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Data Management Services
Turn Your Data into a Strategic Asset with ScienceSoft
In data management since 1989, ScienceSoft helps its customers collect, organize, and store their data, achieve its high quality and full regulatory and security compliance. With a focus on industry specifics, we develop and enhance solutions to manage data throughout its lifecycle and in line with the goals of an organization.
About ScienceSoft
- Data analytics and data science services since 1989.
- Data warehousing and BI expertise since 2005.
- Big data services since 2013.
- A seasoned team of experts, including industry business analysts, solution architects, data engineers, and developers with 12–27 years of experience.
- In-house PMO and established project management practices to guarantee project success regardless of time and budget constraints, as well as changing requirements.
- Expertise in 30+ industries, including manufacturing, retail and wholesale, professional services, healthcare, financial services, transportation and logistics, telecommunications, energy, and others.
- ISO 9001 certified quality management system.
- ISO 27001 certification to assure the security of the customers’ data.
- Regulatory experts on board to ensure compliance with GDPR (for the EU), PDPL (for Saudi Arabia), HIPAA (for the healthcare industry) and other global, local, and industry-specific regulations.
Our Data Management Portfolio
16 results for:
ScienceSoft as a Reliable Data Management Partner
We commissioned ScienceSoft to build a flexible database with user interfaces for uploading and exporting data to access and manage our test data stored as time-based CSV files. ScienceSoft's experts promptly reacted to new solution requirements that appeared during the project without stalling its progress.
The invoicing system created by ScienceSoft automates data integration from different sources, invoice generation, 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.
bioAffinity Technologies hired ScienceSoft to help in the development of its automated data analysis software for detection of lung cancer using flow cytometry. Our project required a large amount of industry-specific methodology and algorithms to be implemented into our new software connected to EHR/LIS systems, which ScienceSoft's team handled well.
Data Management Components That We Cover Separately and in a Bundle
Whether you want assistance with a certain data management component or all of them, ScienceSoft can provide the required service scope.
Data governance
- Drawing up data governance standards and policies to ensure data availability, integration, quality, security, proper usage, etc.
- Evaluating the existing data governance standards and policies.
Data architecture
- Designing data architecture to govern how data is captured, integrated, stored, analyzed, and used.
- Auditing data architecture to align it with the enterprise strategy.
Consolidating data from disparate data sources with extract, transform, load (ETL) or extract, load, transform (ELT) processes and data virtualization.
Data quality management
Data cleansing activities, data enrichment and regular data quality assurance.
Data storage
Designing, implementing and supporting storage solutions for datasets of varying scale and format.
Reference and master data management
Enabling data consistency and quality across transactional and business intelligence systems with data profiling, data deduplication and standardization, etc.
Metadata management
Designing and populating metadata repositories with metadata to ensure localization of a data asset, data lineage, etc.
Data security
Setting up data security practices and regular BI and DWH risk assessment to prevent unauthorized data access and inappropriate data usage.
Data migration and backup
Moving your data from one system to another for ensured efficiency and security with preliminary data assessment, data migration automation, and data completeness evaluation.
How We Tailor Data Management Solutions to Specific Industry Needs
ScienceSoft has practical experience in 30+ domains, including healthcare, banking, investment, lending, insurance, manufacturing, retail & ecommerce, telecoms, transportation & logistics, and more.
Industry-defined capabilities
Having delivered hundreds of projects for every major industry, we know what data sources, software capabilities, and integrations will help our customers solve their industry-defined challenges.
Regulatory compliance expertise
We have in-house compliance experts who ensure compliance with both general and industry-specific regulations, including PCI DSS, HIPAA, FDA, GLBA.
Continuous growth
Our experts keep investing in their expertise to stay up-to-date with industry changes. We are ready to plan and deliver cutting-edge solutions that are fully in line with the latest domain trends.
Data Quality Standards We Target
When establishing data management for customers, ScienceSoft guarantees the following data quality characteristics:
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Consistency No data contradictions within one data store and across different data stores. |
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Auditability Data is accessible, and it is possible to trace the introduced changes. |
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Accuracy The information your data contains is reliable and error-free. |
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Timeliness Data represents reality within a reasonable period of time or in accordance with the corporate standards. |
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Completeness Data is sufficient for answering your business questions. |
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Uniqueness A data record with specific details appears only once in a database, no data duplicates are reported. |
Cooperation Models We Offer
Data management consulting
We are ready to guide you at any step of your data management initiative. Whatever expert assistance you need: choosing optimal techs, reliable TCO and ROI estimates, architecture (re)design, we'll provide you with actionable deliverables to make sure your data turns into a value-driving business asset.
