Business Intelligence comprises a set of processes and strategies for business data analysis and actionable business decision making. Business Intelligence combines all the techniques and technologies, and converts and transforms the raw data into meaningful business information. Through deeper data analysis, BI provides meaningful insights about past, present, and future predictions of business operations.
Big Data is the large volume of data collected from multiple sources. This data can be structured or unstructured and need a deeper analysis before its application. Big data can identify market trends and aid for better business performances. The data provides insights by analyzing and predicting customer behavior through data derived from social media, app usages, purchases, and other sources.
Making better decisions by analyzing huge data sets, to help businesses in expanding is the ultimate aim of Business Intelligence and Big Data.
Big data allows a unified view of data from multiple data sources. This data which is delivered to data warehouses simplifies the data analysis process to derive actionable information. By integrating big data with BI, organizations can view and use data to make improvements in their business.
Big data integration must address scalability and high-performance managing structured and unstructured data. Business size, the resources available, the need, and purpose served by the data, are all important factors to consider during data integration. At all stages, data integration must ensure operational efficiency and risk management.
ETL- Extract, Transform and Load is a process of extracting the desired data from different sources, transforming the collected data into the preferred format, and loading the data in the target system. The data collected from different databases need to be combined and framed into a single framework to enhance data analysis and boost business performance.
Big data analytics finds its uses amongst a wide range of industries. The following are the major industries that take the help of big data analytics companies to leverage the data and increase the ROI.
Financial organizations depend on large volumes of data that need to be handled with much care and attention. In the era of digital banking, these organizations need to rely on data and analytics. Big data exercises a serious role in risk analysis and fraud detection ensures customer satisfaction.
Universities and colleges and even schools can have the best use of big data. With the student data, these institutions can analyze the patterns of student behavior. From the insights gathered from the analysis, every minute detail regarding the students can be analyzed. This will help to understand the students better and approach them with an appropriate curriculum thereby reducing the reasons for dropouts and failures.
Healthcare institutions can deliver personalized patient care and the prediction of health outcomes by analyzing healthcare trends. Big data helps to maintain health records of patients and thereby analyzing the disease patterns. This will help to implement better healthcare strategies and also predict health outcomes. Big data analysis also aids in developing personalized medications and efficient treatments.
Big data has brought a revolution in giving a personalized shopping experience to e-commerce customers. Companies offer recommendations based on the search history of the customers. Big data recommendation engine helps the companies to notify the trends and product updates to the customers by analyzing previous purchases and their search data.
Entertainment and Media are also exploring the benefits of big data analysis. Big data recommendation engine helps the customers and companies. Customers will get the right recommendations based on the programs they viewed, most viewed, the time they spend on streaming on the program, the device used, etc. Personalized advertisements are provided to attract customers to make a buying decision. Even the best time to stream an ad can also be analyzed using big data.
The ultimate aim of any service-based industry is to give the users or customers a personalized experience. Real-time data analysis helps to arrive at better decisions in a fast and specific time frame. Analyzing the traffic conditions in big and crowded cities can also be done. Monitoring cameras and GPS systems enhance transportation. Locating vehicles, driving behaviors, and such conditions can be monitored and data collected can be further analyzed to provide advanced intelligent transportation.
Data visualization is the best way to explore and understand the data for business purposes. Interactive data promote more user engagements and provides informational insights for business processes. Data visualization is one of the best choices for business intelligence to easily analyze and use the best out of the data. With the right business intelligence tool, a user can extract the right information from the data or report generated.
The visual presentation of data helps to analyze the data much deeper to explore the trends and patterns. Informed predictions about the future can also be made with data visualization techniques. Data visualization techniques allow having full control over the data. The huge data sets need not have to analyze for extracting the relevant data.
Automated data visualization enables to get refined and different levels of data. Based on customer interests and requirements, the data can be presented by identifying and understanding the trends and patterns. This will make communication with the customer easier. The data visualization tool is highly efficient and useful to get the most relevant and needed information.
Businesses are becoming more data-driven. The implementation of big data analytics helps businesses in achieving full competitive advantage thereby reducing operational costs. Big data deals with data mining, storage, and analysis, while business intelligence is all about reporting and analysis of data, for making prudent business decisions, technological advancements, the various approaches, and for which the data is made easily accessible.
Dhanesh Haridas, CTO of Epixel MLM Software, has 12+ years of experience in Software Development. He is an enthusiastic business person, a perfect leader, and above all a passionate writer. He is very keen on experimenting with the latest technological advancements. His areas of interest include Artificial Intelligence, Software Development, Data Science, Blockchain Technology, Cryptocurrency, IoT, and so on.