Data warehouse historization

  • Data warehouse solutions

    What is Metadata? Metadata is simply defined as data about data.
    The data that is used to represent other data is known as metadata.
    For example, the index of a book serves as a metadata for the contents in the book.
    In other words, we can say that metadata is the summarized data that leads us to detailed data..

  • How data warehouse design is being created?

    What Are the Steps in Designing a Data Warehouse? The first step is determining the business needs, goals, and expectations surrounding the data warehousing project.
    Here, the team explores the data sources and the overall security level while aiming to understand the users..

  • How do you maintain data warehouse history?

    Type 1: Overwrite old data with new data.
    This is appropriate when historical data is not important and only the most recent data is needed.
    Type 2: Add new rows for new data.
    This is appropriate when it is important to maintain historical data and track changes over time..

  • How do you maintain historical data in a data warehouse?

    Type 1: Overwrite old data with new data.
    This is appropriate when historical data is not important and only the most recent data is needed.
    Type 2: Add new rows for new data.
    This is appropriate when it is important to maintain historical data and track changes over time..

  • What is data warehouse architecture?

    Data warehouse architecture is an intentional design of data services and subsystems that consolidates disparate data sources into a single repository for business intelligence (BI), AI/ML, and analysis..

  • What is data warehousing architecture?

    Data warehouse architecture is an intentional design of data services and subsystems that consolidates disparate data sources into a single repository for business intelligence (BI), AI/ML, and analysis..

  • What is historical in data warehouse?

    Historical data, in a broad context, is data collected about past events and circumstances pertaining to a particular subject.
    By definition, historical data includes most data generated either manually or automatically within an enterprise..

  • What is historized data?

    You can historize an entity to keep track of data changes and enable browsing this entity data at any point in time.
    You can historize Golden Data for all entities, and historize Master Data for ID and Fuzzy Matched entities.
    Historization is configured when you create or alter an entity..

  • A data warehouse architecture consists of three main components: a data warehouse, an analytical framework, and an integration layer.
    The data warehouse is the central repository for all the data.
    The analytical framework is the software that processes the data and organizes it into tables.
Aug 4, 2020Warehouse facts are inherently historical since transactions happen on a transaction date, balances are kept on a balance date, and so on. The 
A data warehouse is ideal for centrally storing all internal and external data sources. The standardization of structured, unstructured and semi-structured data enables faster and more reliable reporting. Historization allows additional reports and past reports can be reconstructed at any time.

Scenario 2

We can use Data Flows to build historization. With scheduled Data Flows, we can build a history of data of different granularity

Scenario 3

We can now use basic data modeling to gain insights about data changes

How does a data warehouse track changes in a dataset?

Tracking the changes in datasets is one of the core functionalities of any data warehouse

The most common form of historization is called slowly changing dimension type 2 (SCD2)

Instead of simply overwriting changes in a dataset (which is a type 1 historization), validity dates are used to identify the time range in which a data set is valid

Is it possible to have data historicized within a data warehouse?

It is possible (or even a core functionality) having data historicized within a classic data warehouse

Data will be added to the data warehouse over time and it is possible to move in time over the data

If I just want to use the data lake and to have also data historicization for the business user, would this be possible?

What is a data warehouse?

The original data warehouse definition, going back to Bill Inmon, states that a data warehouse is (among other things) a “ time-variant, nonvolatile collection of data”

But what do these requirements mean in practice? Time-variant means that the data changes over time

But on which timeline?
Tracking the changes in datasets is one of the core functionalities of any data warehouse. The most common form of historization is called slowly changing dimension type 2 (SCD2). Instead of simply overwriting changes in a dataset (which is a type 1 historization), validity dates are used to identify the time range in which a data set is valid.

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