Data Warehousing Services
Data warehouse services include advisory, implementation, support, migration, and managed services to help companies benefit from a high-performing DWH.
Since 2005, ScienceSoft helps its clients consolidate data in an efficient DWH solution and enable company-wide analytics and reporting.
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What Makes ScienceSoft a Trustworthy Partner
- Data warehousing services since 2005.
- Data analytics expertise since 1989.
- Designing and implementing business intelligence solutions since 2005.
- A dedicated team of DWH solution architects, data engineers, DevOps specialists, database administrators, QA specialists.
- Expertise in delivering complex and large-scale solutions (incl. real-time data warehouses) for 30+ industries.
- Quality-first approach based on a mature ISO 9001-certified quality management system.
- ISO 27001-certified security management based on comprehensive policies and processes, advanced security technology, and skilled professionals.
Data Warehouse Services by ScienceSoft
Data Warehouse as a Service
ScienceSoft rents out a full-scale data warehouse integrated with your existing BI and analytics infrastructure on a subscription fee basis.
ScienceSoft’s team takes on:
- Data warehouse configuration and development.
- Data warehouse integration with the existing infrastructure (data sources, BI and data analytics infrastructure).
- Data migration and data cleaning.
- Continuous support and administration of the data warehouse.
- On-demand data warehouse configuration.
Data warehouse advisory services
Our data warehouse advisory services may include:
- DWH solution design:
- DWH requirements engineering.
- Business case creation.
- DWH solution architecture.
- DWH tech selection, outline of the optimal cloud data warehouse platform and its configuration*.
- Data governance design for data quality, availability, and security.
- Data modeling, ETL/ELT design, etc.
- DWH implementation/migration/optimization plan.
- Consulting support or complete project management.
* Start with a free guide to data warehouse selection by ScienceSoft to make the right technology choice.
Data warehouse implementation
ScienceSoft’s team builds a DWH tailored to your unique data consolidation and storage needs and implements it into your ecosystem.
We offer:
- Data warehouse requirements engineering.
- Data warehouse solution conceptualization and platform selection.
- Data warehouse solution architecture design.
- Data warehouse system analysis.
- Data modeling and ETL/ELT design.
- Data warehouse solution development.
- Data warehouse quality assurance and launch.
- Data warehouse after-launch support.
Data warehouse migration
ScienceSoft helps you optimize DWH performance and lower total cost of ownership by moving your existing on-premises data warehouse to the cloud with no business process disruptions.
ScienceSoft helps you migrate your legacy DWH solution to the cloud or build a hybrid data warehouse by:
- Outlining a migration strategy and a plan.
- Designing a cloud data warehouse architecture.
- Assisting in selecting the right cloud vendor*.
- Configuring the cloud cluster in a way to optimize costs.
- Redeveloping a data warehouse on a new platform.
- Integration of cloud and on-premises environments.
- Transferring both master data and metadata to the new data warehouse.
- Testing the completeness of data to ensure the migration’s success.
* Start with a free guide to cloud data warehouse selection by ScienceSoft to make the right technology choice.
Data warehouse testing
ScienceSoft offers a comprehensive DWH testing set, which can include ETL/ELT testing, BI testing, DWH performance testing and security testing.
ScienceSoft’s DWH testing services have the following stages:
- Studying project requirements.
- Test planning and test design.
- Test implementation.
- Result analysis and accountability.
Data warehouse support
ScienceSoft provides DWH support to help you identify and solve DWH performance issues, achieve DWH stability for timely and quality data flow for business users, lower DWH storage and processing costs.
ScienceSoft’s team offers:
- DWH solution architecture optimization.
- Optimization of individual DWH tools (keeping more data in memory, adding indexes to tune query performance).
- DWH design optimization (changing database schemas, data loading, etc.).
ScienceSoft’s Data Warehouse Portfolio
Cloud DWH and BI Solution for the Producer of Phytotherapy Products
- Consolidation of company-wide data from 5+ data sources into a cloud DWH.
- 20+ report templates to cater to different departmental needs.
- A set of user guides with the detailed information.
Cloud Data Warehouse for Big Data Analysis
- A big data warehousing solution to process 1,000+ raw data types.
- A 5-module analytics system for advertising channel analysis in 10+ countries.
