Modernize your Digital Backbone with Coforge’s ModXpress

ModXpress
Coforge’s ModXpress is a completely Cloud-based solution that uses services like AWS, Azure, and open source services with legacy on-premise Data Warehouse and migrates data into Cloud Database/ Data Warehouse in an automated and configuration driven manner.

Data Studio
Coforge’s Data studio enables you to modernize your Digital Backbone, monetize your Intelligent Connected Experience and manage your Intelligent Operations. Our assets shorten time-to-market for new launches, cut development costs, and provide access to the latest technology-based innovative solutions with the least learning curve.

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Before modernization
Organizations today are facing a complex data landscape. Information is exchanged in ever-growing volumes with customers and business partners. Websites and social media platforms are constantly adding data to the mix. There is even more data coming from new sources such as the Internet of Things (IoT) via sensors and smart, connected devices.

The increase of data source is leading to a muddled architecture, where it is difficult to extract the data on stipulated time leading to increasing difficulty to grapple with emerging business demands.

Need for Solution
•    Increasing    expectations,    both internally and externally
•    Constant need for changing compliance
•    Growing demand for accessible data

Why Modernize your Data Warehouse/repositories?
•    Data Warehouse Modernization is the first step to transform your legacy systems into modern machines for a faster process. It supports the product and feature releases with quicker and better data warehouses.
•    It delivers faster and self-serviceable business insights within seconds of your request.
•    The new data warehouse system can save the organization's expenditure and unearth the potential value of the data assets.
•    It is empowered with seamless business
•    insights that eliminate unnecessarily
•    processes and focus on making crucial business decisions.
•    Modernizing or moving your database repositories to a cloud ecosystem can significantly reduce OPEX & CAPEX
 

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How to modernize your Data Warehouse?
•    Identify what needs to be migrated
•    Schema creation of target table based on Teradata table structures
•    One-time load of large volumes of data from Teradata to target data warehouse
•    Daily schedule source data ingestion to cloud using reusable common framework
•    Transform SQL/logic, Native DB scripts

How to modernize your Data Warehouse?
•    Identify what needs to be migrated
•    Schema creation of target table based on Teradata table structures
•    One-time load of large volumes of data from Teradata to target data warehouse
•    Daily schedule source data ingestion to cloud using reusable common framework
•    Transform SQL/logic, Native DB scripts
•    Continuous reconciliation of data, schema and business consistency
    Continuous reconciliation of data, schema and business consistency

The Business Value
•    70% - Reduced licensing Cost
•    10x - Move Data Faster
•    30-40% - Reduction in overall cost

Delivers enhanced business intelligence
By having access to information from various sources from a single platform, decision-makers will no longer need to rely on limited data or their instinct. The DWH and data repositories are effortlessly applied to a business's process.

Enhance data quality and consistency
A data warehouse converts data from multiple sources into a consistent format leading to more accurate data, which will become the basis for concrete decisions.

Process optimization
It accelerates rollouts and updates, with easy-to-use tools for developing data warehouse designs and data warehouse
implementations.

Generates high return on investment
It reduces migration efforts and costs, thereby creating a significant experience for the organizations by increasing the productivity gains with automated migration tools.

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Technical Details

Coforge’s ModXpress Use Cases
Database modernization- It modernizes data and database migration from on-premise to cloud environment, which reduces Capex and Opex, enhancing application performance.

DWH (Data Warehouse)
Modernization- It gives wings to on- premise DWH by modernizing to AWS (Redshift, Redshift spectrum, or Aurora) or Azure (SQL Server, Synapse etc.). It reduces cost and improves performance by upgrading the appliance DWH solutions.

Data Archival- It archives application data in cost significant passive data repository (e.g. AWS glacier or Azure BLOB). Storage is ten times cheaper than any on-premise or cloud solution. Archival is scheduled on an event basis or at regular intervals.

Data protection- It replicates and backup data to Amazon S3 or Azure BLOB for online copies archived to standby file system. DataSync transfer tasks are always incremental, which only transfers the altered data.

Multi-cloud data interchange- It moves data into or out of AWS/Azure for processing when working with systems that generate data on-premises or on another cloud. It also helps to speed up critical hybrid/multi-cloud workflows across many industries.

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Key Features
Coforge's ModXpress platform helps to achieve data warehouse and data repository modernization by streamlining and automating processes from end to end. Modernization may involve in-memory databases, in-database analytics, real-time functions, and data federation or virtualization. From designing the warehouse to generating ETL code or quickly applying updates, it helps to develop more effective business intelligence projects.

Automatic Schema Conversion
The Schema Conversion Tool makes heterogeneous database migrations predictable by automatically converting the source database schema and most of the database code objects, including views, stored procedures, and functions, to a format compatible with the target database. The items that cannot be automatically converted are marked to be manually converted to complete the migration.

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Automation of Data Migration
It enables the passing of connection information dynamically. It eliminates the need to create multiple linked services for accessing servers with many databases. The tool recognizes XML elements and attributes and automatically creates mapping documents. It successfully processes all the files generically, automatically analyzing and mapping multiple fields to the new database.

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Data Mapping
Enterprises today collect information from an array of data points. Hence, data mapping is used to map data fields from a source file to their related target fields to establish relationships between separate data models. Depending on an enterprise's data management needs, data mapping is used to accomplish a range of data integration and transformation tasks.

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Data Governance
The ETL (extract, transform, load) testing ensures data transfer from heterogeneous sources to the central data warehouse adhering to ransformation rules and compliance with all validity checks. It helps to identify the area of discrepancy and sorts the duplicate records.

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Key Customer Success Stories

Legacy DW Platform Modernization to AWS Redshift
A leading UK based Media company moved a large Oracle based DW Platform to AWS Redshift in x months, leveraging Coforge's Modernize Studio saving.

Azure based Serverless Data lake
UK's Communication regulator could set up an Azure-based serverless data lake swiftly, leveraging Modernize Studio's template-based pipeline build approach. It enabled the regulator's data scientists to work on large volumes of data to predict call drop occurrences.

Legacy DW Platform Modernization to Azure Data Lake & SQL DWH
APAC based retail bank has decided to move from Oracle based on- prem DWH system to Azure Data Lake and DWH to cater growing demand of information from business, built analytics use case and source new data sources (structured/unstructured).

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