Lately, there have been tremendous shifts in the business technology landscape. Advances in cloud technology and mobile applications have enabled businesses and IT users to interact in entirely new ways. To help you understand the various concepts in business data concepts, it is important to understand the difference between business intelligence, Big Data and data mining.
BI vs Big Data
Business intelligence is the collection of systems and products that have been implemented in various business practices, but not the information derived from the systems and products. On the other hand, Big Data has come to mean various things to different people. Some people use the term Big Data when referring to the size of data, while others use the term in reference to specific approaches to analytics.
Business intelligence is the practice of taking large amounts of corporate data and turning it to usable information. This practice enables companies to derive analysis that can be used to make profitable actions. The process of converting corporate data to usable information is time consuming, and involves various factors such as data models, data sources, data warehouses and business models, among others.
Setting up a successful business intelligence environment involves having the right tools and systems in place. It requires having business analysts and owners who can guide the initiative. There are various factors to take into account when setting up a business intelligence environment, including the data types to be analyzed, the right tools for the job and determining how the data will be integrated for business intelligence analysis. Analytics such as descriptive, prescriptive and predictive analytics are also a part of business intelligence.
Big Data is the process of storing, processing and visualizing data. It is essential to find the right tools and applications for creating the right Big Data environment so that you can successfully obtain valuable insights from the data.
Setting up an effective Big Data environment involves utilizing infrastructural technologies that process, store and facilitate data analysis. Today, businesses often use more than one infrastructural deployment to manage various aspects of their data.
Big Data often provides companies with answers to the questions they did not know they wanted to ask. Therefore, there is an inherent usefulness to the information being collected in Big Data. Businesses must set relevant objectives and parameters in place to glean valuable insights from Big Data.
BI vs Data Mining
Business intelligence is a data driven decision-making process that enables data scientists to generate, aggregate, analyze and visualize data to help business make better management decisions. Business intelligence goes beyond data collection and crunching, into how companies can gain from Big Data and data mining. This means that business intelligence is not confined to technology; it includes the business processes and data analysis procedures that facilitate the collection of Big Data.
Data mining is the process of finding answers to issues you did not know you were looking for beforehand. With information overload, many data analysts are not sure they are overlooking key points that can help their companies perform better. Data mining experts sift through large data sets to identify trends and patterns.
Big Data vs Data Mining
Big Data and data mining are completely different concepts. However, both concepts involve the use of large data sets to handle the collection or reporting of data that helps businesses or clients make better decisions. However, the two concepts are used in two different elements of this operation.
The term Big Data can be defined simply as large data sets that outgrow simple databases and data handling architectures. For example, data that cannot be easily handled in Excel spreadsheets may be referred to as Big Data.
Data mining relates to the process of going through large sets of data to identify relevant or pertinent information. Businesses often collect large data sets that may be automatically collected. However, decision makers need access to smaller, more specific pieces of data and use data mining to identify specific data that may help their businesses make better leadership and management decisions.
Various software packages and analytical tools can be used for data mining. The process can be automated or be done manually. Data mining allows individual workers to send specific queries for information to archives and databases so that they can obtain targeted or specific results.