Even though the journey has the same goal, big data vs data warehouse has quite prominent differences. Big data vs data warehouse aims to provide business value through data analysis. However, both have different scopes. To understand both, you need further explanation as below.
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Big Data Vs Data Warehouse? Here are the definitions and differences
A data warehouse is a database created specifically to carry out query processes, analysis and creating reports. This stored data is business history data from a company or organization where this data is not stored in detail.
So, data can last longer. This will be different from Online Transaction Processing aka OLTP data which is stored until the process runs completely. Data sources in a data warehouse come from various types of software, platforms, different networks and formats.
This data is the result of the organization’s or company’s daily transaction processes. Because the sources are different, data must be stored in a standard format. The four main characteristics of a data warehouse are integrated, non-volatile, subject oriented, and time variant .
So What is Big Data?
In the discussion of big data vs data warehouse , big data is a large-scale collection of data that cannot be processed with ordinary conventional tools.
Therefore, this process requires new tools to obtain value from the data obtained. The method is by clustering , stored in data warehouses and partitions. Along the way, big data has three supporting dimensions that are known to the public. Namely, Velocity, Volume and also Variety .
Striking Differences between Big Data and Data Warehouse
In summary, if a data warehouse has a data storage architecture (data repository), then Big Data is the technology that handles and prepares this repository.
Data warehouse accepts limited DBMS data while Big data accepts almost all types of data. Including social media data, DBMS, machine data to transactional data.
Data warehouses are suitable for processing structured data, while Big Data is generally more suitable for processing large and complex data.
Data warehouse focuses on historical data or business needs, while big data focuses on storing data.
Big data handles structural, semi-structural and non-structural data, while data warehouses only handle relational and irrational structural data.
That’s a brief review of big data vs data warehouse . Hopefully this information can broaden your insight.