ScienceSoft Global
Healthcare
Finance
Data Warehousing Consulting Services
Since 2005, ScienceSoft has been helping companies across 30+ industries consolidate disparate data into highly automated, scalable data warehouse solutions that enable timely, accurate analytics and streamline enterprise-wide decision-making.
Data warehouse consulting is expert guidance on planning, implementing, supporting, and upgrading a data warehouse in accordance with an organization’s particular needs. ScienceSoft has deep expertise in traditional and cloud DWH technologies. Our proficiency is proven by official partnerships with Microsoft and AWS.
Why ScienceSoft
- Data analytics expertise since 1989.
- Experience in rendering data warehouse services since 2005.
- Designing and implementing business intelligence solutions since 2005.
- Big data consulting and implementation practice since 2013.
- 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 healthcare, insurance, investment, banking, lending, retail, ecommerce, professional services, manufacturing, transportation and logistics, energy, telecommunications, and more.
- Established project management practices to achieve project goals regardless of time and budget constraints, as well as changing requirements.
- 150+ testimonials from satisfied clients across multiple countries.
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-team workgroups to solve complex problems (e.g., related to data quality, master data management).
Our Clients Say
We first contacted ScienceSoft to get expert advice on the creation of the centralized analytical solution. After we got a clear project roadmap, we commissioned ScienceSoft to develop a part of the solution, covering invoicing. The system automates data integration from different sources and provides visibility into the invoicing process. We have already engaged ScienceSoft in supporting the solution and would definitely consider ScienceSoft as an IT vendor in the future.
We commissioned ScienceSoft to build a flexible database with user interfaces for managing our test data stored as time-based CVS files. ScienceSoft delivered a fully functioning solution regardless of the new requirements that appeared during the project. We are planning to extend the logic of our reports and dashboards and data processing options in our solution, and we’ll definitely be considering ScienceSoft as our partner in this initiative.
bioAffinity Technologies hired ScienceSoft to help in the development of its automated data analysis software for detection of lung cancer using flow cytometry. In addition to the solid technical expertise shown by ScienceSoft, its developers demonstrated a profound understanding of laboratory software specifics and integrations. We would recommend hiring ScienceSoft to anyone looking for a highly productive and solution-driven team.
Having expertise in various data storage solutions, like on-premises and cloud data lakes, data warehouses, and data lakehouses, we don’t promote any as a universal problem-solver. For instance, a data warehouse is excellent for BI and analytics needs, but it will definitely fail to provide a cost-efficient storage for multi-structured data. That is why, ScienceSoft’s best practice in data warehouse projects is to make sure that data is handled in an optimal way along all the stages, including data ingestion, raw storage, transformation, and aggregation. And we choose the best-fitting techs depending on multiple factors (e.g., data volume, complexity, and diversity) and customers’ unique processes.
Technologies We Use
Cloud data storage
- Microsoft Fabric
- Azure Cosmos DB
- Azure Blob Storage
- Azure Data Lake
- Amazon DynamoDB
- Amazon S3
- Amazon RDS
- Amazon Redshift
- Amazon DocumentDB
- Amazon Keyspaces
- MongoDB
Data warehouse technologies
- Microsoft SQL Server
- Microsoft Fabric
- Azure Synapse Analytics
- Amazon Redshift
- Amazon RDS
- Amazon Aurora
- Google BigQuery
- Oracle Autonomous Data Warehouse
- Snowflake
- PostgreSQL
- Teradata
Data integration
- SQL Server Integration Services
- Microsoft Fabric
- Azure Data Factory
- Apache Kafka
- Apache Airflow
- Talend
- Oracle Data Integrator
- Matillion
- Azkaban
- Informatica
- Panoply
- Apache NiFi
- IBM InfoSphere DataStage
Data visualization
- Power BI
- Microsoft Fabric
- Microsoft SQL Server
- Microsoft Excel
- Google Developers Charts
- Tableau
- Grafana
- Chartist.js
- FusionCharts
- DataWrapper
- Infogram
- ChartBlocks
- D3.js
- Oracle Business Intelligence
- MicroStrategy
- QlikView
- Sisense
- Kyubit Business Intelligence
Big data
- Apache Hadoop
- Apache Spark
- Apache Cassandra
- Apache Kafka
- Apache Hive
- Apache ZooKeeper
- Apache HBase
- Azure Cosmos DB
- Amazon Redshift
- Amazon DynamoDB
- MongoDB
- Google Cloud Datastore
Machine learning platforms and services
- Azure Machine Learning
- Azure Cognitive Services
- Microsoft Bot Framework
- Amazon SageMaker AI
- Amazon Transcribe
- Amazon Lex
- Amazon Polly
- Google Cloud AI Platform
Machine learning frameworks and libraries
Frameworks
- Apache Mahout
- Apache MXNet
- Caffe
- TensorFlow
- Keras
- Torch
- OpenCV
Libraries
- Apache Spark MLlib
- Theano
- Scikit Learn
- Gensim
- SpaCy
Cloud services
- Amazon Web Services
- Microsoft Azure
- Google Cloud Platform
Costs & Pricing Models
The cost of data warehouse consulting services may range from $10,000 to $50,000. The exact number will depend on DWH complexity and the type of expected deliverables (e.g., architecture design and toolset selection will be in the higher pricing tier compared to recommendations on cost optimization). Use our online calculator to get a tailored estimate.
During cost estimation, we carefully research our clients’ needs and offer a pricing model with an optimal cost-to-benefit ratio.
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.
Estimate the Cost of Your DWH Project
Please answer a few questions about your business needs, and our experts will return with a ballpark cost estimate for your case.
Thank you for your request!
We will analyze your case and get back to you within a business day to share a ballpark estimate.
In the meantime, would you like to learn more about ScienceSoft?
- Project success no matter what: learn how we make good on our mission.
- Experience in data management and analytics since 1989: check what we do.
- 4,200+ successful projects: explore our portfolio.
- 1,400+ incredible clients: read what they say.
How Consulting Helps Reduce Data Warehouse Costs
Choose Your Service Option
Data warehouse design / migration / optimization consulting
We offer advisory support or complete project management to help you:
- Business case, recommendations on optimizing data warehouse implementation and operation costs.
- 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).
We help you:
- Consolidate disjointed data sources into centralized storage.
- Ensure uninterrupted data flow via planning and implementing the required integrations with other systems (e.g., with an enterprise data lake).
- 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.
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Providing complimentary services (e.g., AI/ML services, data lake consulting, BI and visualization services).
