Sam started his startup and over the years the startup has brown big and become an enterprise with multiple outlets at multiple global locations. As Sam’s enterprise has grown there are multiple departments which were created to handle multiple operational activities based on the geographical location. Every department has its own database and that is working as it is expected and the data is used only with in the enterprise. Let’s consider these individual department’s databases as Data Mart.
Sam is getting the reports from multiple locations on the sales and the profits and losses. Obviously, that is not the best way to do and there is a lot of manual wok which has to be done to consolidate the reports and do the manual calculations and send out the report.
Now to have a single view of the report from various departments for sales, marketing or making plans for any strategic questions for the enterprise there should be a common place where all the data is residing to do multiple slicing and dicing for answering the business questions without any manual work and to get the data/reports as soon as possible. Let’s consider this common place as Data Warehouse, where we have all the consolidated data.
Enterprises can achieve this single view or the report or for that matter to do any Data Mining there are two options which is a Data mart or a Data Warehouse. Let’s understand what the difference between data warehouse and data marts and how they can be compared with each other.
From the scenario, we have taken a data warehouse is a collection of data marts representing historical data from different departments of the enterprise. This data is stored in relational databases and optimized for querying and data analysis as a data warehouse.
A data warehouse can also be viewed as a relational database for historical data from different departments within an enterprise. This is the place where all the data of a enterprise is stored.
Coming to the Data mart, it’s a segment or part of a data warehouse that can provide data for reporting and analysis on a section, unit, department or operation in the enterprise, for example e.g. sales, payroll, production, invoices, customers etc.
Data marts are sometimes (based on the design) complete individual data warehouses which are usually smaller than the enterprise data warehouse. It is an indexing and extraction system. Instead of putting the data from all the departments of an enterprise into a warehouse, data mart contains database of separate departments and can come up with information using multiple databases when required.
By now, you would have understood that the Data Marts are for smaller departments and Data Warehouses are for combined departments.
It is important to note that there are huge differences between these two options though they may serve the similar purpose. Primarily, data mart contains programs, data, software and hardware of a specific department of an enterprise. There can be separate data marts for finance, sales, production, logistics, finance or marketing. All these data marts are different but they can be coordinated or combined based on the need. Data mart of one department is different from data mart of another department, and though indexed, this system is not suitable for a huge data base as it is designed to meet the requirements of a particular department.
Data Warehousing is not limited to a particular department and it represents the database of a complete enterprise. The data stored in data warehouse is more detailed though indexing is light as it has to store huge amounts of information. It is also difficult to manage and usually takes a longer time to process.