know the facts and insights while making decisions.
Data Intelligence enables the process of multisource data and generates meaningful insights that would help to make valuable decisions. It allows combining unstructured data and text analytics results with structured data to use for predictive analytics. It can give a real-time statistical analysis of structured or unstructured data to understand data patterns and dependencies.
Why Do You Need It?
Data intelligence is required to process and understand the data. Data intelligence is rapidly becoming one of the most important elements of big data. Data intelligence has progressed from the infantile stage to a point where it can handle vast amounts of data with intelligence. It isn’t going to fold its wings either; the immediate positive results have attracted many organizations’ attention. Various entrepreneurs have expressed interest in using and developing data intelligence to make intelligent decisions in driving their business. There are multiple cases where we may need it. Some instances have discussed that helps to know why we require data intelligence:
- Artificial Intelligence: Using a machine learning algorithm helps to find the predictive analysis and to recognize correlation. It helps to find domain-specific custom entities and word usage.
- Intuitive Visualization: It allows us to understand data effectively in less time using informative intuitive charts and graphs. Visualization helps to understand complex data within seconds rather than reading and understanding an excel or any other data file. Visualization also generates insights and clear data patterns that are difficult to find in tables or datasets. It enables to easily filter and drill down the reports according to the requirements.
- Insight generation: Based on the collected data, it allows generating or taking insight from the visualization that helps to understand the business progress and customer needs.
- Data-driven decision-making: To make better and data-driven decisions so that those correct decisions can be taken to gain customer satisfaction and revenue.
The Base Foundation For Data Intelligence
Data intelligence is an optimized way that provides an unconventional 360 view of the business environment. It helps to understand the customer requirements better and also monitors the organization’s performance. Based on the data or insights, make decisions according to customer preferences and improve its revenue and benefits. Data intelligence is based on several sets of techniques accordingly to enrich business decisions and processes. These are:
- Descriptive (“What happened”): It is used to review and examine the historical and real-time data to understand business performance and customer behavior. It detects a particular occurrence of a situation.
- Diagnostic (“How it happened”): To know the reason for the occurrence of a particular instance or situation.
- Predictive (“What could happen”): It uses historical and, based on that, predicts future occurrence using some ML algorithm.
- Prescriptive (“What Should We Do”): To develop and analyze the alternative knowledge that can be applied in the course of action. It helps us to understand what to do in the future.
- Decisive: Decisive analytics helps to measure data suitability. It chooses the recommended action to implement it in the environment and real-time process when there are multiple possibilities.
How Can I Use Data Intelligence?
Data intelligence performs the following steps to identify relations and mentions of unstructured or structured data.
- Data Ingestion: It collects structured and unstructured data from different sources such as documents, emails, databases, websites, and data repositories. Data can be inserted into the application or platform manually or scheduled at fixed intervals of time. Data can be processed and used by that application to perform tasks.
- Data Processing: Now, data collected from sources can be processed and used to generate insights. It makes it possible to find a relation between data. Several tools provide an easy-to-use interface for creating custom models to train and test the model to find entities and data relations. It allows using models for future predictive analytics.
- Reporting and Visualizations: Reporting and Visualization is the final step that analyzes the data using charts and graphs. Visualization makes it easy to understand large and complex data effectively.
The Benefits Of Data Intelligence
Data intelligence gives wings to the technology by providing intelligence in their daily tasks and decisions. Let’s discuss the benefits of data intelligence and why organizations should embrace them:
- Changing demands: Data intelligence makes the organization adopt the dynamic changes of the industries. The business nowadays is continuously evolving. To stand in the competition and reduce the chances of failure, organizations must accept and update the newly emerging trends. For example, the trend of the adoption of selfie cameras in smartphones was increasing. Mobile businesses that do not capitalize on the trend are doomed to fail. Data intelligence helps organizations to understand customer behavior and change. Firms are informed about repeated changes and the pattern of occurrence by smart adaptive dynamics. It allows the company to make informed decisions based on the analysis.
- Strong Foundation of Data: Data intelligence makes big data more strong and strengthened by restructuring the process of data arrangements. It allows to gather insights from big data and then render optimized engagement capability.
