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IndiaOverview
Data Complexities in the New Data Economy
The distributed nature of data origination
The growing personas of data stakeholders and their needs
The demand for more actionable insights, beyond reports
The rise of big data with multiple data types
The use of multiple data platforms
The increasing need for real-time or near-time data currency
The management of 1000s of data feeds
The need for speed to market
Why DataOps?
DataOps helps bring order to chaos, solving the critical challenge of transforming data into business value. Without a DataOps solution, data management issues will persist and hinder any efforts to unlock data’s full potential. Delays in time-to-market and monetization will continue, yet the associated costs are avoidable with the right approach.
Advanced-Data Analytics
Advanced-Data Analytics
Enhances the use of multifaceted examination strategies. New AI algorithms designed to process information through all phases of the examination are gaining traction
Dramatically Lower Data Storage & Ops Costs
Dramatically Lower Data Storage & Ops Costs
Accelerates the creation of data services & assets at significantly lower costs by reducing storage infrastructure and data operations expenses, while boosting productivity and efficiency
Execution Without Regulatory Risks
Execution Without Regulatory Risks
Establishes consistent data governance policies that enable rapid and secure data flow
High Performance
High Performance
Delivers business-critical data quickly, utilizing high-performing processors for complex logic
Self-Service Analytics
Self-Service Analytics
Provides a reporting tool to view analytics in real-time
Private workspaces for teams Fully automated env. setup and access to data
Virtualized Datasets
Updated automatically in background, transparent to data consumers Unified data helps find data errors & provide reports
Privacy and Security
Role/policy based secure access to the encapsulated data pods Each service communicates securely with other services
Secure access as per org. governance and compliance rules
Move from dev to prod using DevOps process
Create Personal Space
Data pods create unique environment for each item Data pods capable of hosting microservices, data mounts (VDS)
Integrate DataPod to CI/CD
Infrastructure updates can be easily accommodated Provision pipeline to run through different environments
OFFERINGS
Our offerings and services help organizations evolve their data management strategies to manage data at scale while aligning with real-time market changes.
A key objective of enterprise data strategies is to efficiently utilize data assets to drive an organization’s vision. DataOps plays a crucial role in executing this strategy by streamlining the entire data lifecycle. Our solutions are designed to enhance and optimize your approach, ensuring better results.
Duplicating or migrating data to a data lake or centralized data warehouse is often time-consuming and unsecured. However, with data virtualization, tasks such as data integration, sanitization, policy enforcement, and access control are defined within the virtual layer. These processes are then applied to the data as it is retrieved from the source store. Innova’s service facilitates automatic background updates, provides transparency for data consumers, identifies data errors, and delivers reports with unified data.
These environments provide unique workspaces for each team, hosting microservices and data mounts with capabilities for auto-scaling.
We enable the delivery of trusted data from disparate sources to support a business-ready data pipeline for DataOps. Our scalable, multi-cloud solutions help businesses accelerate their journey to AI-powered transformation. Key benefits include:
Dramatically improved data quality
Real-time data-governance
Accelerated automation
Improved predictive fraud capabilities
Personalized customer experiences
DevOps enables organizations to adopt agile software delivery methodologies like continuous integration (CI) and continuous delivery (CD). With CI/CD, we adapt continuous automation and monitoring throughout the software delivery lifecycle—from build, integration, and testing to delivery and deployment.
Framework for DataOps
Ready to Innovate with Us?