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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.

Data Management Services - ScienceSoft
Data Management Services - ScienceSoft

About ScienceSoft

  • Data analytics and data science services since 1989.
  • Data warehousing and BI expertise since 2005.
  • Big data services since 2013.
  • Seasoned team of experts, including industry business analysts, solution architects, data engineers, and developers with 12–27 years of experience.
  • 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

Start Your Data Management Journey Here!

ScienceSoft’s team is ready to help you resolve any data management issues you’ve encountered with comprehensive data management consulting and implementation services.

ScienceSoft as a Reliable Data Management Partner

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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:

Consistency

No data contradictions within one data store and across different data stores.

Auditability

Data is accessible, and it is possible to trace the introduced changes.

Accuracy

The information your data contains is reliable and error-free.

Timeliness

Data represents reality within a reasonable period of time or in accordance with the corporate standards.

Completeness

Data is sufficient for answering your business questions.

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.

Go for consulting

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.

Go for implementation

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.

Go for DMaaS

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.

Go for evolution

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.

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.

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 strucutres compatibiltlity 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

Please answer a few questions about your data management needs to help our experts calculate your quote quicker.

*What is your industry?

*What describes your situation best?

*What services are you interested in?

What are your primary data sources?

*Do you have any preferences for the environment?

*Do you have any tech stack preferences, incl. cloud platforms?

*At what level of maturity is your current data management?

What services are you looking for?

?

E.g., adding solution components, improving reports, rearchitecting the solution, adding advanced capabilities like machine learning.

?

Databases, clouds, programming languages, etc.

*At what level of maturity is your data management solution?

What are your primary data sources?

?

If you don’t know the data size in TB, describe it as the number of data records: e.g., orders, payments, cases, customer interactions, sensor readings.

?

You can describe the volume in TB or percentage.

*Are there any compliance requirements for your solution? Check all that apply.

Almost done!

Please let us know where we should send your estimate. Our experts may need to ask a few extra questions to calculate a precise quote for your case.

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