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https://www.prismetric.com/business-intelligence-vs-data-warehousing-vs-data-analytics/

A discussion on Business Intelligence, Data Warehouse, and Data Analytics with essential pointers that's help to the difference between above all terms in a proper way.

With the ever-increasing use of technology in the business realm, it is clear that the companies who will properly use their data will emerge as champions. Big Data Analytics for sure is one of the technologies in-vogue, but it is a good practise to keep an eye on the trends in Big Data Analytics. This will help implement the most feasible trends and strategies to keep your business afloat. In the age of Big Data, there are a lot of terms that are used daily and three of the most common terms used with respect to Big Data are Business Intelligence (BI), Data Warehousing, and Data Analytics.Let’s now understand the terms one-by-one before the difference between the terms;

What is Business Intelligence?

Big Data Business Intelligence Solutions enable companies to have ideas of presentation. It is also known as BI among the business professionals. BI is the process where you take insights from the available data and use the analytics to produce fruitful action. During the process, Business intelligence deals heavily with data warehousing as the warehouse acts as the source of information for analytics.

What is Data Warehousing?

Data Warehousing is a place where the business data is stored so that it can be used as and when required. Warehousing can happen at any step during the analytics process as the raw data can be acquired and rescanned. Due to prominent big data analytics technologies, the original data in the data warehouse remains safe and potentially unrecoverable.

What is Data Analytics?

Data analytics is a process where computer programming techniques and statistical methods are combined to study the data and derive insights for the betterment of the business. Advanced Big Data Analytics Services include a lot of prep work as the data might be formatted for machine-reading, or filled with errors or other troublesome flaws. Sophisticated data analytics is performed to validate the data with the help of profound toolsets.

To understand the difference between the aesthetics of Business intelligence, Data Warehousing, and Data Analytics, let’s have a one-on-one matchup.

Head-to-Head comparison between Business Intelligence and Data Warehouse

• Basic Usage

Business Intelligence is a system that is used for deriving insights related to a particular kind of business based on the available data. A data warehouse is a place to store historical and current data so that it can be used as and when the need arises.

• Source of Information

In a Data Warehouse, the information is held in fact tables and dimensions. Thus, data dealing with revenue and costs, demographics, or other attributions can be easily placed in a synchronized order. Big Data business intelligence solutions source their data from the data warehouse. Thus, authentic Data Warehousing becomes a must in Business Intelligence.

• Audience

In top-rated advanced Big Data analytics companies, the senior executives and managers have direct access to the analyzed data by Business Intelligence tools. Whereas, data engineers, business analysts, and data analysts use the information from the Data Warehouse to do a competent ‘behind the curtains’ work.

• OutputThe output of Business Intelligence analytics is in the form of charts, graphs, and business reports. The output in a Data Warehouse, on the other hand, is in the form of dimension tables. It is used for upstream applications and for the Business Intelligence tools.

• Tools used

Business Intelligence analytics uses tools for data visualization and data mining, whereas Data Warehouse deals with metadata acquisition, data cleansing, data distribution, and many more. The tools used for Big Data Business Intelligence solutions are Cognos, MSBI, QlickView, etc. On the other hand, Data Warehousing uses tools such as Amazon Redshift, Informatica, and Ab Initio software.

 

How To: Big data is going to be a significant factor in business

Difference between Data Analytics and Data Warehouse

• Time-Variant

In a Data Warehouse, the data collected is actually identified by a specific time period. This is done as a Data Warehouse mainly stores analytical reports and historical data related to the company. For Data Analytics, the best possible approach involves automating insights into a certain data set, in a given set of date and time.

• File System

As in Data Analytics, science of examining raw data is included; it uses the data filing system to save the data for further processing. It takes almost an entire day to complete the processing of the data in a Data Warehouse. Using SAP can be highly instrumental here as it helps in reducing the time taken to process the data. Comprehensive SAP BI/BO solutions providing company can prove to be your apt ally in dealing with this problem.

• Memory Type

Data Warehouse and Big Data both have non-volatile memory. Thus, the previous data never gets replaced or deleted even when the new data adds on. In the Data Warehouse, there is no chance that the operational database will impact the data in the warehouse directly. In Data Analytics, the information is stored in file format for the reference of the researcher to derive conclusions which is solely based on the previous data.

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