- Useful Data: No doubt the world is generating a large volume of data every day that can change the world and improve the services according to customer demands and preference. But most of the data is not in the form of use. It is not possible to directly use that data. It is required to transform it into a useful form to use data. Data intelligence is also in charge of converting raw data into cumulative information. Data intelligence cleans and transforms data into smart capsules of ready-to-use data that can be used in the company to assess results. Data intelligence makes it possible not to worry about defining particular cases to the computers.
- Augmented Analytics: Advanced statistical approaches are used in data intelligence to advance visualized predictive and prescriptive analytics. Instead of building a complete application every time, it automates the data processing that can be completed just by doing some simple steps. If required, further changes may be recommended based on the results. There is no way for business plans to fail with such extensive planning for a real-life scenario. Advanced simulations enable businesses to predict potential outcomes and make changes to prescriptions as needed.
- Accelerate innovation: Data intelligence makes it possible to accelerate innovations by making smart use of data. It allows using data insights to drive business innovations and use them to develop their services by considering customer preferences and requirements.
What is the difference between data information and intelligence?
- Data: It is the raw form of data recorded truth at a point in time. It might be a conversation, a purchase, or an interaction with your company’s website. Data is the compilation of results from those incidents that are then quantifiably recorded so that companies can review them easily.
- Information: It is a collection of data or a way of bringing data together. When data is picked from an event and put into narrative forms, it helps to answer the following questions:
- What is the churn rate of employees?
- How long is the sales cycle of an organization?
The information helps to answer these questions that move the business.
- Intelligence: Intelligence is a group of information to derive intelligence or decisions in their application or tasks. For instance, suppose you are selling more in southern regions, then the smart and intelligent answer will be why that might be. To get an answer, it will look at numbers such as the number of events, amount spent on advertisements, marketing campaigns southern region clients receive. After that, it can be compared with the other region (North region). Through this analysis, we get to know that there are more client interactions in the southern region, so to increase sales in the North region, it is necessary to do the same.
Data Intelligence In The Real World
- Healthcare: Rapid digitalization of healthcare systems are adopting technologies to create a connected healthcare environment. Hospitals need to synchronize with the technology to become smart, advance, and more accurate. Hospitals use various types of sensors, apps, digital equipment that are generating a large volume of data regularly. This data can be used to automate several processes such as administrative, treatment, and clinical processes. Data intelligence capabilities allow ML, AI, and Deep learning to make the healthcare processes more accurate, fast and help the practitioner handle the increasing number of cases and processes. These advanced technologies help to extract real-time intelligence and make decisions regarding the diagnosis process, prescribing medicines, hospital management, laboratory, patient care, etc., and leads to high operational efficiency and care delivery.
- Supply chain management: Supply chain software generates and collects a vast amount of data. But they are not aware of how they can best use it to make their operations more effective. Data intelligence in the supply chain management network predicts business risk, minimizes loss, and makes automated self-learning supply chains. As a result, it drives real-time coordination and innovations.
- Human Resource: Organizations are using HR software to manage internal HR functions such as payroll, employee benefits, recruitment, training, talent management, attendance management, employee engagement, etc., to enhance their features and capabilities. They always have to do many tasks to understand employees better, attract top talent, and initiate programs to retain them and analyze their performance. They have a lot of data generated from their HRMS(Human Resource Management System) software. Data Intelligence can help them analyze and understand the data, gather insights, and make a precise decision that can make their organization drive healthier and faster.
- E-commerce: One of the success secrets of an e-commerce website is using customer reviews to know their experience, preference and then use them to make profitable decisions. Using ML and NLP techniques to interact with their customers and get data from them and use it to drive performance, improve Customer Engagement, Service Quality, Support Quality, and ultimately Sales. Data Intelligence makes it possible for them to accomplish these tasks, recommend products, understand customer preferences, solve their queries, improve quality and services, etc. Harnessing this information can give you a treasure trove of insights that can power your products and processes, improve customer experience, marketing, manage store operation, etc.
Conclusion
Akira AI is a data intelligence platform that provides intelligence using analysis and learning by processing data from various sources.
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