Data management software implementation
Our business analysts, architects, and developers have the skills and expertise to build robust software that will ensure full-cycle data management, including data aggregation, cleansing, cost-efficient storage, and secure sharing. We'll also focus on future-proofing your solution to ensure its smooth evolution in case your goals and processes change.
Data management as a service
ScienceSoft will choose a cloud platform optimal for your case and configure it to your needs. We'll aggregate data from multiple sources, organize its optimal storage, implement data quality procedures, ensure 99.99% cloud service availability and complete security of your data both at rest and in transit.
Data management solution enhancement
Whether you have issues with your solution or want to upgrade it with new capabilities, we'll help you take your software to the next level of accuracy and functionality. You can also count on us to augment your internal team with the required talents.
ScienceSoft's Related Expertise to Maximize Data Management Value
Since 2005, we build BI solutions with ETL/ELT pipelines, DWHs, and multidimensional OLAP cubes to aggregate disparate data into a single point of truth. We also create sleek reports and interactive dashboards to drive faster interpretation of analytics insights.
Since 1989, we implement software that enhances BI features with advanced capabilities to identify trends and dependencies in data sets, perform root-cause analysis, build what-if models, and provide smart recommendations for processes optimization.
Since 2003, we deliver scalable systems that efficiently handle multi-source, complex data to ensure low-latency response to an unlimited number of concurrent user requests and enable analytics on petabyte-scale data.
ScienceSoft USA Corporation Is a 3-Year Champion in the Financial Times Rating
Three years in a row (2022–2024), the Financial Times has included ScienceSoft USA Corporation in the list of 500 fastest-growing American companies. This is the result of our dedication to driving project success despite any constraints and disruptions.
Tools and Technologies Used for Data Management
Examples of Data Management Challenges ScienceSoft Solves
For new implementations
Eliminate manual work
We automate data aggregation and quality assurance processes and let your teams focus on the tasks that can’t be efficiently addressed without human involvement.
Get rid of data silos
Aggregating disjoint company data into a single point of truth, we make sure you have a clear view of your processes and involved entities (e.g., customers, patients, partners).
Ensure regulatory compliance
We develop clear data management policies for data collection, storage, processing, and disposal. We also establish security mechanisms to prevent sensitive data disclosure and unauthorized access.
For existing solutions
Improve data processing speed
We audit your solution at all levels, including architecture, code, and hardware (for on-premises solutions), to identify possible reasons for slow response times. We also advise you on improvement steps (e.g., introducing load balancing or cashing, optimizing queries in accordance with database structure).
Enhance data quality
We perform a thorough assessment of your data to identify underlying issues and inconsistencies. To achieve the desired data quality, we develop quality-driving data management standards and implement tools for automated quality monitoring.
Enable integration with other systems
We make sure your solution smoothly incorporates data from all the required sources, including legacy software. We advise you on the steps to achieve data formats and file structure compatibility and help guarantee secure data exchange between the systems.
Data Management Costs
Data management costs depend on the service option and project complexity. Below, we list average prices for data management solutions implementation, consulting, evolution, and DMaaS.
- Data management consulting: $10,000–$100,000, depending on software complexity and the scope of the required deliverables (e.g., a feasibility study will be in the lower tier compared to architecture design).
- Data management implementation: $30,000–$1,000,000
- Basic data management solution: $30,000–$50,000
- Data management solution of average complexity: $50,000–$300,000
- Enterprise-wide data management solution with big data support: $300,000–$1,000,000
NB: Data management solution implementation brings up to 460% 3-year ROI with a payback period of 3 months.
- Data management evolution: $20,000–$1,000,000
- Improvement of 1 or 2 data management aspects: $20,000–$50,000
- Data management solution re-architecting: $40,000–$150,000
- Introducing an enterprise data platform with big data support: $30,000–$1,000,000
- Data management as a service: $4,000/mo - $14,000/mo for companies with small to average data complexity.
Calculate the Cost of Your Data Management Initiative
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