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To an outsider, Data Analytics and Business Intelligence might look similar and serve the same purpose, but there lies the difference. Continuous advancement in the fields of business intelligence, data analytics, and data science is making it necessary to understand the distinction between these terms and compare Business Intelligence VS Data Analytics.
Business Intelligence (BI) is a comprehensive term encompassing data analytics and other reporting tools that help in decision making using historical data. BI vendors are developing cutting edge technology tools and technologies to reduce complexities associated with BI and empower business users.
Data Analytics focuses on algorithms to determine the relationship between data offering insights. The major difference between BI and Analytics is that Analytics has predictive capabilities, whereas BI helps in informed decision-making based on analysis of past data.
Data Science is one of the recent fields combining big data, unstructured data, and a combination of advanced mathematics and statistics. It is a new field that has emerged within the field of Data Management providing an understanding of the correlation between structured and unstructured data. Nowadays, data scientists are in great demand as they can transform unstructured data into actionable insights, helpful for businesses.
Business Intelligence (BI) helps different organizations in better decision-making leveraging a wide range of latest tools and methods. It is the broadest category involving data analytics, data mining, and big data. BI involves varied processes and procedures which help in data collection, sharing, and reporting to ensure better decision making. With recent advancements in BI tools, users can generate reports and visualizations all by themselves, without relying on IT staff.
BI refers to data-driven decision making with the help of aggregation, analysis, and visualization of data to strategize and manage business processes and policies. Traditionally, BI deals with analytics and reporting tools, which helps in determining trends using historical data.
The recent trend in Business Analytics showcases the increase in value for integration, as well as the consolidation of information to ensure policy formation and meet strategic objectives. Several companies are utilizing hi-tech business tools to meet ever-growing data technology needs with extended capabilities.
A recent survey in Forbes Magazine said, “The Big Data trends have affected the data analysis in different ways that led to almost 15 % growth in this arena last year alone.”
Business Intelligence and Analytics vendors are noticing the shift driven by big data and are prepared to face similar marketing scenarios. The role of analytics is extremely important in extracting the relevant information and deriving actionable insight. Analytics is becoming a significant factor in decision making at any future-oriented organization. Simple and easy to retrieve reports is a critical functionality required in data analytic tools. Organizations are facing challenges in integrating the BI systems with the existing system and generate reports that offer actionable insights.
According to CEO of Big Data-Startups, Mark van Rijmenam, “the difference between Business Intelligence and Data Analytics lies in the fact that Business Intelligence helps in making business decisions based on past results while data analytics helps in making predictions that are going to help you in the future.”
Vice President of Engineering, Noetix Products, Pat Roche said, “Business Intelligence is required to operate the business while Business Analytics is required to transform the business.”
BI focuses on achieving operational efficiency using real-time data to bring about efficiency in different job functions. It involves an in-depth analysis of historical data from varied sources to help in making informed decisions. It helps individuals in making queries, asking data-related questions and getting results. BI tools are specially designed to display the results of analytics in a manner understandable even to a layman.
Business Analytics, on the other hand, helps in determining future trends using data mining, predictive analytics, statistical analysis, and others as well to drive innovation and success in business operations.
With huge volumes of data being continuously shared, data explosion can be witnessed everywhere around us in the form of mobile data generation, real-time data, and others as well. As a result, there is a greater need for protecting data integrity as never before.
Data Analytics has a significant part to play in data security. It is transforming the way to conduct intrusion detection, malware countermeasures, and others as well. Companies are using advanced analytics to manage privacy and security challenges.
Integration of Big Data and Business Intelligence with Cloud Computing is recently trending in the IT sector. However, there are concerns about whether this combination is going to work out or not. According to the latest research reports by Saugatuck Technology, “cloud-based BI and analytics will witness enormous growth in the coming years.” The amalgamation of BI with the cloud can enhance growth rate by leaps and bounds in the next few years.
In the present scenario, businesses need to extract insights and make the most of them from every tweet and customer care interaction. Business Intelligence (BI) and Analytics can help in making insightful business decisions, taking appropriate action along with quick implementation while Data Business Intelligence leverages cutting edge technology BI tools to address data analysis issues. Data Scientists and Domain Specialists are professionals who can skillfully use these tools to fuel business success and innovation.
Excellent post. After reading this I got a clear cut idea regarding these important terms formerly used interchangeably by me when I was talking to my clients. Thanks for sharing this.
Explained in a very simple and understandable language without using much of technical jargon. Excellent!… Two thumps up for this post!!
The complex theories are explained so easily. Thanks for sharing.
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