Data Warehousing Consulting Services
Data warehouse consulting helps consolidate disparate data sources for analytical querying and reporting. Since 2005, ScienceSoft’s data warehouse consultants help companies implement a scalable, high-performing data warehouse or upgrade the existing one to optimize its performance and costs.
- Data analytics expertise since 1989.
- 18 years of experience in rendering data warehouse services.
- Designing and implementing business intelligence solutions since 2005.
- 10 years of big data consulting and implementation practice.
- 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.
- Expertise in 30 industries, including: manufacturing, retail and wholesale, professional services, healthcare, financial services, transportation and logistics, telecommunications, energy.
Technologies We Use
Cloud data storage
We leverage Azure Cosmos DB to implement a multi-model, globally distributed, elastic NoSQL database on the cloud. Our team used Cosmos DB in a connected car solution for one of the world’s technology leaders.
We use Amazon DynamoDB as a NoSQL database service for solutions that require low latency, high scalability and always available data.
ScienceSoft used MongoDB-based warehouse for an IoT solution that processed 30K+ events/per second from 1M devices. We’ve also delivered MongoDB-based operations management software for a pharma manufacturer.
Data warehouse technologies
Our Microsoft SQL Server-based projects include a BI solution for 200 healthcare centers, the world’s largest PLM software, and an automated underwriting system for the global commercial insurance carrier.
We use Amazon Redshift to build cost-effective data warehouses that easily handle complex queries and large amounts of data.
ScienceSoft has used PostgreSQL in an IoT fleet management solution that supports 2,000+ customers with 26,500+ IoT devices. We’ve also helped a fintech startup promptly launch a top-flight BNPL product based on PostgreSQL.
Data integration
We use Kafka for handling big data streams. In our IoT pet tracking solution, Kafka processes 30,000+ events per second from 1 million devices.
With ScienceSoft’s managed IT support for Apache NiFi, an American biotechnology corporation got 10x faster big data processing, and its software stability increased from 50% to 99%.
Data visualization
Practice
7 years
ScienceSoft sets up Power BI to process data from any source and report on data findings in a user-friendly format.
Big data
By request of a leading market research company, we have built a Hadoop-based big data solution for monitoring and analyzing advertising channels in 10+ countries.
A large US-based jewelry manufacturer and retailer relies on ETL pipelines built by ScienceSoft’s Spark developers.
Our Apache Cassandra consultants helped a leading Internet of Vehicles company enhance their big data solution that analyzes IoT data from 600,000 vehicles.
We use Kafka for handling big data streams. In our IoT pet tracking solution, Kafka processes 30,000+ events per second from 1 million devices.
ScienceSoft has helped one of the top market research companies migrate its big data solution for advertising channel analysis to Apache Hive. Together with other improvements, this led to 100x faster data processing.
We leverage Apache ZooKeeper to coordinate services in large-scale distributed systems and avoid server crashes, performance and partitioning issues.
We use HBase if your database should scale to billions of rows and millions of columns while maintaining constant write and read performance.
We leverage Azure Cosmos DB to implement a multi-model, globally distributed, elastic NoSQL database on the cloud. Our team used Cosmos DB in a connected car solution for one of the world’s technology leaders.
We use Amazon Redshift to build cost-effective data warehouses that easily handle complex queries and large amounts of data.
We use Amazon DynamoDB as a NoSQL database service for solutions that require low latency, high scalability and always available data.
ScienceSoft used MongoDB-based warehouse for an IoT solution that processed 30K+ events/per second from 1M devices. We’ve also delivered MongoDB-based operations management software for a pharma manufacturer.
We use Google Cloud Datastore to set up a highly scalable and cost-effective solution for storing and managing NoSQL data structures. This database can be easily integrated with other Google Cloud services (BigQuery, Kubernetes, and many more).
Machine learning platforms and services
Machine learning frameworks and libraries
Frameworks
Libraries
Cloud services
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.
Data warehouse design
- Engineered data warehouse requirements.
- Business case, recommendations on optimizing data warehouse implementation and operation costs.
- Data warehouse solution architecture and selected DWH platform.
