Data persistence layer(12/1/2020)

 When it comes to management and figuring out how to run a data tool, think of it as a warehouse or retail store front in this sense. This in particular is how a Data presistence layer works. When it comes to a DPL you will have 6 different methods were you must go through in order for to the data to reach its finally desistation. these different methods are considered to be semantic, Data Warehouse, presistent, transform, staging, and finally source. to be more specific a presistent layer contains a set of tables that are in charged of gathering and recording information. This is done so we understand the full history in etor spect of changes to the data of the table or query. infact when it comes to having multiple source, table or query files they are allowed to be staged at a different table or in a different view inorder to meet the transfer layer requirements. Something crucial to learn about a DPL is that in many cases you can consider it a bi-temporal table.You might be wonder to yourself what is a bi-temporal table is? well it is considered to be a table that permits queries with a size of two or larger to be stored in. This all comes down too how useful DPL is. With DPL you are allowed to include and store all of the history you need all of the time instead of how many other software do it where you have a break up of history and information when needed the most. As well this will save you a tremondce amount of time do to the flecability to be able to drop and rebuild your data set with the same amount of data history at any point in time. DPL as well offered ETL performance which is considered to be where you are allowed to make changes to to the process data. When it comes to DPL, DPL is aware of what has been altered and when it has been altered in order to make the appropriate changes in the data set. The main reasoning behind switching to a data persistence layer is mainly for the reason of allowing you to be able to analyst data in a timely manner while still staying accuarete. This also allows you to have add ons like churn or other third party software to boost the persistence layering unlike like other data processesers. Another feature is the ability to have evidence for example presistanent layering will give you information that will point directly too and explain why something has changed. As well it gives you the power of auditing where you are able to orginiaze, maintain, complete an accurate picture of past event to understand what truly happened in the data.