ALL DATA SOLUTIONS

  In the modern business environment, data is to be protected data from breaches. Keeping this in mind, major database solution providers like Oracle and Microsoft had launched various initiatives like triggers, complex queries, timestamps, and data audits. The first player was Microsoft when in 2005 it launched SQL Server Change Data Capture (CDC) with “after date”, “after delete”, and “after insert” features. A modified version, introduced in 2008 and still being usedcan monitor and capture any changes made to the SQL Server database. The functioning of the SQL Server change data capture   feature is not a complex one. All changes like insert, update, and deletemade to a SQL Server tableare captured by Change Data Capture which then enters the details of the modifications in a user-friendly relational format. Information about metadata and column structure necessary to apply changes to the target database are captured for the changed rows and stored in change tables. These tables re

  Data lakes are data storage repositories that ensure massive volumes of data in its native form – structured, semi-structured, or unstructured – can be stored for processing at a later date. In the past, data storage solutions had various components like data warehouses, data marts, and more. But now, with cloud-based platforms like the Snowflake data lake, all these are not required. Snowflake data lake   is a high-performing cloud-based solution that provides unlimited storage and computing capabilities. Users have the option of scaling up or down in data storage usage and pay only for the resources used. This is critical for businesses as there is no need to invest in additional hardware and software to meet extra storage requirements whenever there is a spike in demand. Another advantage of the Snowflake data lake   is that it has optimized computing capabilities. Even when multiple users simultaneously execute several intricate queries, there is hardly any drop in speed or perf

  ETL is the process of extracting, transforming, and loading data from multiple sources into a centralized data repository with the ETL tool being able to extract data in its native format. On the other hand, SAP is a software system that helps to process data and ensures that the ideal flow is maintained to optimize business efficiencies. The full package has ERP, database systems, application servers, and technology stacks. Multiple tasks can be performed by the SAP ETL tool. Not only does it integrate different systems and transforms data formats to match each other but also helps to move data to and from the SAP ecosystem. The SAP ETL tool   also verifies whether the value of a name has been specified. The most critical advantage here is that data can be extracted and transformed externally even outside the application. There are several reasons why most organizations in this modern data-driven environment prefer to use the SAP ETL tool. The first is that once the SAP ETL too

  Several issues are faced by organizations today in the areas of data security and safety and ramping up systems for preservation of historical data. Leading database platforms took steps in this regard by launching data audits, timestamps, complex queries, and triggers, one of them being Microsoft. It led the innovation when in 2005, it introduced the SQL Server CDC   with the “after date”, “after delete”, and “after insert” features. SQL Server CDC   captures and records all activities like insert, update, or delete that are applied to a SQL Server table. Changes made are available in a user-friendly relational format and metadata and information that are required for posting changes to the target databases are captured in modified rows. These are stored in change tables with the same structure as the columns in the tracked source tables. SQL Server CDC   also tracks and records changes in the mirrored tables with column structures that are the same as the source tables. This is exc

SAP CDS (SAP Core Data Service) is a data modeling structure that defines and consumes data models that are not on the application server but on the database server. Certain key needs are met by the powerful in-memory database of SAP HANA. These include fast real-time performance for optimized activities at the database level, quick retrieval of data, and reduced application execution time. Developers use the SAP CDS to create underlying data models and application services for exposure to UI clients as CDSView SAP. CDS View SAP   is a virtual data model of SAP. It allows direct access to the underlying tables of the HANA database. CDS View SAP   was introduced by SAP with a new programming model that focused on pushing logic from the application server to the client-side and database and is known as ‘Code -to-Data’ or ‘Code Pushdown’. CDS View SAP   gets the logic from the ABAP application and executes it on the database server instead of the application server. ABAP CDC Views are bas

The SAP Extractor is a program in SAP ERP that can be both customized or taken from a standard Data Source. It prepares and captures data through an extract structure that can be transferred to the Business Warehouse of SAP. Both the options of the SAP Extractor help to describe a delta load process or various types of full load. The SAP BW can remotely access the various data transfer activities of the SAP Extractor . For more on SAP Extractor, click here. SAP Extractor executes SAP data extraction in three ways. The first is Content Extraction used to extract BW content, FI, HR, CO, SAP CRM, and LO cockpit. The second is Customer-Generated Extraction where the SAP Extractor is used for LIS, FI-SL, CO-PA. The third is Generic Extraction which is based on DB View, Infoset, Function Modules. The SAP Extractor used for a specific extraction activity depends on the particular needs of an organization. Data capturing and extraction with the SAP Extractor is initiated with the h