Data Science Services

Embrace a data-centric culture.

Just as Agile has revolutionized software development, technology-driven Big Data capabilities are driving fact-based optimization decisions, future business initiatives, and marketing direction – while itself becoming a source of revenue.  Fully exploiting “Data as an Asset” requires introducing new operational structures, tools, and skills – while using traditional assets in new ways. Cue SQA’s Data Science Services.

Data Management Services

Data management is a required discipline in any IT organization, and its maturity strengthens the foundation of the business itself.  Big Data capabilities are heightening the importance of effective and efficient data management, as the discipline must be prepared to manage huge data sets while supporting increased development velocity and reduced time-to-market through timely information for decision making.  “Data as an Asset” requires a data governance mindset best realized through a DataOps approach based on DevOps principles.

Our Data Management Services include:


  1. Designing a tailored, fit-for-purpose data governance model

  2. Implementing capabilities that enhance data architecture, modeling and design, automated data delivery, quality, storage and batch operations, integration and interoperability, warehousing, reporting, analytics/BI, quality and security

  3. Building a DataOps pipeline with right-priced tools that integrate with your enterprise delivery lifecycle

  4. Embedding automated EDI/ETL testing in the DataOps pipeline to enable a continuous data quality capability

  5. Evaluating existing data structures to ensure that they are “fit for purpose” – especially from an end user perspective – and provide high scalability and responsiveness

  6. Designing and enabling the right balance of canned and user-defined reporting capabilities – again with performance and scalability in mind

Data Quality Services

Data equals trust.  Decisions can only be made with confidence when decision makers believe and understand the data on which they are basing those decisions. Data quality establishes the foundation of trust that makes data science actionable.  In many regulated industries, the ability to demonstrate the provenance of data (how it was obtained and manipulated and that it is complete, consistent and accurate) is an indispensable component of any successful initiative.

Our Data Quality Services include:

  1. Creating standard Data Definition Libraries to regularize use of data-related terms – thus creating a common “language” for the Enterprise

  2. Creating mechanisms to evaluate data quality at intake points and correct quality issues or exempt the data for human evaluation – rather than allowing it to contaminate existing validated data sets

  3. Integrating automated data validation steps into the DataOps pipeline, with automated alerting and logging

  4. Building the capabilities to track and visualize Data Provenance

  5. Installing security and administrative safeguards to prevent and detect unauthorized or undocumented access or changes to data state

  6. Building and/or training Data Quality Teams with the tools, processes and skills to address the root causes of poor data quality rather than simply correcting detected issues after the fact

"Thank you again for all that your organization did to support the badly needed changes in testing, agile and process improvements. You and your team did make a difference." - Dan Sheehan, Chief Information Officer, Beacon Health Options

How We Do It

Empower Data Management, Business Analytics/Business Intelligence and Data Quality teams with improvement roadmaps, formal classroom training, hands-on coaching and pilot programs.

Evaluate the current Data Management strategy, practices and structures against present and future business need, and design and implement an approach to Data Management that is right for the business.

Provide experienced, local consultants who implement scalable “fit for purpose” Data Governance capabilities.

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