Data Work

A data lake is a storage repository that is highly scalable and flexible and holds massive volumes of data. Further, data lakes can hold data in its native format, whether unstructured, semi-structured, or structured. Thus, organizations that need to store huge volumes of data in any form prefer data lakes. Snowflake, a fully secured and high-performing platform, has all the attributes of both a data warehouse and a data lake, and hence, businesses prefer the Snowflake data lake as their main data storage system. The Snowflake data warehouse function can be used for storing data in AWS S3, Microsoft Azure, or Google Cloud Storage and make data analytics and data transformation faster.  There are several benefits of the Snowflake Data Lake. It can hold data in any format along with structured data such as CSV, Parquet, JSON, and tables. It has high computing powers and the performance of the Data Lake is not impacted even when multiple users simultaneously execute multiple queries. A

A program in SAP ERP, the SAP Extractor is widely used for extracting and customizing data from any standard source. This process is done through an exact structure that can be moved to the SAP BW (Business Warehouse). The Extractor also describes a delta load process or multiple types of full load with the SAP BW even getting remote access to the data transfer abilities of the SAP Extractor . The process of data extraction is started by the SAP Extractor with help from several application-specific extractors. The data is then hard-coded for the Data Source and sent to the BI Content for BW. The Extractor is designed in a manner to match the structure of the Data Source. SAP data can also be extracted from the source systems and transferred to the SAP Business Warehouse through generic extractors. The reason why the SAP extractor can easily recognize which data should be extracted and from which tables the data is to be read once the Data Source is identified by the generic extractor

A View may be defined to be a projection of several entities and it is possible to create an SAP CDS V iew as a design-time file in the storage repository of the SAP HANA Extended Application Services (SAP HANA XS). The SAP CDS View was first launched by SAP as a programming model in-built into SAP HANA. It enables direct and seamless access to the underlying tables of the HANA database. The objective here is to facilitate logic from the application server to the client-side database named ‘Code-to-Data’ or ‘Code Pushdown’ by SAP. Later, this logic can be extracted by the SAP CDS V iew from the ABAP applications and executed on the database. In the past, typically the application server and not the database server has been used for data modeling. After SAP introduced a new infrastructure for data modeling done at the database level using Core Data Services (CDS), popularly termed SAP CDS V iew, there were several benefits that can be leveraged now. Here are some of the benefits of

A cloud-based platform, the Snowflake Data Lake is a data warehousing solution that offers unlimited storage and computing facilities. It is a pay-as-you-use service and businesses can scale up or down in usage of storage resources by paying only for what is availed. Thus, when faced with a sudden spike in demand for storage resources customers of the Snowflake Data Lake do not have to invest heavily in additional software or hardware. Features of the Snowflake Data Lake There are several cutting-edge and advanced features of this cloud-based platform. ·         Scalability and Flexibility: The dynamic and scalable computing resources of Snowflake vary based on the current volume of data requirements and the number of users. Whenever there is a change in the computing requirements, resources are generated automatically without affecting running queries. This is because the compute engine auto-adjusts to the increased flows without a drop in speeds or performance. ·         Single-poi

In April 2020, SAP launched the SAP HANA Data Lake with the goal of strengthening its existing data storage capabilities and offering customers an affordable storage system. Included were an SAP HANA native storage extension and SAP Data Lake. From the very introduction of this system, several cutting-edge capabilities were added to this package. This led to the SAP Data Lake of the SAP IQ cloud-based system being considered at par with other competitors such as Microsoft Azure and Amazon Simple Storage Service. The structure of the SAP Data Lake is unique and is unlike other data lakes. It resembles a pyramid that is segmented into three parts. The top section holds data that is critical for businesses and is accessed regularly and processed for daily operational requirements. This is vital data often referred to as hot data and the cost of storing it in the SAP Data Lake is the highest. The middle of the pyramid is for storing data that is infrequently used but not as unimportant a

In the modern data-driven business environment where massive volumes of data have to be processed for analytics, it makes sense to migrate databases to the cloud. One of the ways to do so is to migrate databases from on-premises Microsoft SQL Server to S3 , the cloud-based service of AWS (Amazon Web Service). One of the main advantages of moving databases from SQL Server to S3 is that during the process the source database remains fully functional and there is no need for downtime. This is very helpful for large organizations for whom shutting down systems even for brief periods might upset operating schedules. Further, this form of migration is also very useful for migrating database code objects including views, storing procedures, and functions as a part of database migration. Data migration to S3 can be carried out regardless of the size of the SQL Server and can validate the target database during the replication of data from the source to the target. A lot of time is thereby sav