Address digital transformation and data modernization challenges to leverage data as a strategic asset and become data-driven. An organization’s data maturity is key in unleashing the effectiveness in realizing the organization’s data value in a sustained manner.
Our strategy and advisory services take into account the complexity and scale faced by data leaders in their pursuit of achieving the goals and objectives of the Federal Data Strategy. Here, we assist agencies at any step along the data strategy roadmap. Our services bring together the Data Management Maturity (DMM) and Data Management Body of Knowledge (DMBOK) practices, certified data practitioners, and knowledge and experience from federal agency engagements.
- Data Maturity Assessment – Founded in CMMI’s Data Maturity Model we provide objective assessment of an organization’s maturity. This results in a maturity score, findings, and roadmap recommendations.
- Data Modernization Readiness – Evaluation of the organization’s ability to implement practices to achieve and operate in the future data state. This results in a roadmap, blueprint, and action plans.
- Data Management Maturity – Approaches, plans, and models to build enterprise data management capabilities across Data Strategy, Governance, Quality, Platform, and Operations.
Traditional methods of siloed data stores, data duplication and inconsistent or missing data lineage and lack of trust in data pose a huge opportunity cost to organizations and will not deliver to the velocity or relevancy of the business goals.
Modern data platforms accomplish the consistent data management, curation, discovery and self-service enablement for access, analytics and integration with very little or no data duplication. Independent scalability of each service across the data lifecycle is a key value of modern data platforms.
Our “Modern Data Platform” is a set of best practices comprising technologies and processes to effectively use and manage data, while reducing the effort and complexity of managing the platform itself. These platforms are modular, using the services & products based on needs and scales to meet demand while optimizing cost.
Our data experts provide strategic planning and guidance to address the organization data maturity and data processes along with the core data platform itself. Our proven structured approach and utilizing industry standard models, frameworks and methodologies, coupled with our innovative toolkits and utilities provides accelerated delivery to outcomes.
Data applications allow rich analysis and simple presentation by using different data products. These offer programmatic capabilities with a low code/no code approach which aid in democratizing data science and analytics for the user community.
Traditionally, the data lifecycle from ingest to analytics was dealt with in silos. As data volumes that needed to be handled for analytics exploded, the challenge of data delivery for dashboards was addressed by DataOps. However, the AI/ML part of the process remained in a silo. Here huge amounts of time was spent on data preparation. After analysis by data scientists, the results again needed to be passed to dashboard/application developers adding time to the eventual use of data for decision making.
Now data applications provide data scientists and analytics developers a means of self-service to make their AI/ML and analytics data sets, models, and visualizations available without delay to end users. Reducing overall cost of operations through low code tools is another benefit of data applications.
We provide an open-source low code platform for developing and delivering data analytics available in your on-prem or Cloud environment. Creating data applications to seamlessly support your data analytics needs.
Modernize data in tandem with digital transformation. Legacy databases can be expensive. Modernization must consider purpose built databases for Massively Parallel Processing, time series, NoSQL, and streaming. Modernize effectively by identifying the best value with the right fit data technologies.
Successful transformations require the ability to confidently and securely move data into modern data technologies is needed. Data volumes and complexity require data migration capabilities that address all these considerations.
Data migration is a set of services, tools, and best practices that allow the movement of data from the source or legacy systems to target modernized data stores. These include ETL/ELT, data assessment and validation, data quality check and Change Data Capture services for planning smooth cutovers without data loss for your modernized systems and data stores.
We bring in substantial field experience in large volume and legacy database migration. Our systematic approach utilizes assessment and planning toolkits to provide fine grained database features and configuration assessments along with data volume estimations. Our ML based toolkit even assesses PII data to ensure caution and appropriate migration preparation. Our sound assessment enables us to deliver a solid and clear plan for the migration, parallel run and delta refreshes, and finally cut over.
