Technological foundations of business intelligence (BI) and data warehouses

I would like to discuss different among BI, Big data and data mining.

Business Intelligence:

BI decision making based on data. It includes the generation, aggregation, analysis and visualization of data to inform and facilitate the company’s management and strategy development. All other terms relate to certain aspects of how the information is collected or munched while BI goes beyond data to include what leading companies are actually doing with the ideas they glean from it. BI is not strictly technology; it involves the processes and procedures that support data collection, sharing, and reporting, all in the service of making better decisions. One trend in recent years has been away from systems that rely on IT staff to provide reports and graphs for decision makers with regard to so-called BI self-service tools that enable business users to generate their own reports and visualizations to share with colleagues and help everyone choose what to do.

Big Data

Big Data refers generally to the huge amounts of data available online and in the cloud, which always requires more computing power to collect and analyze. Because the sources are so diverse, data are often completely unstructured and raw. Since you’ll probably use this data for purposes it was not designed to serve, you need to clean a little before you can collect useful information from him. The systems you put in place internally to track key performance indicators are obviously the main source you turn when you need to answer a question about your business, but Big Data provides virtually unlimited quantity information, you can sift through for ideas related to your industry, your company, your potential customers. Big Data is the library you visit when the information to answer your questions are not readily at hand. And like a real library, it allows you to search for answers to questions you did not even know you had.

Data Mining

Data Mining is probably in the category of analysis, but most analyzes are based on data from systems in place to track key performance indicators known it is generally more as mining.Data Mining is the practice to sift all the evidence in search of previously unrecognized patterns. Some companies are even hiring scientists, statistical experts and IT who know all the tricks to find the hidden signals in noise. One of the difficulties to maintain all the terms are right that there are tools that bring together elements of all categories. BI power, for example, is obviously a BI tool, but it allows business users to analyze, visualize and share data in a multitude of ways. You can also use the analysis and visualization features information you shoot in the cloud, so it is an example of Big Data. Ultimately, however, it is also important that we apply the appropriate labels to all that is that you have an effective way to collect and use the information to keep your business growing and thriving

*****Comparison among BI , Big Data and Data mining*******

BI vs. Big Data

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Big Data refers collectively to the act of generation, capture and treatment generally huge amounts of data on an ongoing basis while Business Intelligence refers collectively to software and systems that import data flow for any size and use them to generate information displays that link to specific decisions. Big Data is a term much more widespread, and encompassing genericized. He took the wind because digital systems generate more data than ever, and new approaches are needed to handle and store data. Obviously, the data streams as they must come up with methods to transfer, store, access and process the data without making computer servers to a grinding halt.
The business intelligence, on the other hand, can use the data streams of all sizes to analyze and view critical information. This process is known as “analysis” because it digests analysis and data flow in a way that is both easier to understand and more points clearly towards actions necessary based on said data.

BI vs. Data Mining

Business Intelligence is a data-based decision making that allows data, scientists to generate, aggregate, analyze and visualize data to help companies make better business decisions. Business intelligence goes beyond data collection and calculations on how companies can take big data and data mining. This means that business intelligence is not limited to technology; it includes the business processes and data analysis procedures that facilitate the collection of important data.

Data mining is the process of finding answers to questions you did not know you were looking for in advance. With information overload, many data analysts are not sure that they give on the key points that can help their businesses more successful. Data mining experts sift through large data sets to identify trends and patterns.

Big Data vs. Data Mining

Big data is a term for a large data set. Big data sets are those who outgrow the simple kind of database architectures and processing of data that were used in the past when large data were more expensive and less feasible. For example, the data sets that are too large to be easily manipulated in a Microsoft Excel spreadsheet might be called large data sets.

Data mining refers to the activity of going through large data sets to search for relevant or pertinent information. This type of activity is really a good example of the old axiom “a needle in a haystack.” The idea is that companies collect massive data sets that can be homogeneous or collected automatically. Policymakers need access to smaller pieces, more specific data from these large assemblies. They use data mining to find the information that will inform the leadership and help lead the way to a business.

Data mining may involve the use of different types of software such as analysis tools. It can be automated, or it may be largely labored, where individual workers send specific requests for information to an archive or database. In general, data mining refers to operations that involve relatively sophisticated research operations that return targeted and specific results. For example, a data mining tool can look through dozens of accounting information for years to find a specific column expenses or accounts receivable for a specific operating year.

In short, big data are the operating assets and data is the “manager” of which is used to provide beneficial results.

Finally, I would like to share an episode from YouTube, which could help us better understanding of Big Data, BI and Data mining

References:

BI vs. Big Data vs. Data Mining https://selecthub.com/business-intelligence/bi-vs-big-data-vs-data-mining/

Business Intelligence vs Analytics vs Big Data vs Data Mining http://blog.apterainc.com/business-intelligence/business-intelligence-vs-analytics-vs-big-data-vs-data-mining

 

 

 

 


					
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