- Up to 100 times faster analytical query processing.
DWH and Analytics for a Multibusiness Corporation
- 100 ETL processes to ingest structured and unstructured data from 15 sources in a data warehouse.
- An analytical server with 5 OLAP cubes and about 60 dimensions to enable retail analytics, stock management, etc.
- 90+ reports for different business directions and user roles.
DWH and an Analytics Solution for Advanced Sales Analysis
- A solution for a multinational FMCG corporation with more than 200 markets, 1 bn consumers, and 60,000 employees.
- A three-module BI solution for data unification and processing.
DWH and Analytics Solution for 500+ Nursing Homes
- An on-premises data warehouse solution to enable comprehensive standardized reporting.
- A universal 4-dimensional analytical cube.
- Role-based data access.
DWH and an Analytics Solution for a Regulatory Authority
- A centralized DWH solution and a BI module with an analytics sandbox to support experimental/development analytics activities.
- Support for 200+ concurrent business users handling over 500 reports simultaneously.
DWH and BI Consulting for an Agency with 1000+ Staff
- A concept of the solution to get data-driven insights for tactical and strategic decision-making, planning, and performance management.
- A set of detailed recommendations to consolidate disparate data sources in a data warehouse and save up to 90% of the report preparation time.
Data Warehouse Solution for Airline Market Data Analysis
- A data warehouse deployed in ScienceSoft’s data center.
- A 10-dimension OLAP cube to analyze the 10-year history of external data.
- Web-based reporting with self-service capabilities.
Data Warehouse and Analytics Solution for the Automotive Industry
- An ETL-based data warehouse with a staging area, DWH database and data marts.
- Multidimensional analytical cubes.
- 40+ customizable reports and dashboards.
The Financial Times Includes ScienceSoft USA Corporation in the List of the Americas’ Fastest-Growing Companies 2023
For the second year in a row, ScienceSoft USA Corporation ranks among 500 American companies with the highest revenue growth. This achievement is the result of our unfailing commitment to provide high-quality IT services and create best-value solutions that meet and even exceed our clients’ expectations.
Why Build Data Warehouse Solutions with ScienceSoft
With dozens of DWH projects in our portfolio, we still haven’t had a chance to say: “Oh, it’s just like that X project, remember? Let’s use it as a template!” And honestly, I don’t think this will ever be the case. Even same-industry companies face unique challenges, which requires different approaches to make data work. I believe that tailoring DWH solutions to specific business concepts and processes is what drives customer satisfaction with ScienceSoft’s services.
Technologies We Use
Our Cooperation Highlights
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TimingTo meet the DWH project timeframes and help you get ROI early, we apply the most relevant iterative software development methodologies (Agile, Scrum). |
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Service deliveryTo maximize the value of our services, ScienceSoft:
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Flexible pricing models
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Data Warehousing Services FAQs
What if our data is voluminous? Do you have experience in big data?
ScienceSoft is equally proficient in working with both traditional and big data. We have 10 years of experience in end-to-end big data services, including big data analytics and visualization.
How to ensure our employees actually use the DWH?
Making it easy to reach company-wide DWH adoption is one of our priorities. To achieve this, we design DWH capabilities with unique user needs in mind. For instance, we enable zero code reports creation for BI users with a limited tech background and ensure easy solution navigation. We also create detailed software documentation and provide training for your internal teams.
We implemented a DWH. What’s next?
After implementing a data warehouse, it’s crucial to keep it high-performing and stable and ensure its capabilities correspond to the changing needs of your organization. This is achieved through ongoing DWH maintenance (e.g., continuous monitoring and adjustment of hardware and software configurations) and timely evolution (e.g., adding new data sources, data models, and reports).
What is the difference between a data warehouse and a database?
The difference between a data warehouse and a database is in the nature of data the storages handle and the purposes they serve. A data warehouse stores highly structured, pre-processed data from multiple sources to enable its analytics via BI reports and queries. A database handles real-time operational and transactional data from one application to enable app transactions.
What are the leading DWH vendors?
According to the 2023 Forrester Wave Report, Snowflake, Google BigQuery, Amazon Redshift, and Azure Synapse Analytics are singled out as leaders and strong performers. ScienceSoft widely uses these platforms in our practice. Visit our dedicated page to learn more about their specifics.
