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Data warehousing services for your enterprise 


Helping businesses take better decisions with simplified access to complex data.

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Data warehousing services 

Nuvento’s Data Warehousing and Analytics services help enterprises streamline their data for quicker access and retrieval. Streamlined data helps draw insights for enhanced business decision-making. Our data warehousing solutions include internal and external functions for seamless access to the right data without any overlapping. It helps to reducerrors and inconsistencies that creep in when data is aggregated from diverse sources. 

We’re specialists in efficient data warehouse design and architecture, data warehouse migration services, data modeling, data profiling, ETL/ELT and data warehouse performance optimization solutions. And we work with best-in-class enterprise data warehouse management technologies like Matillion and Snowflake that are built for simple and efficient data warehousing, making access to complicated data easy. Our data warehousing services facilitate efficient business analysis and forecasting for smart decision-making.  

Data mart strategy development

Whether you’re looking for a “start small and grow” strategy with department-wise data marts or thinking along the lines of building a well-integrated data warehouse for your enterprise in a go, we make it happen. We evaluate your business framework and set up data models to improve your business processes and business intelligence.

Data modeling

We create conceptual structures for your business’s data objects, relational information between them and rules for each one of them. We help in building abstract models that organizes data descriptions, data semantics, and consistency of the data to ensure all data objects required by the database are accurately represented. We prepare the ground for your data warehouse.

Data profiling

Organize and sort data in the data warehouse to deliver accurate results. We examine and create useful summaries of your data to deliver a high-level overview to identify data issues, letting you ensure data quality and credibility. Profiled information helps in making better decisions. Eliminate data errors with organized data sorting and take full advantage of your data.

Data mapping

Matching data fields from one database to another for extracting business value out of your data. Simplify your data migration, integration and management processes by connecting the dots between your data sources within your data warehouse. We create a roadmap to ensure your data gets to the right destination, so your integration and migration processes yield the right results.

Extract, transform and load (ETL)

We create recurring activities for extracting data, formatting it and loading into the data warehouse system. We combine your critical data sources to unlock hidden insights needed to drive strategic business decisions that yield improved business outcomes.

Performance optimization

We carry out data warehouse performance optimization, so they run queries and updates faster. We also focus on maintaining performance by maximizing the use of data warehouse resources. We carry out complete data warehouse tuning, performance assessments, data load tuning and integrity checks for enhanced performance of the data warehouse.


DWH solution for claims operations 

A multi-line business insurance company aimed to implement a data warehouse solution for managing its claims operations. The client sought to optimize the data load mechanism to a 6-hour process two times a day.


Nuvento’s team comprising of its lead solutions architect, SQL engineers, and ETL experts assessed the requirement. They came up with a six-month redesign and optimization plan. They proposed a new design to get the ETL time under 7 hours and optimize the data model to help the report queries to be completed in 5 seconds.


The plan comprised of verifiable micro-milestones delivered every three days and verified with the business user representatives for data quality and performance. This micro-milestone-based agile model ensured timely completion and verification without surprises.

Corrected errors in the historical data

Report launch time reduced from ~60 seconds to 5 seconds

Data load reduced from 36 hours to 6 hours

Operational and maintenance tasks got simplified

Customer Success Story

A multi-line business insurance company aimed to implement a data warehouse solution for managing its claims operations. They used MS SQL server, and the source systems were a popular multi-line claims system, ERP systems, home-grown applications, AS400, and mainframe systems. They also had multiple feeds coming in from business sources and digitized forms. They had around 150 TB of data, and the ETL processes that extracted data from these sources took over 30-36 hours, as opposed to an overnight processing requirement.

Data load reduced from 36 hours to 6 hours

ETL process was redesigned and optimized

Data process was remodeled and re-sequenced

Corrected errors in the historical data

Data and analytics solutions

Analytics as a service

We enable users to organize, analyze and present information giving users actionable insights, putting them in control of the analytical insights they need. We let you gain access to descriptive, predictive and prescriptive analytics that meet your data insight needs.

Business intelligence modernization

We modernize your legacy BI platforms and deliver business insights and predictive analyses on mixed and complex data types in time. We also incorporate self-service BI and analytics for users to let them derive data-driven insights for decision-making.

Data management

Acquiring, validating, storing and protecting data and ensuring it is accessible to users, compliant to regulations and helping to maximize the benefit to the organization. We build robust data management strategies for enterprises.

Data visualization and reporting

Turning regular data into information and enabling users to make sense of it with visualizations, dashboards and reports. With our data visualization and reporting services, you can convey information quickly and effectively.


What is an enterprise data warehouse?

An enterprise data warehouse is a centralized and structured data repository, which holds the enterprise’s business data, including information on the customersThe EDW gathers the enterprise data and makes it available for analysis, business intelligence and data-driven decision making.  

EDWs contain current data, such as real-time feeds or the latest snapshots from the source systems, as well as historical data. Enterprises consistently store final, nonredundant business information in one place making it the single accessible version of truth, with regards to enterprise data.  

Why do enterprises need a data warehouse?

Data warehouses are the central data store within your company. It is the single version of truth for your enterprise dataIt systematically stores, sorts and eliminates redundancies in the data.  

Enterprise data warehouses enable enterprises to run analysis on huge volumes of data. It ensures consistency of collected data, lets enterprise make better business decisions and improve their bottom line.  

How do I know if my organization needs a data warehouse?

If your enterprise operates in a highly competitive industry, has vast amounts of data, has trouble with the integration of widely dispersed and siloed datayou could benefit from implementing a data warehouse.  

Difference between a data warehouse and a data mart?

A data warehouse centrally stores data from varied sources to provide meaningful business insights. Data in a data warehouse is extracted from several functional units. It is then checked, cleansed and integrated with the data warehouse system. Data warehouses use fast computing systems that have large storage capacities, which help it answer complex queries relating to data.  

A data mart is a focused form of a data warehouse which holds data for a specific department or line of business. It draws data from sources like an internal operational system, external operational system or the central data warehouse. It is meant to serve a specific community and is designed to meet its needs. Data marts are usually controlled department wise.  

How often should I refresh data in the data warehouse?

Enterprises must update their data warehouses regularly so that the information derived from it is current. Refresh is the process of updating the data.  

How long does it take to implement a data warehouse infrastructure?

It is possible to deliver an operational cloud data warehouse loaded with all source data in close to 8 to 12 weeks, if you have your data properly sorted and the perfect plan in place.  

How do you support system migrations?

System migrations are part of technology modernization, where the process involves transferring old IT systems to new hardware infrastructure or the cloud infrastructure.  

Whereas migrating data to data warehouse means a change in storage, database or application. In the context of extract/transform/load (ETL) processes, we help enterprises use extract, transform and load software or processes to read and extract data from sources, process it in the data warehouse and ensure optimal results 



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