Is Big Data Replacing Data Warehouse?
Since both Big Data and Data Warehousing are having similarities between them but at last they are two different terms with huge difference.
Today Big Data is one of the latest revolution when it comes to Technology. One question is frequently raised by people that will Big Data be replacing Data Warehouse?
Since both Big Data and Data Warehousing are having similarities between them but at last they are two different terms with huge difference. To be specific Big Data is a data solution which completely works on volume, velocity and variety. Wherein Data warehousing is about architectural concepts embedded in data computations.
Talking about the Big Data vs Data Warehousing. Here are some points which will exactly tell us about the comparison of both technologies –
It is extracting data from Structured Query Language (SQL) based data and make use of it in making analytic reports in form of definition, data repository which is been generated from a process known as data warehousing.
It stands on Volume, Variety and Velocity. Volume defines the amount of massive data coming from different sources. Variety refers to number of types of data which mainly supports all type of data format and Velocity refers to the speed by which data is processed.
What are the Preferences?
If any organization wants to know their future predictions on their current year performance, they prefer to go with data warehousing. For which they will be needing the reliable data from sources.
If an organization wants to compare with a massive amount of data, which will make them to take better decisions in terms of more profitability, how to increase revenue, customer attraction. In such cases they will always prefer Big Data.
Are they Subject Oriented?
Yes, It is subject oriented because, it keeps the capacity of providing information which is actually specific to subject like customers, products, suppliers, revenue, sales and etc. but not on the ongoing operations in organizations. It mainly focuses on displaying data which actually helps in decision making.
It is subject oriented too, only the difference is about source of data. Big Data can accept and process data from all sources inclusive of social media, machine or sensor specific data. It also focuses on providing exact analysis on data specifically.
Data collected in a data warehouse is actually identified by a time period and it mainly holds historic data for analytical report.
It has a lot of approaches to be identified in the already loaded data, a time period is one of the approaches. It mainly processes flat files, so archives with time and date are the best approach to identify the loaded data. It also have the opinion to work with streaming data, so it does not always hold historical data.
It manages specifically Structured (Relational data.)
It accepts all types of formats. Structured data, relational data also unstructured data including emails, video, audio, text messages, stock data and financial transactions related data.
Previous data is never erased whenever new data is added on, which is one of the major function of Data Warehousing. And as it is totally different from operational database, so any changes made on an operational database won’t be having any direct impact on the data warehouse.
Again previous data do not get erased on adding new. But here in some case of streaming, directly use Spark or Hive as an operational environment.
So what’s the Conclusion?
After comparing the differences and some similarities from the above respective points, we can come down to a bottom line that – they are not same and therefore are not interchangeable at all. Therefore we can say that Big Data will not be replacing Data Warehouse. Organization has to work on what exactly they need, Big Data or Data Warehouse or ultimately the Combination of both!