Enterprise Data Management Services Platforms
Manage, Transform, govern, control, improve and exploit data for beneficial business outcome.
XenonStack Recommends
Driving innovation through Enterprise Data Management
EDM implementation services assist organizations in managing and handling many types of data and formats, from legacy data to the most recent forms of internal and external sources. Build an effective enterprise data management transformation strategy that reduces modern architecture's complexity and automates operations by providing easy access to business users.
Data Governance
The main Fundamental purpose is to define policies, procedures, roles, tasks and ownership in the whole organisation. Defining the key business metrics for data consistency, quality, and trustworthiness.
Data Architecture and Security
Functional data architecture with data security helps to structure and secure the operational environment in which the data will be integrated, stored and processed.
Data Warehousing and BI
Transforming input data into a suitable format for creating reliable insights. Enabling business users with insights to make intelligent and data-driven business decisions.
Consolidate Business data with Data Management Strategy
Every enterprise has to define the data strategy based on its needs and business objectives. Ensuring the Data reliability and lineage to produce precise insights
Enterprise Data Management (EDM) offerings for an agile and data-centric organization
Master data management (MDM)
MDM solutions are driven around reducing redundant, inconsistent data and providing a unified view of insights and information.
Data Management Strategy
AI-driven automated discovery, classification, and metadata management solutions for businesses.
Real-Time Ingestion and Processing has driven capabilities to reduce downtime and latency, and gain visibility into the infrastructure health.
Create governance and security models for stewards to build a single source of truth to keep the organization agile.
Empowering AI and Intelligence-driven businesses. End-to-End BI Implementation and Consulting Solutions to facilitate data-driven decision-making.
Google Cloud's Database Solution
Deliver the best experience to customers with Reliable, global scale, and open standards GCP solutions.
AWS Analytics Services
Reinvent business with data from its movement, storage, creation of modern architecture, analytics, log and streaming analytics, BI, and ML; AWS offers all services.
Azure End-to-End EDM Services
Manage Data Assets with Business Glossary, Dictionary, Data modeling, and discovery, Source connectivity, and more with Azure.
Rapid access to High-Quality and Business-ready Pipelines and Insights
Data Integration architecture solutions empower enterprises with end-to-end lifecycle management
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Architecture and Best Practices of Master Data Management
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Why Modern Enterprise Data Strategy?
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Implementing DataOps Architecture in AWS, Azure, and GCP
Adapt and respond to change faster and effectively by managing enterprise data
XenonStack provides assessments, strategy and implementation for effective and flexible Enterprise Data Management .
Enterprise Technology
Banking and Finance Sector
Healthcare
Education
Transportation
Retail
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Key Enablers
Enablers for Accelerating Digital Transformation
Enterprise AI
Big Data Engineering
Generative AI
DevOps
Data Science
Data Visualization
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Overcome the challenges posed by complex mass-scale enterprise IT
Overcome the challenges posed by complex mass-scale enterprise IT
Leveraging DevOps Principles for Better Analytics
Leveraging DevOps Principles for Better Analytics
Streaming Analytics
Data Catalog
Data Lineage
Data Denormalization
Streaming Analytics
Streaming analytics is continuously processing and analyzing data records rather than in batches. Streaming analytics is helpful for data sources that send data in small sizes in a steady flow as the data is generated.
Data Catalog
Data Catalog provides a single self-service environment to the users, helping them find, understand, and trust the data source.
Data lineage is the process of understanding, documenting, and visualizing the data from its origin to its consumption.
Data Denormalization
Denormalization is a technique in which we add the duplicate data to one or more table. With the help of this, we can avoid costly joins in a relational database.