The project is to integrate the data coming from different sources to snowflakecloud data warehouse.

The project is to migrate the existing data warehouse from on prem Netezzadatabase to Snowflake Cloud Data warehouse. This is as is migration of sameschema from Netezza to Snowflake.Integrate the existing sources and Develop an automated solution to reconcile thedata from different relational sources to Snowflake.

The existing Datawarehouse in Netezza to be migrated to Snowflake . In this project we have used Snowflake hosted in AWS , Linux machine to develop the python script , AWS S3 to load the data files extracted from Netezza . Snowflake Datawarehouse is a Datawarehouse as a service provided to focus on using data not managing. It is a Multi cluster shared data architecture with separated storage and compute.

To extract the data from Netezza an external table is used to unload data to files and those file split in too few MB/GB files depending on size of table in Netezza and uploaded to S3 and then copied to snowflake using COPY command. Initially database and schemas are created in Snowflake by extracting the DDL

The Cassady Remote Configurator is a platform to store the Configuration data of multiple controller’s configuration data in cloud and synchronize with OIP IoT platform that contains telemetry data. The Azure database for PostgreSQL (Paas) is used to store the controller data and azure web job, EventHub, Blob services is used to facilitate the D2C and C2D paths to synchronize the data between controller and remote database.

The project focuses on building a cloud solution to sync device configuration datafrom various controllers providing water hygiene and energy technologies. Thisinvolves syncing C2D and D2C messages by integrating IoT components like IoTHub, Event Hub and Azure database for PostgreSQL.

The Data warehouse is developed extracting data from different Oledb sourcesand File systems. The Requirement from business is they initiate a project insource systems and forecast the resources for the project. The Source systemsalso contain the ongoing Project data and the resources working for the project.The data from all the source systems are brought at one place called datawarehouse which contain the data elements pertaining to an entity. The SVOT(Single Version of truth) and PNR (People Number Report) Reports are generatedfrom data warehouse for the business users. SQL server is used for storing datawith SSIS ETL tool for integration and SAP Business objects for reporting

The Project is developing a FATP (Finance and actuarial transformation Program)data warehouse. It is divided into two modules GRIP and Reserving. GRIP (Gross &Reinsurance Process) which mainly deals with data of ongoing process of thebusiness. Reserving is the process where the GRIP data is analyzed and stored tohandle the Solvency. Solvency is the amount of risk that can be handled duringdisaster. FATP is initiated as part of its Solvency Smart initiative to provide afundamental shift in their ability to improve its reporting capabilities inaccordance with the regulation by utilizing a combination of technology solutionsand enhanced efficiency in the actuarial reserving and financial reporting processto reduce report generation time lines and increase emphasis on analytic andunderstanding business results.

The BI Project is extracting data from trade system using ETL solution and provides business users in business intelligence to analyze the trade exceptions. The SQL server is used to store the data, SSIS (SQL server Integration services) ETL is used to transform the data in business needs and SSAS (SQL server Analysis services) provides the data in multi-dimensional view to analyze. Similar way trade data is extracted from file system and provide business users in business intelligence to analyze the movement of trades through different systems and same tools are used as mentioned above. Jasper reports developed from I report tool to be integrated in framework developed using Java to support the similar way as reporting tool as UI.

The Project is developing a FATP (Finance and actuarial transformation Program) data warehouse. It is divided into two modules GRIP and Reserving. GRIP (Gross & Reinsurance Process) which mainly deals with data of ongoing process of the business. Reserving is the process where the GRIP data is analyzed and stored to handle the Solvency. Solvency is the amount of risk that can be handled during disaster. FATP is initiated as part of its Solvency Smart initiative to provide a fundamental shift in their ability to improve its reporting capabilities in accordance with the regulation by utilizing a combination of technology solutions and enhanced efficiency in the actuarial reserving and financial reporting process to reduce report generation time lines and increase emphasis on analytic and understanding business results.

The BI Project is extracting data from Centralized Storage of Odeon Cinema transactional data using ETL solution to create exporting financial data and transforming into the required export format which can be consumed by the AMC Oracle system. The SQL server is used to store the data, SSIS (SQL server Integration services) ETL is used to transform the data in business needs. SSIS Solution is developed in a way it accepts different parameters dynamically to generating finance report of individual cinema that can be used to reconcile against their finance system.