We live in a generation where business and IT have easy access to interact all because of advancement in cloud technology and mobile applications. In all this process the swiftly growing technologies are business intelligence and allied concepts big data and data mining.
Both BI and Big Data can be considered as two batsmen on the same pitch—both aim at winning for the team, but personal scores matter too. In this context, the main aim is to provide well-planned strategies by analyzing data that’s been mined over time.
In simple terms, business intelligence is a composition of system software that helps in generating meaningful and useful information that enables the user to understand the keen insight of the company and know about the trends, patterns, technologies, and reports.
Big data is always assumed as huge and unstructured data, whereas big data is not just huge but it is also about the composition of data, operation of days, and value-added in developing data.
One of the first things that consumers are reminded of when reading or speaking about the Big Data is the 3Vs system it meticulously follows. It’s a trademark characteristic of the technology that primarily makes online streaming easier. The latter, however, reminds many of its eternal ability of reporting, analyzing, strategizing, and pulling decisions on traditional data.
The tools and methods have definitely evolved over time between the two, and today’s corporate world is only proof.
Business Intelligence Services:
Business Intelligence (BI) often refers to the traditional set of technology-driven software tools that primarily aim at providing accurate reports and insights into the business and market to its stakeholders. With the ability and function of analyzing raw data into meaningful information, it is simply a set of processes and architectures that help in designing profit strategies for businesses. Except for the manual maintenance of the application, the system is highly automated. It simply extracts data from the one that is mined, slices the data according to the analyzer's preference, and finally presents itself in forms of reports, graphs, etc.
In short, one can say that the service has brought the hardships of business analysts to ease. This is primarily due to its ability to reciprocate the consumer-seller relation through appropriate methods. Although it's a service of older generations, it remains as one of the most sought after methodologies in today’s time and day.
Big Data Services:
One of the biggest advantages of Big Data is the Predictive Analysis. Big Data Analytics tools can predict outcomes accurately, thereby allowing businesses and organizations to make better decisions, while simultaneously optimizing their operational efficiencies and reducing risks.
By harnessing data from social media platforms using Big Data Analytics tools, businesses around the world are streamlining their digital marketing strategies to enhance the overall consumer experience. Big Data provides insights into the customer pain points and allows companies to improve upon their products and services.
Big Data Analytics could help companies generate more sales leads which would naturally mean a boost in revenue. Businesses are using Big Data Analytics tools to understand how well their products/services are doing in the market and how the customers are responding to them. This, they can better understand where to invest their time and money.
With Big Data insights, you can always stay a step ahead of your competitions. You can screen the market to know what kind of promotions and offers your rivals are providing, and then you can come up with better offers for your customers. Also, Big Data insights allow you to learn customer behavior to understand customer trends and provide a highly ‘personalized’ experience to them.
Here are the few takeaways which may sum up the key differences between the two:
Business intelligence enables the user to take effective decisions and help in providing accurate reports by retrieving information from the main data source.
Big data ‘s main purpose is to record data, operate data, analyze data for both structured and unstructured to enhance customer output.
Business intelligence requires an operating system, dashboards, ERP databases, data warehouses components.
Big data requires Hadoop, spark, hive, HDFS, R servers, etc components.
Business intelligence provides the following benefits
While both the contenders have their set-backs, there are certain features that only one possession can nail.
When we speak of Big Data, the modern methodology instantly reminds of fraud detection, storage mining, improved decision making, and efficient data analysis services. Data Services like cost-saving, improved data insights, accurate prediction and forecasting, and other professional services have definitely seen the light of the day.
Business Intelligence, on the other hand, is a veteran in this game. Sophisticated data quality, efficient reporting, better business decisions, increased market revenues, reduced manufacturing costs, are still some services that the world remembers BI by.
To conclude, one can say that the two “rival” ideologies make it a point to complement each other’s presence. Big Data should be grateful to the fact that it has branched from the sophisticated body BI Services. On the other however hand, BI simply provides a launching pad to understanding the dynamics of the data analytics services for any newbie. Conclusively, the two giants work hand in hand and are highly related to each other. One may be a newer data service provider, while the other may be a veteran, but the two will always work in conjunction.