- Data governance policy and design. Data governance includes:
- Data quality
- Data availability
- Data security
- Data model and ETL/ELT design.
Data warehouse development and QA
- Customized DWH platform.
- Integrated data sources.
- ETL/ELT pipelines.
- DWH performance testing and DWH launch.
- After-launch DWH support.
Data warehouse migration / optimization / evolution
- DWH migration / optimization / evolution strategy and plan.
- DWH solution redevelopment on a new platform.
- Data and metadata transfer to a new data warehouse.
- Data completeness and accuracy assessment.
- Data administration services: data quality and security rules and policies setup, new data sources integration, ETL/ELT processes adjustment.
- DWH performance control: monitoring query performance, data transformations correctness, data availability.
- DWH issues resolution.
Highlights of Our Data Warehouse Consulting Services
Multidisciplinary expertise
Our data warehouse consulting team consists of:
- Project managers.
- BI consultants.
- DWH architects.
- Data quality experts.
Effective communication
- One-to-one sessions with project stakeholders.
- Meetings with several or all stakeholders to reconcile conflicting expectations.
- Presentations of important project decisions, deliverables, risks or project milestone results.
- Cross-departmental workgroups to solve complex problems (e.g., related to data quality, master data management).
Pricing Models
Fixed price
- Small DWHs or DWHs with simple data sources.
- Short-term (up to 4 months) fixed-scope engagements.
Time & Material
- Midsize and large data warehouses or data warehouses with complex architecture.
- End-to-end DWH consulting.
Our Featured Data Warehouse and BI Projects
Development of a Cloud DWH and BI Solution for the Producer of Phytotherapy Products
- Transparent company-wide reporting and analysis.
- 20+ report templates to cater to different departmental needs.
- A set of user guides with the detailed information on the solution’s components and functions.
Migration of a Data Warehousing Solution to Facilitate Big Data Analysis
- Five-module analytics system for processing more than 1,000 different types of raw data and analyzing around 30,000 attributes.
- Up to 100 times faster analytical query processing.
Development of a DWH and Analytics Solution for 500+ Nursing Homes
- Improved analytical process and standardized reporting.
- Simplified analytical system support due to the consolidation achieved at all levels (database, SSAS, and reporting).
Development of a DWH and Analytics Solution for a Multibusiness Corporation
- Ingesting and storing structured and unstructured data from 15 data sources.
- About 100 ETL processes.
- An analytical server with 5 OLAP cubes and about 60 dimensions overall.
- 90+ reports.
Development of a DWH and Analytics Solution for Advanced Sales Analysis
- Solution for a multinational FMCG corporation with more than 200 markets, 1 bn consumers, and 60,000 employees.
- Three-module BI solution for data processing and unification.
Development of a DWH and Analytics Solution for a Regulatory Authority
- Centralized BI platform with an analytics sandbox to support experimental/development analytics activities.
- Support for 200+ concurrent business users handling over 500 reports simultaneously.
Development of a Data Warehouse and Analytics Solution for Luxury Vehicle Dealers
- Analytical system for the automotive software provider with a network of 55,000 clients in 80 countries.
- ETL-based DWH solution with a staging area, DWH database and data marts.
- Over 40 customizable reports and dashboards.
Data warehouse implementation / migration / optimization consulting
We offer advisory support or complete project management to help you:
- Implement a cost-effective DWH solution under set time and budget.
- Migrate your legacy DWH solution to the cloud to achieve dynamic scaling of the DWH infrastructure and optimize DWH performance and costs.
- Upgrade the existing DWH solution to meet new business needs (e.g., add real-time analytics).
End-to-end data warehouse implementation
We help you:
- Consolidate disjointed data sources into centralized storage.
- Build a solid foundation for transparent analytics and reporting.
- Achieve high data quality.
- Ensure data security and compliance.
Data warehouse support and evolution
We help you meet newly arising analytics needs by:
- Reducing data latency.
- Solving performance and concurrency problems.
- Lowering storage and processing costs.
- Achieving DWH stability.
- Ensuring timely and quality data flow for business users with near-zero DWH downtime.
How Consulting Helps Reduce Data Warehouse Costs
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