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I know what is Data Warehouse & what is Big Data. But I am confused with Data Warehouse Vs Big Data. Both are same with different names or both are different(Conceptually & Physically).
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What are the differences between a database and a data warehouse? A database is any collection of data organized for storage, accessibility, and retrieval. A data warehouse is a type of database the integrates copies of transaction data from disparate source systems and provisions them for analytical use.
A data warehouse is built to support management functions whereas data mining is used to extract useful information and patterns from data. Data warehousing is the process of compiling information into a data warehouse.
Real-time data warehousing involves the continuous process of loading data into a warehouse and making it instantly available to the different business functions that require it. This is unlike the traditional data warehousing approach, where data is loaded in batches overnight or hourly schedules from source systems.
A database stores the current data required to power an application. A data warehouse stores current and historical data from one or more systems in a predefined and fixed schema, which allows business analysts and data scientists to easily analyze the data.
I know that this is an older thread but there have been some developments in the last year or so. Comparing the data warehouse to Hadoop is like comparing apples to oranges. The data warehouse is a concept: clean, integrated data of high quality. I don't think the need for a data warehouse will go away anytime soon. Hadoop on the other hand is a technology. It is a distributed compute framework to process large volumes of data. In the past data warehouses were typically built on relational databases and data warehouse appliances. However, over the last couple of years various limitations of the RDBMS have emerged (exploding license costs in the face of growing data volumes, poor fit for purpose for querying graphs and hierarchies and ingesting unstructured data types etc.). At the same time MPP SQL query engines on Hadoop have appeared such as Apache Drill that now make it possible to query data that sits on Hadoop.
I have written a whole series of posts on the subject if you are interested in all of the details. Data Warehousing in the age of big data. The end of an era?
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Maybe this viewpoint can help you: Basically Data Warehouse is an architecture, while Big Data is a technology. The first one became a well-known trend in the recent 20 years, while the latter one gained popularity only in the last decade.
Big Data and Data Warehouse are both used for reporting and can be called subject-oriented technologies. This means that they are aimed to provide information about a certain subject (f.e. a customer, supplier, employee or even a product). Data Warehouse is more advanced when it comes to holistic data analysis, while the main advantage of Big Data is that you can gather and process information from almost all well-known sources (f.e. social media or even specific machine data).
More here gbksoft.com/blog/big-data-and-data-warehouse/
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