Purpose & Description:
Data analytics (DA) is the science of examining raw data with the purpose of drawing conclusions about that information. Data analytics is used in many industries to allow companies and organization to make better business decisions and in the sciences to verify or disprove existing models or theories.
Analytics is the discovery and communication of meaningful patterns in data. Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance. Analytics often favors data visualization to communicate insight.
Bhavna Corporation applies analytics to business data, to describe, predict, and improve business performance. Areas within analytics include:
- Predictive Analytics
- Enterprise Decision Management
- Retail analytics
- Web analytics
- Credit risk analysis, and fraud analytics
Analytics can require extensive computation, since the algorithms and software used for analytics harness the most current methods in computer science, statistics and mathematics. This is especially true for big data analytics.
Bhavna Corporation uses big data analytics techniques to provide solutions. Big data analytics refers to the process of collecting, organizing and analyzing large sets of data, called as big data, to discover patterns and other useful information. Big data analytics can help organizations better understand the information contained within the data and will also help identify the data that is most important to the business and future business decisions.
Analyzing big data allows analysts, researchers, and business users to make better and faster decisions using data. Using advanced analytics techniques, businesses can analyze data sources independently or together with their existing enterprise data to gain new insights into their business and the markets in which they operate.
Bhavna Corporation has expert teams with knowledge of big data analytics. We help organizations break down data silos and analyze data which improves business in terms of efficiency, customer retention, competitive position, time to market, and profitability.
How big data analytics works?
- The volume of data and the different formats of the data (both structured and unstructured data) are collected across the entire organization.
- The different types of data can be combined, contrasted and analyzed to find patterns and other useful business information.
- Data silos are broken down to enable access to all data that an organization stores in different places, and often in different systems.
- Platforms that can pull in unstructured data as easily as structured data. This massive volume of data is typically so large that it's difficult to process using traditional database and software methods.
- To analyze such a large volume of data, big data analytics is typically performed using specialized software tools and applications for predictive analytics, data mining, text mining, and forecasting and data optimization. Collectively these processes are separate but highly integrated functions of high-performance analytics. Using big data tools and software enables an organization to process extremely large volumes of data that a business has collected to determine which data is relevant and can be analyzed to drive better and more timely business decisions.
- Organizations are increasingly looking to find actionable insights into their data. Many big data projects originate from the need to answer specific business questions. With the help of our solutions, organizations can achieve these answers
- Providing a big data analytics platform , which help organizations to boost sales, increase efficiency , and improve operations
- Provide the best customer service and risk management system.