Advantages And Disadvantages of Data Lakehouse

• Posted by Joy Green Mar 14 Filed in Technology #Data Warehouse  #Data Lakehouse  13 views
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  Over the past fifteen years, two approaches to data management have emerged. Two types of data have emerged: the data lakehouse and the data warehouse. In the past, companies used both models for data availability and performance reasons. They had to develop two different systems and implement complex synchronization procedures. On the other hand, the “data house and data lake” is a new revolution.

  By eliminating data replication, the data lake transforms data management. It also improves data security by eliminating the need to create unnecessary security rules. To better understand the concept, it is helpful to compare Data Lakehouse with previous data management systems.

  Features And Functions

  Data Warehouse

  To meet specific business intelligence and analytics requirements, the data warehouse stores highly organized and consolidated data. Once transformed, the data is integrated into a predefined schema.

  Advantages And Disadvantages of Data Warehouses

  Advantages

  ·         Inadequate or no data processing.

  ·         Easy access for analysts and business users.

  ·         Consolidated data is the only reliable source of information.

  ·         Increases trust in data and facilitates decision-making.

  Disadvantages

  ·         Unstructured or semi-structured data cannot be stored in this format.

  ·         Increased operational costs due to additional overhead.

  DataLake

  Supports data science and machine learning through affordable archiving of raw data. Combining different formats, such as call lists and ERP transactions, to produce huge numbers. To make data available to BI and analytics tools, teams utilize data flows and schema transformations.

  Advantages And Disadvantages of DataLake

  Advantages

  ·         Managing and storing data is cheaper than working in a data warehouse

  ·         Self-service BI tools and easier access to a variety of data for data experts

  ·         Ability to perform innovative data analysis to uncover unexpected results

  Disadvantages

  ·         Potential problems with data flow and input processes

  ·         Lack of support for transactional data (ACID)

  ·         No limitations on data quality

  Data Lakehouse

  Unlike traditional data lakes and data warehouses, this solution offers flexible tenancy. It provides cost-effective storage, eliminates data redundancy, and improves data quality through form and schema development. ETL processes are required to connect the integrated data warehouse and unstructured data storage tier. The concepts of budgeting, segmentation, and structuring the data layer are used to ensure data quality and ease of data access.

  Advantages And Disadvantages of a Data Lakehouse

  Advantages

  ·         Compared to a multi-solution system, a single data lakehouse requires less time and resources to manage.

  ·         Reduced data storage costs.

  ·         All data is directly accessible to BI and machine learning tools.

  ·         Direct access for all users reduced redundancy and data transfer.

  ·         Simplified forms management.

  ·         Data management is simplified with a single point of control.

  ·         Support for ACID-compliant transactions.

  ·         Increased productivity during the development phase.

  Disadvantages

  ·         Potentially limited functionality.

  ·         Concept is underdeveloped.

  Comparison Between Data Warehouse, Data Lake and Data Lakehouse

  Although data warehousing is more complex, it is easier to utilize data in a data warehouse. In contrast, a data warehouse makes it easier to collect and store data but can be challenging to use and retrieve. A data warehouse is a better option when there are several different data sets, some of which are better suited for the first option and some of which are better suited for the second option. A data warehouse is a system that stores all data in one place, providing organized storage for some types of data and unstructured storage for others.

  Conclusion

  With a data warehouse, you can collect and update data in one place. Combining the benefits of data lakes and data warehouses, a data warehouse is secure and provides quick access to data and the use of a wide range of analytical tools.

  Data warehouses can be used to store both structured and unstructured data. With an adaptive data warehouse architecture, all measurement parameters can be easily retrieved and analyzed to evaluate new theories.

  Data warehouses are an option that should not be overlooked if your company wants to take advantage of the latest technologies to create practical solutions based on data analytics.