Abstract Modern ETL tools should be capable of extracting data from different sources like RDBMS, Flat files, Cloud Data-Stores, Data Lakes, Warehouses etc. and should smoothly build integration between them. Data transformations or pre-processing tasks have become complex because of variety of data often in semi-structured or un-structured form. Data pre-processing tasks are now preparing …
Amazon SageMaker Autopilot automatically builds, trains, and tunes the best machine learning models based on your data, while allowing you to maintain full control and visibility.
Lots of data in petabyte scale is generated every moment and to analyze these data quickly is getting tough for organizations. Streaming data makes the job even more complex. AWS comes with a solution called Kinesis, which is capable to collect, process and analyze real-time streaming data, so that we can get timely insights and react accordingly.
Power BI is emerging as a leader in the Business Intelligence Tools domain. It provides interactive visualizations and business intelligence capabilities, which is simple enough for end users to create reports and dashboards.
Abstract Data pipeline is a set of operations, starting from getting data, transforming them and moving them to required destination for process and analysis. In Amazon we have Redshift, a petabyte scale data warehouse, where the data is stored for faster analysis. Data can be moved to Redshift swiftly from Amazon S3 with copy command …
Automate Data Pipeline with Glue, Lambda and CloudWatch Read More »
Abstract Database Administering of MS SQL Server can be done using many tools and utilities. One of them is SQLCMD command line tool used in a non-graphical interface medium. Since SQL server is also available in Linux this command line tool (SQLCMD) is available Bash as well as PowerShell. Window Subsystem Linux (WSL) also can …
Connecting SQL Server using Sqlcmd and Bash Script Read More »
ABSTRACT Data warehouses, also known as online analytical processing (OLAP), store data that has strict data types that conform to a schema with rows and columns in a denormalized table. Data warehouses are designed for analytic processing to help business with decision making. The way that the data is stored is optimized for speed and …
