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    Data warehouse (DWH)

    Data warehouse (DWH)

    A centralized data warehouse where necessary analytical data is gathered from various data sources

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    Collect, Control, Manage
    Infallible information for analytics
    Infallible information for analytics

    A unified, reliable data source is created in the company, where the quality of the required data is normalized and recorded in a format convenient for analytics. As a result, the amount of data useful for analytics increases

    Independence from accounting software
    Independence from accounting software

    It is possible to collect data from various internal accounting or external sources in the database and as a result, the company has the opportunity to observe trends that would be impossible within a particular software

    More time for analytics
    More time for analytics

    Data in the warehouse is updated in automatic mode. Data analysts no longer have to spend resources on their unification processing. Analysts are encouraged to concentrate on analytical activities instead of routine

    System Architecture

    Unified Data Warehouse is a key part of a Data Management System. Data Warehouse combines the amount of data collected from different sources needed to solve further analytical tasks. The warehouse may combine data from the company’s internal accounting software, as well as from external statistical or analytical sources.

    Before being stored in a warehouse, the data is transformed in a way that it can be used for mathematical manipulations and various analytical processing; Both directly in the database and through various analytical Business Intelligence tools.

    System
    The stages of Data
    The stages of Data Warehousing

    The process of creating a Data Warehouse involves collecting, processing, and organizing data from various sources so that the received database responds to business analytics tasks. The process consists of the following main stages:

    1. Determination of analytical tasks and relevant necessary data
    2. Identification/study of data sources
    3. Infrastructure Preparation (server and software licenses)
    4. Definition and development of data storage architecture
    5. Setting up an ETL data exchange process
    6. Data processing, processing for analytical purposes
    7. Ensuring data security and optimal performance
    The stages of Data
    Interested in more about data storage?
    Interested in more about data storage?
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    Advantages of Data Warehousing

    Data warehouses unlike specific software:

    • Enables opportunity of historical analysis – all the historical data in the organization is placed in one common warehouse, which makes it possible to analyze the whole history as a result of a relationship with one source.
    • Increases scaling – Data warehouse architecture and related infrastructure allow you to store large period and volume data using minimal resources of server infrastructure.
    • Increases the relevance and quality of data – With the placement of data in a shared warehouse, data is transformed and processed, which increases the consistency and quality of the data.
    Advantages of Data
    Advantages of Data
    Advantages of Data Warehousing
    • Interacts with Local and Cloud Warehouses – When creating and interacting with data storage, it is possible to use both local and cloud sources and tools, as well as hybrid options
    • Meets more analytical requirements – When it comes to data warehousing, its architecture increases the productivity of the SQL Query programming language and the ability to retrieve large amounts of data in an optimal format.
    • Increasing Human Resources’ Efficiency – Data placed in a unified space is easy to use if necessary because the time of addressing and processing them is reduced.
    Advantages of Data
    The Head of the Data Laboratory

    Irma has held various leadership positions, including as Lean Transformation Coordinator, IT Portfolio Manager, and Agile Coach. Lean Management was introduced in Georgia together with the consulting company Mckinsey & co and a local team, both in the front office and in the back office.

    Irma Berdzenishvili

  • IBerdzenishvili@bdo.ge
  • +995 32 254 58 45
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